submitted to the university of lucknow for the...

THESIS

SUBMITTED TO THE

UNIVERSITY OF LUCKNOW

FOR THE DEGREE OF

IN

By

BOTANY

2014

DEPARTMENT OF BOTANY

UNIVERSITY OF LUCKNOW

LUCKNOW-226007

AND

Doctor of Philosophy

I DEDICATE THIS THESIS TO THE

ALMIGHTY GOD

WHO

GAVE ME STRENGTH AND SERENITY TO

COMPLETE THIS STUDY

CERTIFICATE

This is to certify that the thesis entitled “Identification of alternative plant parts of

some important bark drugs for sustainable harvesting” submitted for the award of

degree of Doctor of Philosophy in Botany, is bonafied work of Ms. N. Manika which

has been carried out under our joint supervision. She has fulfilled all the

requirements, for the degree of Doctor of Philosophy in Botany, regarding the

nature and prescribed period of work. The work included in the thesis is all

original, unless stated otherwise. We have checked data from time to time and are

satisfied about their genuineness.

Dr. (Mrs.) Nalini. Pandey Dr. G.D. Bagchi

Associate Professor Ret. Chief Scientist

Department of Botany Department of Botany and Pharmacognosy

University of Lucknow Central Institute of Medicinal and Aromatic

Lucknow-226007, India Plants, Lucknow-226015, India

(Supervisor) (Co-Supervisor)

Acknowledgments

I bestow my heartfelt sense of gratitude and appreciation to my supervisor, Dr. Nalini

Pandey, Associate Professor, Department of Botany, University of Lucknow for her

valuable guidance, keen interest and consistent support that was indispensable to carry

out my PhD work as well as for allowing me to focus my research towards the relatively

unexplored field. Her truly scientific intuition was an oasis of ideas and passion for me,

which exceptionally inspired and enriched my growth as a student and a researcher.

I feel greatly privileged to express my sincere gratitude and thankfulness to my co-

supervisor Dr. G.D. Bagchi, Ret. Chief Scientist, Department of Botany and

Pharmacognosy, CSIR-CIMAP, Lucknow, under whose erudite guidance, this

investigation has been carried out. It was his able supervision, advice and guidance from

the very early stage of this research which has resulted in fruitful outcome. I feel bereft of

words to acknowledge his contribution to shape my academic perceptivity.

I am highly thankful to Prof. A.K. Tripathi, Director, CSIR-CIMAP, Lucknow, for the

facilities, encouragement and moral support.

I express my genuine gratitude to Prof. Y.K. Sharma, Head, Department of Botany,

University of Lucknow for being very supportive and giving me attention and time.

I am highly grateful to Dr. N.K. Srivastava, Senior Principal Scientist and Head,

Department of Botany and Pharmacognosy, CSIR-CIMAP, Lucknow, for accepting me

as a student after superannuation of Dr. G.D. Bagchi. Above all and the most needed, he

provided me unflinching encouragement and support in various ways.

With great pleasure, I confer my sincere thanks to Dr. M.M. Gupta, Chief Scientist and

Dr. R.K. Verma (Department of Analytical Chemistry, CSIR-CIMAP), who accepted me

in their lab and for sharing their knowledge to drive scientific exploration.

It is immense pleasure to express my heartfelt gratitude to Dr. D.U. Bawankule, Scientist,

Department of Molecular Bioprospection, CSIR-CIMAP for giving me the opportunity to

take on this project in his lab, and showed enthusiasm and interest in my work even if I

started with the very basics of pharmacology.

I am thankful to Dr. S.C. Singh (Technical officer), Mr. Govind Ram and Mr. Sabajeet

Chaubey for their help rendered in laboratory work during the thesis.

More specific thanks are due to Dr. Claire Delvaux, Royal Museum for Central Africa,

Benin, who enthusiastically replied to my queries regarding bark regeneration.

I cannot thank enough to Dr. M.P.S. Negi, Central Drug Research Institute, Lucknow, for

the help rendered regarding statistical analysis of the enormous data.

The financial assistance rendered by Council of Scientific and Industrial Research

(CSIR), New Delhi in form of CSIR-SRF is deeply acknowledged. The support provided

by the HRD cell of CSIR-CIMAP is also highly accredited.

Over the time it took to write this thesis, a number of people encouraged, supported, and

influenced me. I am especially thankful to those who consistently encouraged me

throughout the work. Thus, special thanks go to my friends and co-workers (I am sure

that you will recognize yourself) for their support and cooperation during my research

work.

I would like to thank the people involved in the field-work. In this respect, I do have to

thank Mr. Anil Yadav, who always carefully drove me during the forest experiments.

I owe a great debt of gratitude to my parents; my father Mr. N.K. Pandey and mother

Mrs. Meenakshi Pandey for educating me to this level and all their support. Mum and

Dad, I say God richly bless you for all that you have been doing for me. I also give

special thanks to my siblings (Neetika and Utkarsh) for being so loving and supportive

during all the ups and downs that this journey has brought.

Above all, I would like to thank God, the Almighty, for having made everything possible

by giving me strength and courage to do this work.

Place: Lucknow (N. Manika)

Date:

TABLE OF CONTENTS

Acknowledgments

Abbreviations

Chapter 1: General Introduction

General introduction 1-4

Medicinal Plants: The Imperative NTFP 4-5

Conservation: Challenges and Concern 5-7

Why conserve and restore tree species 7-12

Chapter 2: Review of Literature

1. Bauhinia variegata L. 13

1.1. Botanical description 13

1.2. Geographic distribution 14

1.3. Phenology 14

1.4. Phamacognostical studies 14

1.5. Ethnobotanical/ Ayurvedic uses 15

1.6. Phytochemistry 16-17

1.7. Pharmacological potential 17-21

2. Oroxylum indicum Vent. 22



2.3. Phenology 23

2.4. Phamacognostical studies 23-24

2.5. Ayurvedic/Ethnobotanical uses 24



3. Holarrhena pubescens Wall. ex G.Don 31



3.3. Phenology 32

3.4. Phamacognostical studies 32-33

3.5. Ethnobotanical/ Ayurvedic uses 33



4. Terminalia arjuna (Roxb.) Wight and Arn. 38


4.2. Natural Habitat 38

4.3. Phenology 38

4.4. Phamacognostical studies 38

4.5. Ayurvedic/Ethnobotanical uses 39



Chapter 3: General Material and Method

1. Collection of the plant materials 45

2. Herbarium preparation and identification 45

3. Processing 45

3.1. Drying of the plant materials 45-46

3.2. Powdering 46

3.3. Extraction 46-47

4. Chemicals and reagents 47

5. Preparation of standard solution 47

6. High Performance Liquid Chromatography (HPLC) analysis 48

6.1. Bauhinia variegata 48-49

6.2. Oroxylum indicum 50-51

6.3. Holarrhena pubescens 52-53

6.4. Terminalia arjuna 54-55

Chapter 4: Ecological responses to bark harvesting in medicinal tree

species

1. Introduction 56-59

2. Materials and methods 59

2.1 Study area 59

2.2 Harvest and measurement design 59-64

3. Statistical analysis 62

4. Results 65

4.1. Bauhinia variegata 65

4.1.1. Edge augmentation 65-72

4.1.2. Sheet growth 73-80

4.1.3. Agony shoots 81

4.1.4. Correlation and regression 81-83

4.2. Oroxylum indicum 84





4.3. Holarrhena pubescens 103

4.3.1 Edge augmentation 103-110




4.4. Terminalia arjuna 122





5. Discussion 141-143

Chapter 5: Assessing the effect of storage on bio-deterioration of

secondary metabolites in crude herbal drugs



2.1. Plant material 145-146

2. 2. Preparation of standard solution 146

2.3. Chromatographic analysis (HPLC) 146

2.4. Statistical analysis 146

3. Results 146

3.5.1. Bauhinia variegata 147-154

3.5.2. Oroxylum indicum 155-170

3.5.3. Holarrhena pubescens 171-174

3.5.4. Terminalia arjuna 175-178


Chapter 6: Testing the suitability of plant part substitution method

for sustainability of tree species



2.1 Plant material and sample preparation 182

2.2 HPLC analysis 183

2.3 Pharmacological potential 183

2.3.1 Bauhinia variegata and Oroxylum indicum (anti-inflammation) 183-184

2.3.2 Holarrhena pubescens (Antibacterial assay) 184

2.3.3 Terminalia arjuna (Hypolipidemia) 185

2.4 In-vitro cytotoxicity assay 185-186

2.5. Statistical analysis 186

3. Results 186

3.1 Bauhinia variegata 186

3.1.1 Chemical analysis 186-187

3.1.2 In-vivo anti-inflammatory activity 187-188

3.1.3 Cytotoxicity 188

3.2 Oroxylum indicum 188

3.2.1 Chemical analysis 188-189

3.2.2 In-vivo anti-inflammatory activity 190


3.3 Holarrhena pubescens 191

3.3.1 Chemical analysis 191

3.3.2 Anti-bacterial activity 191-192


3.4 Terminalia arjuna 192

3.4.1 Chemical analysis 192

3.4.2 In-vivo hypolipidemic activity 192-193



Chapter 7: Effect of phenology and temporal variation on bioactive

secondary metabolite concentration within tree species



2.1. Plant material 206

2.2. Secondary metabolites 207

2.3. Preparation of standard solution 207

2.4. Chromatographic analysis (HPLC) 207

3. Statistical analysis 207

4. Results 207-213

4.1. Bauhinia variegata 214-217

4.2. Oroxylum indicum 218-221

4.3. Holarrhena pubescens 222-223

4.4. Terminalia arjuna 224-225


Chapter 8: General Conclusion and Summary 229-235

Bibliography 236-264

Abbreviations

NTFPs Non Timber Forest Products

FAO Food and Agriculture Organization

WHO World Health Organisation

d.b.h. Diameter at breast height

CBD Convention on Biological Diversity

SFR State Forest Report

FRLHT Foundation for Revitalisation of Local Health Traditions

PP Polypropylene

PS Polystyrene

HPLC High Performance Liquid Chromatography

HCL Hydochloric Acid

TFA Trifluoroacetic Acid

PDA Photo Diode Array

LC Liquid Chromatography

LOD Limit of Detection

LOQ Limit of Quantitation

RP Reverse Phase

RSD Relative Standard Deviation

ICH International Conference On Harmonization

v/v Volume/ volume

rpm Rotation per minute

CAGR Compound Annual Growth Rate

SFM Sustainable Forest Management

MIC Minimum Inhibitory Concentration

MBC Minimum Bactericidal Concentration

GAP Good Agricultural Practices

CHAPTER 1

General Introduction

1

GENERAL INTRODUCTION

Forests are intricate ecosystems competent of providing an extensive range of

economic, social and environmental benefits, which are indispensable for human life

and play several roles in local, national and global progress that are subjected to

invariable advancement and change (FAO 1995a). Over the time, although forests

stood the same, human insight of forests and utilization of forest resources have been

shifting constantly (Wang 2004). Forests have played key roles in the lives of people

by providing a diversity of valuable forest products for numerous benefits (Kala

2004). They have been a source of timber and non-timber products without clear

domination for a particular group of stakeholders. In 1970s, recognition of the critical

role of forests in the life of rural smallholders and local communities refocused

attention on multiple values of the forest and stakeholders (Garcia-Fernandez et al.,

2008). Now it is highlighted that the importance of each different user group must be

clearly understood before making interventions (FAO 2006). As evident, there are

numerous roles which forests play for human utilization, there occurs a concern about

this evolving nature and this concern resulted in nations of the world to adopt a set of

non-legally binding principles on the management, conservation and sustainable

development of all types of forests (Heissenbuttel et al., 1992). Basically forests

provide timbers and non timber forest products (NTFPs) and in the past, policy

makers, forest economists and foresters have viewed forests primarily as a source of

national revenue with timber as the dominant product (Tewari 1994; Tewari and

Campbell 1995) where the harvesting of timber is a planned, exogenous disturbance

(Attiwill 1994) by human. Non-timber forest products (NTFPs) consist of goods of

biological origin other than wood that are derived from forests, the category “NTFP”

is broad, encompassing many different kinds of products and production systems in a

wide range of social, economic and ecological contexts for instance edible nuts, fruits,

herbs, spices, condiments, aromatic plants, resins, gums, fibres, animal products and

medicinal plants (FAO 1999). NTFPs have been harvested by human population for

subsistence use and trade over thousands of years (Ticktin 2004). In recent years,

there has been a growing appreciation of the importance of non-timber forest products

(NTFPs) and the role they play in the socio-economic wellbeing of rural communities

and other stakeholders (Akhter et al., 2008; Croitoru 2007; Cunningham 2001; Delang

2006; FAO 1995b, 1997; Hiremath 2004; Neumann and Hirsch, 2000; Peters 1994;

2

Shackleton et al., 2007, Sheil and Liswanti, 2006; Ticktin 2004; Vermeulen 2009;

Walter 2001). The harvesting of NTFP from natural forests is a customary subsistence

activity of communities inhabiting forests around the world (Ticktin 2004).

Historically, NTFPs were usually considered to be of little importance, a status

reflected in their designation as „minor‟ forest products. Much of their use were seen

as being primarily of only local interest, and such commercial exploitation was

associated with lack of capital and technology, and often with exploitative use of

labour (Homma, 1992).

However, during the last few decades there has emerged growing interest in attributes

of NTFPs that appeared to be relevant to the growing focus on rural development and

conservation of natural resources (Arnold and Perez, 2001). It was primarily

demonstrated by Peters et al. (1989) that NTFPs not only yield higher net revenues

per hectare in comparison to timber but could also be harvested with noticeably less

damage to the forest. Later on, Godoy and Lubowski (1992), Myers (1988) and

Vodouhe et al. (2008) supported the study. NTFPs play a pivotal role in the socio-

economic wellbeing for millions of people, not only from forest fringe communities

but also for other stakeholders (Mamo et al., 2007). Approximately 70-80% of the

world‟s population still resorts to herbal medicines for their healthcare needs resulting

in faster growing herbal sector (Hamilton 1992).

However, the extraction and commercialization of NTFPs were recognized as a

profitable contrivance for economic and rural development. Nevertheless, with time,

it was observed that NTFP harvesting endure some factors which negatively influence

their survival over time. The most important factor was their harvest from wild

without control on harvesting quantities and area of harvest (Cunningham 1993; FAO

2005; Hamilton 1992; Kuipers 1995; Lange 2006). Overexploitation due to growing

demand in local, national and international markets (Cunningham 1993, 1995;

Kuipers 1995; Lange 2006; Ticktin 2004) and less income of local collectors

(Vodouhe et al., 2008) were the important reasons and lastly, the unsustainable

management of resources which prevents sustainable harvesting of NTFPs in long run

(Peters 1994; Ticktin 2004). As it was already an established livelihood practice,

government and non-government organisations began the promotion of commercial

exploitation of NTFPs, as a strategy able to contribute to forest conservation and

3

poverty alleviation (Arnold and Pérez, 2001). Over the years, this practice increased

and exploitation became common. Later, Peters et al. (1989) proposed that these

products can also be harvested with considerably less damage to the forest than timber

exploitation. Further, it was established that the intensity of subsistence harvesting as

traditionally practiced by forest peoples for thousands of years, was usually lower

than that of industrial extraction and that the regular extinction of a plant species over

the time was rarely a visible trend (Delvaux 2009). Subsequently, commercial

harvesting guided to the rising over-exploitation of species throughout the world and a

new concept became evident which projected for restoring the natural symmetry with

sustainable harvesting. This method implies to the harvest of forest products in such a

way that the harvest had no long-term harmful effect on the reproduction and

regeneration of the population being harvested (Hall and Bawa, 1993). The multi-use

forest management for timber and non-timber forest products is envisioned as a

promising and more balanced alternative to the timber-dominated strategy (Garcia-

Fernandez et al., 2008). NTFP gathering usually affects the genetic diversity of the

population being exploited, especially when harvests are flowers or fruits that show

differential traits resulting in different degrees of pressure. In recent years, finally,

NTFPs gained much attention from the conservation world to be sustainably

harvested to avoid their overexploitation.

The estimated total value of the most economically important NTFPs in world trade is

about $11 billion annually (Wilkinson and Elevitoh, 2003). It is estimated that of the

6.2 billion people on the planet, 25 percent depend to varying degrees on the forest's

resources for their livelihood and 350 million people living in or near dense forest

depend highly on them for their subsistence or livelihood (Killman 2003). FAO

estimated that NTFPs are capable of generating 4 million man-years of employment

annually (FAO 2002). The global trade value of NTFPs has increased from US$9

billion in 1996 to US$14 billion in 2005. Though the increase in global trade from

1996 to 2000 (US$9.4 billion) was marginal (4%), from 2000 to 2005 the increase

rose by 50% (Based on UN Comtrade data).

Indian forests contribute significantly to meet the demand for fuelwood, fodder, and

non-wood forest products and the major portion of all wood harvested (92%) is for

fuelwood for cooking. Additionally, forestry and logging contributes to 1.2% of

India's GDP (Economic Survey, Ministry of Finance, 2011). The Indian forest

4

products industry had total revenue of $65,844.6 million in 2011, representing a

compound annual growth rate (CAGR) of 5.5 percent between 2007 and 2011.

Industry consumption volumes increased with a CAGR of 0.2 percent between 2007-

2011, to reach a total of 355.4 million cubic meters in 2011. The performance of the

industry is forecast to accelerate, with an anticipated CAGR of 7.7 percent for the

five-year period 2011 - 2016, which is expected to drive the industry to a value of

$95,467 million by the end of 2016 (http://store.marketline.com)

Medicinal Plants: The Imperative Non Timber Forest Product

Plants have been used as a source of drugs since time immortal, as traditional

preparations in the history of all civilizations. Traditions of plant-collecting and

knowledge on plant-based medications have been handed down from generation to

generation (Maydell 1996) and people were completely dependent on medicinal herbs

for the prevention and treatment of different types of diseases. With time, man

discovered many more plants and their active principal compounds to cure various

ailments and consequently, pharmaceutical industry began to concentrate their

research for using plant molecules as base drug for semi-synthetic medicines. But, as

totally synthetic drugs came into markets, the interest in natural medicines became

suppressed for a long period of time. However, at the end of 1980s, there was a

renewed interest of the pharmaceutical and scientific communities in herbal remedies

which directed to the increased awareness and urgent need to develop new effective

drugs, from traditionally used medicinal plants (Taylor et al., 2001). The rising

recognition of medicinal plants is due to several reasons, including escalating trust in

herbal medicine. Allopathic medicine may cure a wide range of diseases; yet, its high

prices and side-effects are causing many people to return to herbal medicines which

have fewer side effects (Kala 2005). Rural communities harvest mostly the wild

medicinal plants for their own health care, but this wild harvesting was not

detrimental to plant survival as the quantity collected tended to be small and also most

of the material collected came from the more common varieties. This is not true for

pharmaceutical, phyto-pharmaceutical companies and also the local markets which

need an increasing amount of specific medicinal plants (Delvaux 2009). For instance

the biological tests of taxol used more than 3.25 tons of bark between 1977 and 1987

(Chevassus-au-Louis 2000). A risk of over-harvesting and depletion of the plant

resources occurs by this kind of explorations. Pharmaceutical companies all over the

5

world have investigation schemes which examine plants for potent biological

activities in search of new creating new drugs (Phillipson 1997), which is causing

detrimental impact on forest ecosystems on a global level. Besides this, there is an

enormous demand in medicinal plants, for domestic use and for commercial trade,

resulting in a huge trade on local, national and international levels (Hamilton 1992;

Lange 2006). It appears evident that the growing commercial trade of natural products

in medicinal plants causes an increasing volume of harvested plants mostly from the

wild (Hamilton 1992; Lange 2002). These harvests may affect plant populations at

two different levels. Primarily, at the level of the entity, on vital rates for example

growth and reproductive ability and, secondly, at the level of the populace, which

demonstrate effects on the demographic organization and lasting dynamics. The direct

effects of exhaustive collection may include decline in the output, density and

regeneration of the targeted plant species, depending on the part of the plant that is

utilized. Since countless species of botanicals are medicinal, their conservation is, in

some ways, is a very complicated procedure for the conservationists.

Conservation: Challenges and Concerns

Plant diversity is remarkably high in Asia. Thousands of plant species with high

proportion of endemic species and more than 100 endemic families are found in Asia.

10 out of 34 international biodiversity hotspots are in Asia. These hotspots have been

identified by Conservation International based on endemism of plant and remnant

original vegetation. Vegetation types in Asia are diverse, with a full spectrum of

vegetations from tundra to tropical rainforest, with a typical latitudinal distribution

pattern of vegetations.

The World Health Organization (WHO) has estimated the present demand for

medicinal plants is approximately US $14 billion per year (Sharma 2004). The

demand for medicinal plant-based raw materials is growing at the rate of 15 to 25%

annually, and according to an estimate of WHO, the demand for medicinal plants is

likely to increase more than US $5 trillion by 2050.

The Indian subcontinent is well known for its diversity of forest products and the age-

old healthcare traditions. A great deal of traditional knowledge of the use of various

plant species is still intact with the indigenous people. Apart from health care,

medicinal plants are mainly the alternate income-generating source of underprivileged

6

communities. The global demand for herbal medicine is not only large, but growing.

The market for Ayurvedic medicines is estimated to be expanding at 20% annually in

India (Subrat 2002). Estimates for the numbers of species used medicinally include

more than 8000 species from India. In India, out of the total land area of 329 million

ha, only 78.29 million ha are classified as forests. This represents only 23.81 percent

of the total geographic area as against the recommended forest coverage of 33

percent. Total growing stock of India‟s forests is estimated to be 6047.15 m cum. The

annual estimated production of wood and fuel wood from forests is estimated to be as

3.175 m cum and 1.23 m tones (state forest report of 2011). In India over 50 million

people are dependent on NWFPs for their subsistence and cash income (Hegde et al.,

1996). Commercial NWFPs are estimated to generate Rs. 3 billion (US$ 100 million)

annually in India.

This rising demand of plant based drugs is unfortunately creating heavy pressure on

medicinal plant populace due to over harvesting (Kala et al., 2005; Light et al., 2005)

and the conservation issues mainly concern the current trend of increasing volumes of

harvests from „wild‟ population. (Hamilton 2004; Ticktin 2004).

The expanding trade in medicinal plants has serious implications on the survival of

several plant species, many of which are under threat of becoming extinct. Today this

rich biodiversity of medicinal plants is facing a serious threat because of the rapid loss

of natural habitats and overexploitation of plants from the wild. To meet the demands

of the Indian herbal industry, which has an annual turnover of about US$ 300, million

medicinal plants are being harvested every year from some of 165 000 ha of forests

(FRLHT 1997). Harvesting medicinal plants for commercial use, coupled with the

destructive harvest of underground parts of slow reproducing, slow growing and

habitat-specific species, are the crucial factors in meeting the goal of sustainability.

In India, decline in environmental quality, scarcity of an array of natural resources

and loss of biodiversity has been observed in the last few decades (Singh and Bagchi,

2013). Studies document continual and unremitting deforestation and biodiversity

loss, particularly in the biodiversity hotspots of the Himalayas and the Western Ghats

(e.g. Jha et al., 2000; Lele and Joshi, 2009; Pandit et al., 2007). Additionally, illegal

wildlife trade exerts a heavy cost on India‟s biodiversity (TRAFFIC 2008). These

7

pressures continue in contemporary times due to a large human population and

associated problems.

Conservation issues in medicinal plants mainly concern those plants which are

harvested from the 'wild', which is the case for the great majority of species.

Conservation issues arise if the trade threatens conservation of biodiversity or is not

sustainable. Biodiversity may be threatened if the trade endangers survival of the

species, erodes its genetic diversity or causes loss or degradation of important natural

or semi-natural ecosystems. For instance, more than 95% of 400 plant species used by

Indian herbal sector are harvested from wild (Uniyal et al., 2000) and there is major

trade from the Himalayas, including Nepal, to India and beyond, mostly for use in

herbal medicine (notably Ayurvedic medicine). The volume of this trade is unknown,

because it is believed that the greater part of it passes through unofficial channels

(Hamilton 1992). Especially, tree species, being harvested from the wild, for the

medicinally important root and bark contributes in establishing the underpinnings of

healthcare practices throughout Asian nations including India and other developing

nations of the world. Unregulated harvesting of medicinal plants is therefore a cause

for conservation concern.

Why conserve and restore tree species?

The concept of sustainable forest management (SFM) arises from the notion of

sustainable development that has gained increasing recognition worldwide since the

late 1980s. Encompassing an array of issues, sustainable management has become an

overarching term that captures an unfolding paradigm shift in contemporary forest

management (Wang 2004). Conservation and sustainable management of biodiversity

is critical for better livelihoods because non sustainable harvesting not only threatens

the survival of valuable medicinal plants, but also the livelihood of population

dependent on them. However, the choice of species for conservation and the method

of protection is a much complex procedure. The scale of international trade in

medicinal plants is difficult to assess with precision because of the paucity of reliable

statistics and trade secrecy (Hamilton 1992) but it is well established that the major

concern should focus on those species which are harvested from „wild‟. Moreover,

trees are of exceptionally high ecological, socio-economic and cultural importance.

8

As the principal biomass component of forest ecosystems, they provide habitat for at

least half of Earth‟s terrestrial biodiversity.

Commercialization coupled with the destructive harvest, slow growth rate and habitat-

specificity have imposed a major threat to the growth and survival of these species.

Therefore, the integration of conservation and use is therefore not an option but an

imperative (Newton 2008). There is a regular and even ever-growing necessitate for

defining adequate protection stratagem to develop and promote sustainable harvesting

of medicinal tree species through the use of enhanced harvesting systems (Botha et

al., 2004; Belcher et al., 2005; Cunningham 1991; Geldenhuys 2007; Light et al.,

2005). The sustainable management of medicinal tree species is far from simple

(Delvaux 2009). Extraction of their crucial plant parts like root and bark may alter

biological processes at many levels. For instance, the most direct ecological

consequence of NTFP extraction is alteration of the rates of survival, growth and

reproduction of harvested individuals. Changes in these vital rates can, in turn, affect

the structure and dynamics of populations. Those tree species which are usually

harvested for their root and stem bark, are highly influenced by the injudicious

techniques of harvesting. From a botanical perspective, bark is a complex sheath that

protects trees from insults of nature and transports carbohydrates and growth

regulators within a plant. Without it, a woody perennial plant simply would not

survive. The phloem together with the periderm forms the bark tissue which shields

the xylem from the environment, mechanical injuries and infectious microorganisms

(Biggs 1992). The periderm is a protective layer of secondary origin and is constituted

by three tissues. The phellogen (or cork cambium) is the meristematic tissue that

produces phellem (or cork) to the outside and phelloderm (or cork parenchyma) to the

inside of the stem (Hudler 1984). Thus, harvesting bark has serious deleterious effects

on survival of a tree species. Additionally, harvests may affect the physiology and

change demographic and genetic patterns of populations, and alter community and

ecosystem level processes (Ticktin 2004).

Furthermore, most medicinal plants are harvested for more than one reason

(Shackleton et al., 2002; Ticktin 2004) and the exploitation capriciously effects on the

plants. Harvesting bark or roots is detrimental for tree survival (Cunningham 1991;

Geldenhuys 2004; Peters 1994; Witkowski et al., 1994; Vermeulen 2006) whereas

flower and fruit harvesting has positive impact on regeneration capacity (Hall and

9

Bawa, 1993; Gaoue and Ticktin, 2008; Peters 1994). The sustainable management of

medicinal trees requires knowledge of how different species respond to different

harvesting techniques (Ticktin 2005). Specifically, the production rate of the resource

will determine how much of it can be used sustainably (Geldenhuys 2004). The

conservation status of the world‟s tree species is poorly understood. It is striking that

many countries do not yet possess a complete list of tree species occurring within

their borders, let alone assessments of their extinction risk.

The impacts of variation in life history, plant parts and environment on harvest limits

and capacity for regeneration support some previous hypotheses and guidelines for

assessing NTFPs, which have the most potential to support livelihoods of dependent

population and foster conservation (Cunningham 2001; Peters 1994; Ticktin 2004).

Vital rates of non timber resources may also be significantly affected by differences in

harvest techniques which include seasonal timing of harvest, timing of harvest in the

plant life cycle, frequency of harvest, size of individuals harvested and intensity of

harvest (Anderson and Rowney, 1999; Geldenhuys and Van der Merwe, 1988; Ticktin

et al., 2002). The exploitation of medicinal plants can also affect many levels of forest

ecology from individual and population to community and ecosystem.

The range of methodologies and modus operandi used in experimentations makes

assessment very difficult and indicates to the requirement of standardizing the

methodologies in various ways. Although, a range of actions are recommended to

maintain the diversity and to conserve medicinal species which includes the co-

ordinated conservation action, based on both in situ and ex situ strategies, inclusion of

community and gender perspectives in the development of policies and programs,

control on the medicinal plant trade, the establishment of systems for inventorying

and monitoring the status of medicinal plants, encouragement for microenterprise

development by indigenous and rural communities, the protection of traditional

resource and intellectual property rights and many more (Hamilton 2004). But

innovative strategies for the development of sustainable harvesting practices are still

required to manage these resources considerately.

Arnold and Perez (2001) suggested that uncontrolled harvesting may lead to the

depletion of species drastically. Over long periods of time, forests can and do recover

from even heavy use if allowed the time to do so without further disturbance. But this

10

does not happen if there is repeated harvesting at short intervals relative to the forest‟s

regeneration cycle (Poore et al., 1989), unless there is a monitoring and control

system that provides a constant flow of information about the ecological response of

species to varying degrees of exploitation (Peters 1994). Tree species have been the

focus of increasing interest regarding the so-called conservation-through-use

approach, which aims to achieve conservation by increasing the value of wild

resources to local communities (Newton 2008). Though these species exhibit wide

range of features that amplifies their probability for sustainable management, the

approach is rarely successful in practice. The reasons for this may be, the lack of

sustainable harvesting, proper interaction between threats, successful

commercialization, the economic benefits received by producers and so on (Newton

2008). Despite numerous pleas to consider different approaches for conservation and

management of tree species, debate has been focused on whether species-based or

ecosystem-based study should be the major focus for biodiversity conservation

efforts. Several theoretical and practical arguments have been made on both sides of

this debate, but unfortunately, two distinct groups of protagonists have developed

(Likens and Lindenmayer, 2012). Nevertheless, research and management for

biodiversity conservation should be best conceptualized as a continuum rather than as

separate and biased approaches. But over and above, management through complete

study on species to species contributes to an integration of understanding of multiple

interacting factors, including ecosystems and can highlight links with other species,

especially when functional roles are studied. Moreover, every species react differently

to diverse management protocols. More focused research is needed to define how

conservation and use of species can be successfully combined (Hutton and Williams,

2003; Mackinnon 2009).

As it is evident that millions of people depend on exploitation of the forest thus the

concept of sustainability means that we should be able to assure the maintenance of

viable populations of tree species that are harvested (Newton 2008). Restrictions

placed on forest use in order to protect forests brought into community forestry

schemes, and put them under sustainable forest management, can impose costs on

local people which reduce their incentive to become involved. Allowable harvests

may be reduced, and the structure of benefits changed as the composition of the forest

changes under management (Arnold and Perez, 2001).

11

Further, it is imperative to distinguish that divergence of interests between

development and conservation does not necessarily mean that the different balances

between the two that result are less or more „sustainable‟ than the other. Rather it is

the recognition that sustainability has a number of different dimensions. The objective

of ecological sustainability is usually expressed in terms of maintaining forest cover

and biodiversity. The goal of sustainable forest management has usually focused on

maintaining a continuous flow of stated outputs, while retaining the productive

capacity of the forest intact. The confrontation of the scientific and economic

community is to find a triumphant equilibrium among these diverse requirements. For

this, approaches which are restricted only to a certain level cannot be favoured, but

there is a need of focusing on all levels of forest ecology (Ticktin 2004). Earlier

studies approached the trade of NTFPs and the biology of the tree species from many

different points of view. However, it should not be assumed that all species from a

forest considered to be sustainably managed will necessarily themselves be

sustainably harvested, in terms of maintaining viable populations (Newton 2008;

Ticktin 2004). Consequently, in the case of medicinal plant management it is more

essential to pay special attention to the study of the individuals and populations of

target species. Previous studies on quantitative assessment of the ecological

implications of harvesting were targeted at the population level and very few of them

focused on the individual tree level (Delvaux 2009; Ticktin 2004). Same was in the

case of bark harvesting surveys. But sustainable management must take into account

the versatile aspects of proper harvest system, resource allocation and wise

management of the species. In Asian countries, efforts to minimize biodiversity loss at

the global scale have been unsuccessful owing to the unsustainable harvest systems

(Mackinnon 2009) and inadequate execution of the precautionary regulations.

Judicious management of resources is critical for better livelihoods in less developed

nations, due to the fact that the impact of ecosystem degradation and biodiversity loss

have a direct influence on the proportion of GDP statistics posing a predominant

economic impact of loss which eventually influences the poor populace, which are

most significant beneficiaries of forest biodiversity. Due to over exploitation and slow

regeneration rate, the planning of conservation measures for tree systems is a must.

Under the backdrop of these facts, this study examines some scientific conservation

insights which would fulfill the precondition of sustainable harvesting and yet

12

simultaneously provide the base resource for pharmaceutical use. This study

delineates some novel concepts for sustainable management of tree species using four

important medicinal tree species viz. Bauhinia variegata, Oroxylum indicum,

Holarrhena pubescence and Terminalia arjuna. These management relevant and

multi-faceted approaches described in the study may bring new horizons for

developing conservation strategies for tree species. The following studies were carried

out, to fulfill the objectives:

Collection, processing and extraction of various plant parts of Bauhinia

variegata, Oroxylum indicum, Holarrhena pubescence and Terminalia arjuna.

Development of method for High Performance Liquid Chromatography

(HPLC) analysis of various studied species.

Studying the ecological responses to bark harvesting in the above mentioned

species by three types of treatments i.e. total bark removal, partial bark

removal and cover treatment.

To assess the effect of long term storage in different mediums on bio-

deterioration of secondary metabolites in crude bark drug of the studied

species.

To test the suitability of plant part substitution method for developing an

innovative strategy for sustainability of the studied tree species.

To test the effect of phenology and temporal variation on major bioactive

secondary metabolite concentration within plant parts of the species.

CHAPTER 2

Review of Literature

13

REVIEW OF LITERATURE

1. Bauhinia variegata L.

Plants of the genus Bauhinia (Fabaceae) are widely distributed in most tropical

countries and have been used recurrently in folk medicine to treat diverse kinds of

pathologies, particularly inflammation, diabetes as well as pain and infections. There

are about one hundred species under the genus Bauhinia and eight are native to India.

In recent years, interest in these plants has increased significantly throughout the

world. The biological properties of different phytopreparations and pure metabolites

have been investigated in numerous experiments. Studies have confirmed their

reported therapeutic properties. It is noteworthy that Bauhinia variegata is the most

important studied plants for drug usage, in different parts of the world, which is

commonly known as „Camel‟s foot tree or Orchid tree‟.

1.1. Botanical description

B. variegata L. is a small to medium-sized deciduous tree with a short bole and

spreading crown, attaining a height of up to 15 m and diameter of 50 cm. The bark is

light brownish grey, smooth to slightly fissured and scaly. Inner bark is pinkish,

fibrous and bitter. The twigs are slender, zigzag; when young, light green, slightly

hairy and angled, brownish grey in color. Leaves have minute 1-2 mm long stipules,

early caducous; petiole puberulous to glabrous, 3-4 cm; lamina broadly ovate to

circular, often broader than long, 6-16 cm diameter, 11-13 nerved, tips of lobes

broadly rounded, base cordate, upper surface glabrous, lower surface glaucous but

glabrous when fully grown. Flower clusters (racemes) are unbranched at ends of

twigs. The few flowers have short, stout stalks and a stalklike, green, narrow basal

tube (hypanthium). The light green, fairly hairy calyx forms a pointed 5-angled bud

and splits open on one side, remaining attached; petals 5, slightly unequal, wavy

margined and narrowed to the base; 5 curved stamens; very slender, stalked, curved

pistil, with narrow, green, 1-celled ovary, style and dot like stigma. Pods dehiscent,

strap-shaped, obliquely striate, 20-30 by 2-25 cm, long, hard, flat with 10-15 seeds in

each, seeds brown, flat, nearly circular with coriaceus testa.

14

1.2. Geographic distribution

B. variegata is a plant of tropical and subtropical climates with hot, dry summers and

mild winters. Tree is native to China, Colombia, India, Myanmar, Nepal, Pakistan,

Thailand, Vietnam and also being cultivated in Brazil, Egypt, Kenya, Puerto Rico,

Tanzania, Uganda, Zanzibar, Zimbabwe. However, morphologically some species of

the genus are very identical, thus making it complex to identify the correct one. The

studied species demands plenty of light and requires good drainage. Severe frost

damages the leaves of seedlings and saplings, but they recover during summer. The

tree is fairly resistant to drought but susceptible to fires.

1.3. Phenology

In its natural habitat in India, the tree is deciduous, remaining leafless from Jan-Feb to

April with leaf fall in Nov-Dec. Flowering occurs when the plant is leafless. Tree

starts flowering at a very early age of 2-3 years. The seeds disperse from the pods and

germinate on sites with favorable light and moisture conditions, while in unfavorable

niches the radical dries up or is destroyed by birds.

1.4. Phamacognostical studies

The bark of the plant is greyish brown externally and pale pink inside. External

surface is rough because of large number of longitudinal cracks and fissures.

Transverse section of the bark shows 12 - 20 layers of cork cells. The cork is followed

by a single layer of phellogen, beneath which lies a wide zone of phelloderm of

tangentially elongated to isodiametric cells. The pericyclic fibres are broad, thickly

lignified, and have narrow lumen. Lignified fibres and stone cells are distributed in

this region. They are tapered at both ends. The phloem is represented by sieve tubes,

companion cells, phloem parenchyma, phloem fibres, crystal fibres and stone cells,

transversed by uni to biseriate medullary rays (Prakash et al., 1978). Microscopic

studies of flowers revealed uni to multicellular covering trichomes. They are broader

at the base and pointed at the apex. Thin walled multicellular balloon-shaped gland

surmounts the trichomes. Ovary is superior with marginal placentation. Pollen grains

are spheroidal and tricolporate pores being broad. Exine is thick, differentiated into

sexine and nexine (Dey et al., 1988).

15

1.5. Ethnobotanical/ Ayurvedic uses

Plant has been used frequently in folk medicine for varied purposes. The aborigines of

Ghatigaon forests, Gwalior, Madhya Pradesh use the flower buds of Bauhinia for the

treatment of diarrhoea, dysentery and haemorrhoids (Bhatnagar et al., 1973). The

flowers are used in piles, oedema and dysentery (Malhotra and Moorthy, 1973), as

laxative and anthelmintic.

The bark of the plant is medicinally more important and is used by tribals against a

variety of ailments. The bark is used in fever, as tonic, astringent, antileprotic, wound

healing and as antigoitrogenic (Kapoor and Kapoor, 1980; Sahu, 1981; Singh and

Aswal., 1992; Thakur et al., 1992). In an ethnobotanical survey of the Eastern Ghat

region of Andhra Pradesh, the stem bark is documented to be useful for the treatment

of asthma (Reddy et al., 2006). The bark is also documented for the cure of

dysmenorrhoea, menorrhagia, tuberculosis and wounds (Kirtikar and Basu, 1999).

The leaves are used in the treatment of stomatitis (Balajirao et al., 1995). The roots

are used as an antidote for snake poisoning, in dyspepsia, flatulence and as

carminative (Kapoor and Kapoor, 1980). They are also reported to be useful as

antitumour and in obesity (Shah and Joshi, 1971).

In Ayurvedic literature, the plant is known by various names as Kanchnar, Gandari,

Yugmapatra and Karbudara. It is reported to have Kasaya rasa, Ruksha guna, Shita

virya and Katu vipaka. The stem bark of Bauhinia is used in the treatment of

krimiroga (worm infestation), gandamala (scrofula), apaci (cervical lymphadenitis)

and vrana (acne) (Anonymous 1998; Kapoor, 2005). Ayurvedic practitioners have

been using the bark powder of B. variegata in combination with other drugs for the

treatment of various ailments. In combination with Commiphora, Curcuma domestica

and Saraca indica, it is used in gynaecological ailments. For the treatment of

lymphatic swelling it is given with Commiphora wightii, Boerhaavia diffusa and

triphala. In osteoporosis, Bauhinia is prescribed with Withania somnifera, Mimusops

elengi, Zingiber officinale and Commiphora wightii. Diarrhoea is treated in

combination with Picrorrhiza kurroa and Terminalia belerica (Sebastian, 2006).

Kanchnar guggul, an Ayurvedic formulation is commercially available for the

treatment of TB tumors, ulcers, gonorrhoea, in an abnormal increase of white blood

cells (Uniyal et al., 1998).

16

1.6. Phytochemistry

The most important flavonoids of the plant are apigenin, luteolin, quercitrin, rutin and

quercitin (Bhandari et al., 2007) which possess major anti-inflammatory activity.

Phytochemical analysis of the root bark of B. variegata yielded a new flavanone,

(2S)-5, 7-dimethoxy-3, 4- methylenedioxyflavanone and a new dihydrodibenzoxepin,

5,6-dihydro-1,7-dihydroxy-3,4-dimethoxy 2-methyldibenzoxepin. The structures of

the new compounds were determined on the basis of spectral studies. A novel

flavonol glycoside 5,7,3',4'-tetrahydroxy-3-methoxy-7-Oalpha- L-

rhamnopyranosyl(1--)3)-O-beta-galactopyranoside isolated from the roots of Bauhinia

and its structure was identified by spectral analysis and chemical degradations

(Yadava and Reddy, 2003). The stem bark showed presence of hentriacontane,

octacosanol, stigmasterol (Prakash and Khosa, 1978a), sterols, glycosides, reducing

sugars and nitrogenous substances on preliminary phytochemical screening (Prakash

and Khosa, 1978b). The stem yielded a flavonone glycoside characterized as 5, 7-

dihydroxyflavonone-4–O–α-L–rhanmopyranosyl- β–D–glucopyranoside (Gupta et al.,

1979). The isolation of β-sitosterol, lupeol, kaempferol-3- glucoside and a 5, 7-

dimethoxyflavonone-4–O–α– L–rhamnopyranosyl-β-D-glucopyranoside was also

reported from the stem of the plant (Duret and Paris, 1977, Gupta et al., 1980). A

flavonol glycoside, characterized as kaempferol-3-glucoside, was isolated from stem

of this plant (Gupta and Chauhan, 1984). A new phenanthraquinone, named

bauhinione, has also been isolated from B. variegata, and its structure has been

elucidated as 2, 7-dimethoxy-3- methyl-9,10-dihydrophenanthrene-1,4-dione on the

basis of spectroscopic analysis (Zhao et al., 2005). Two new long chain compounds,

heptatriacontan- 12, 13-diol and dotetracont-15-en-9-ol have been isolated from the

leaves of B. variegata. Structures of these compounds have been elucidated by

spectral data analyses and chemical studies (Singh et al., 2006). The leaves were also

found to contain crude protein, calcium and phosphorous. Due to its nutritive value,

the leaves were recommended as fodder for cattle (Sharma et al., 1968). Leaves of B.

variegata were also reported to contain volatile oil. The analysis of oil by GC/MS

showed presence of germacrene D, spathulenol, δ- and γ- cadinene. Keto acids of

flowering buds were analyzed during their development and correlated with the free

amino acids and amides. Only four amino acids (α-Alanine, aspartic acid, glycine and

glutamic acid) appeared in early stages where glutamic acid showed a sharp drop

17

from initial to later stages. Phosphoenolpyruvic acid, oxaloacetic acid and α-

ketoglutaric acid appeared in later stages. Their absence in early stages attributed to

their rapid utilization in floral bud development (Mukherjee and Laloraya, 1977).

1.7. Pharmacological potential

1.7.1. Antioxidant activity

The aqueous and ethanolic extracts of stem bark of B. variegata have shown

significant antioxidant activity (Mishra et al., 2011). The percent free radical

scavenging activity gradually increases with increasing concentrations of B. variegata

extracts in DPPH radical scavenging assay. Dose dependent antioxidant activity

pattern was also observed in phosphomolybdate assay. Antioxidant activity was

directly correlated with the amount of total phenolic contents in the extracts. B.

variegata in L-dopa extract has shown the highest FRAP values (Gautam et al., 2011).

1.7.2. Anti-inflammatory activity

A new triterpene saponin, named as 23-hydroxy-3alpha-[O-alpha-L-1C4-

rhamnopyranosyl-(1"g 4')-O-alpha-L-4C1-arabinopyranosyl-oxy]olean- 12-en-28-oic

acid O-alpha-L-1C4-rhamnopyranosyl-(1"”g 4"”)-O-beta- D-4C1-glucopyranosyl

(1"”g6"‟)-O-beta-D-4C1-glucopyranosyl ester, isolated from the leaves, was found

nontoxic (LD50) and to have significant anti-inflammatory activity (Rao et al., 2008).

It also showed antinociceptive effects that are more potent than the reference drugs.

The mechanism responsible for the antinociceptive action of the extract is partly

related to the modulated release or action of pro inflammatory mediators involved in

the models of pain used. It also showed a slight anti schistosomal activity. A novel

flavonol glycoside, 5,7,3‟,4‟-tetrahydroxy-3-methoxy-7-O-a-L-rhamnopyranosy

(1g3)-O-ß-D- lactopyranoside (C28H32O16) isolated from ethyl acetate soluble

fraction of the 90% ethanolic extract of the roots of B. variegata showed marked anti-

inflammatory activity as tested by carrageenan induced hind paw oedema method

(Almeida et al., 2006; Yadava et al., 2003). In the continuing search for novel anti-

inflammatory agents, 6 Flavanoids namely, kaempferol (Ambasta 1998), ombuin

(Araujo et al., 2005), kaempferol 7,4‟-dimethylether 3-0-ß- D glucopyranoside

(Asima et al., 1992), kaempferol 3-0-ß-D-glucopyranoside (Azevedo et al., 2006),

isorhamnetin 3-0-ß-D- glucopyranoside (Bhakuni et al., 1974) together with one

18

triterpene caffeate, 3ß-trans-(3,4-dihydroxycinnamoyloxy) olean- 12-en-28-oic acid

(Bodakhe and Alpana, 2007) were isolated from the non-woody aerial parts of B.

variegata.

1.7.3. Anthelmintic activity

Following the traditional claim, a study was conducted to investigate the anthelmintic

potential of the stem bark of Bauhinia. The crude ethanolic extract of the plant was

evaluated for anthelmintic activity using Indian earthworm Pheretima posthuma

(Annelida) and Ascardia galli (Nematode) as test worms. Various concentrations (10 -

100 mg/ml) of ethanolic extract were tested in the bioassay, which involved

determination of time of paralysis and time of death of the worms. Piperazine citrate

(10 mg/ml) was included as reference standard. The results of the study showed

promising anthelmintic activity at higher concentration of 100 mg/ml when compared

with the standard included in the study (Mali et al., 2008). In one study, the ethanol

extract of stem of the plant showed juvenilizing activity against Dysdercus cingulatus

nymphs (Srivastava et al., 1985).

1.7.4. Antimicrobial activity

In one study, the fresh juice of the plant was screened for antimicrobial study and

found devoid of bacteriostatic activity against Staphylococcus aureus and Escherichia

coli (Bhavsar et al., 1965). In another study, the methanolic extract of leaves exhibited

antibacterial activity against Proteus vulgaris, Bacillus anthracis, Escherichia coli,

Streptococcus agalactiae and antifungal activity against Aspergillus fumigatus and

Aspergillus niger (Sharma and Saxena, 1996). The leaf extract also exhibited toxicity

against ringworms caused by fungi Epidermophyton floccosum, Trichophyton

mentagrophytes and Microsporum gypseum (Mishra et al., 1991). The aqueous and

methanolic extracts were evaluated against five bacterial strains, viz., Bacillus cereus,

Staphylococcus aureus, Klebsiella pneumoniae, Escherichia coli and Pseudomonas

pseudoalcaligenes. The most susceptible bacteria were found to be K. pneumoniae, B.

cereus and the most resistant bacteria was E. coli. (Parekh et al., 2006a). In another

study, bark powder was defatted with petroleum ether. The non-defatted as well as

defatted plant material was then individually extracted in different solvents with

increasing polarity, viz., 1,4-dioxan, acetone, methanol, dimethyformamide (DMF)

and distilled water respectively. The antibacterial activity of all extracts (non-defatted

19

and defatted) was determined by agar well diffusion method at the three different

concentrations of 10 mg/ml, 5 mg/ml and 2.5 mg/ml. The antibacterial activity of

defatted extracts was found more than non-defatted extracts against the test

microorganisms (Parekh et al., 2006b).

1.7.5. Antitumor activity

The antitumor potential of the ethanol extract stem of B. variegata has been evaluated

against Dalton‟s ascitic lymphoma (DAL) in Swiss albino mice. A significant

enhancement of mean survival time of B. variegata treated tumor bearing mice was

found with respect to control group. Treatment was found to enhance peritoneal cell

counts (Rajkapoor et al., 2003a). The antitumor activity of ethanol extract of B.

variegata was evaluated against Ehrlich ascites carcinoma in Swiss albino mice and

found to be a potent cytotoxic towards tumour cells (Rajkapoor et al., 2003b). In

another study, the chemopreventive and cytotoxic effect of ethanol extract of B.

variegata was evaluated in N-nitrosodiethylamine induced experimental liver tumor

in rats and human cancer cell lines. Oral administration of ethanol extract effectively

suppressed liver tumor induced by DEN. The extract produced an increase in

enzymatic antioxidant (superoxide dismutase and catalase) levels and total proteins

when compared to those in liver tumor. The histopathological changes of liver

samples were compared with respective controls. It was found to be cytotoxic against

human epithelial larynx cancer and human breast cancer cells. These results showed a

significant chemopreventive and cytotoxic effect of B. variegata against DEN

induced liver tumor and human cancer cell lines (Rajkapoor et al., 2003b).

1.7.6. Hepatoprotective activity

To validate the traditional claim for the cure of jaundice, the hepatoprotective activity

of stem bark of Bauhinia was investigated in carbon tetrachloride (CCL4) intoxicated

Sprague-Dawley rats. The alcoholic stem bark extract of the plant at different doses

(100 and 200 mg/kg) was administered orally to male rats. The effects of extract on

serum enzymes, liver proteins and lipids were assessed and significant

hepatoprotective activity of the extract were found (Bodakhe and Alpana, 2007).

20

1.7.7. Nephroprotective

The nephroprotective activity of the ethanolic extract of B. variegata whole stem

against cisplatin-induced nephropathy was investigated by an in vivo method in rats.

Treatment with the ethanol extract for 14 days significantly lowered the serum level

of creatinine and urea, decreased urine creatinine and albumin with a significant

weight gain, and increased urine output when compared with the toxic group. The

histological damages in the B. variegata extract-treated group were minimal in

contrast to the toxic rats (Panda et al., 2011).

1.7.8. Antihyperlipidemic

Lipids are one of the most susceptible targets of free radicals. This oxidative

destruction is known as lipid peroxidation and may induce many pathological events.

In the preliminary studies, it was found out that the aqueous and ethanolic extracts of

B. variegata L. have shown promising antihyperlipidemic activity (Rajani et al.,

2009). It may partly owe its antihyperlipidemic activity to its antioxidant activity. A

study on antihyperlipidemic activity of butanolic fraction of total methanol extract of

leaves against Triton WR- 1339 induced hyperlipidemia in rats showed not only

significant reduction in cholesterol, triglyceride, LDL, VDL level, but also an increase

in HDL level (Kumar et al., 2011).

1.7.9. Anticarcinogenic and Antimutagenic

Anticarcinogenic and antimutagenic potential of B. variegata extract was evaluated in

Swiss albino mice using a skin carcinogenesis and melanoma tumour model, along

with micronucleus and chromosomal aberration tests. In these studies, a single

application of Kachanar extract at various doses significantly prevented micronucleus

formation and chromosomal aberrations in bone marrow cells of mice, in a dose

dependent manner (Agarwal et al., 2009).

Moreover, it is also used as fodder for livestock. Altogether, the species has an ethno

botanical, medicinal (bark), edible (leaves and pods) and ecological importance (Rijal

2011). Multipurpose species, in which multiple plant parts are harvested from the

same individuals, face higher risk of overexploitation. We could affirm that this plant

contains various chemical constituents which are responsible for its wide

pharmacological efficacy. Results of preclinical studies have suggested its possible

21

applications in clinical research. B. variegata appears to be a promising therapeutic

agent and can certainly play an important role in the discovery of new and effective

medicinal agents and due to which industrial demand of this species is likely to boost

up due to the global exigency in the domain of health care market. Therefore, it needs

contemplation for the appropriate conservation and a fine harvest system.

Currently, it is among highly traded species of India

(http://www.nmpb.nic.in/index1.php?level=0andlinkid=90andlid=642) and the

industrial demand of this species is likely to boost up due to the global exigency in the

domain of health care market. Therefore, this multipurpose species needs deliberation

for the proper conservation and a fine harvest system (Rijal 2011).

22

2. Oroxylum indicum Vent.

Oroxulum indicum, commonly known as „Sonapatha‟ is an important medicinal tree

used in Ayurveda and other indigenous medical system for over thousands of years. It

has been used as a single drug or as a component of several poly-herbal drug

preparations. There is increasing interest both in the industry and scientific research

for this tree because of its strong biological properties.

O. indicum is used as one of the important ingredients of well-known ayurvedic

preparation „„Dashmool‟‟. It is also used in other ayurvedic formulations such as

Dasamularistha, Syonaka putapaka, Syonaka sidda ghrta, Brhatpancamulyadi

kvatha, Amartarista, Dantyadyarista, Narayana Taila, Dhanawantara Ghrita,

Brahma asayana, Chyavanaprasa and in several commercial formulations like

Dashmoolarisht, Agastyaharitakyaveleha, Bramha rasayan (Dabur India Ltd., New

Delhi, India), Mentat BS, Anxocare (Himalaya Drug Co., Bangalore, India) and many

more. Destructive and non sustainable methods of harvesting coupled with low

regeneration rate and habitat devastation have posed serious threat to the survival and

availability of this highly useful tree (Yashodha et al., 2004).


O. indicum is a small or medium sized deciduous tree up to 12 m in height with soft

light brown or grayish brown bark with corky lenticels. The leaves are large, 90-180

cm long 2-3 pinnate with 5 or more pairs of primary pinnae, rachis cylindrical,

swollen at the junction of branches, leaflets 2-4 pairs ovate or elliptic, acuminate,

glabrous. The large leaf stalks wither and fall off the tree and collect near the base of

the trunk, appearing as a pile of broken limb bones. The flowers are reddish purple

outside and pale, pinkish-yellow within, numerous, in large erect racemes. The

flowers bloom at night and emit a strong, stinky odour which attracts bats. The tree

has long fruit pods that curved downward, hang down from the branches, looking like

the wings of a large bird or dangling sickles or sword in the night. Fruits are flat

capsules, 0.33-1 m long and 5-10 cm broad and sword shaped. Seeds are numerous,

flat and winged all around like papery wings, except at the base. The fresh root bark is

soft and juicy; it is sweet, becoming bitter later. On drying, the bark shrinks, adhere

closely to the wood and becomes faintly fissured.

23


O. indicum is native to the Indian subcontinent, usually found in the Himalayan

foothills with a part extending to Bhutan and Southern China, in Indo-China and the

Malaysia ecozones.

2.3. Phenology

The tree is propagated naturally by seeds, which germinate in the beginning of the

rainy season. Seedlings require moderate shade in the early stages. However, the seed

set is poor and seed viability is low. Problems related with its natural propagation and

indiscriminate exploitation for medicinal purpose has pushed O. indicum to the list of

endangered plant species of India. The plant flowers in June-July and bears fruits in

November.


Microscopic studies of the roots of O. indicum revealed that the root cork consists of

polyhedral cells with the fragments of pitted stone cells lying underneath the cork

cells. The outer layer of cork is lignified while as the inner cork layer is non-lignified.

Cortex is wide and made up of thin walled parenchymatous cells. Abundant crystal of

calcium oxalate are scattered as such in parenchymatous cell of cortex. Phloem

consists of thin walled radially arranged phloem parenchyma cells showing narrow

tangential segments of sclerenchyma. The microscopic studies carried out on the root

bark of O. indicum revealed that the transverse section of the plant consists of cork,

cortex, phloem and medullary rays. Cork consist of about 30 to 35 layers of

tangentially running, polyhedral cells with the fragments of groups of tangentially

running rectangular to oval, thick walled pitted stone cells lying underneath the cork

cells. The outermost cork layer consists of about 15 to 20 rows of lignified cells and

rest of were non-lignified. Cortex is made up of thin walled parenchymatous cells.

Stone cells and abundant lignified sclerides isolated in large groups are present in the

cortex. The abundant acicular crystals of calcium oxalate are present which remains

scattered as such in parenchymatous cells of cortex. Phloem forms the major part of

the bark and was composed of broad radial strips separated by medullary rays. It

consists of about 25 to 30 layered, thin walled radially arranged phloem parenchyma

cells showing narrow tangential segments of sclerenchyma. The phloem region is

24

traversed by medullary rays, which are biseriate to tetra seriate and made up of thin

walled cells (Lawania et al., 2010).

2.5. Ayurvedic/Ethnobotanical uses

Medicinal treatise of Ayurveda dates back to pre-historic Vedic era, which is the

ancient testimony for use of plants as medicine. According to the Ayurvedic

literatures, medicinal properties of O. indicum are vast. Root bark of plant is acrid,

bitter, pungent, astringent to the bowels, cooling, aphrodisiac, tonic, increases

appetite, useful in “vata”, biliousness, fevers, bronchitis, intestinal worms, vomiting,

dysentery, leucoderma, asthma, inflammation, anal troubles. It is used in the treatment

of diarrhoea, dysentery, rheumatism and has diaphoretic properties too (Kirtikar and

Basu, 2001; Prakash, 2005). O. indicum is used as one of the important ingredients of

some commonly used Ayurvedic preparations like Dasamularishtha, Amartarista,

Dantyadyarista, Narayana Taila, Dhanawantara Ghrita, Brahma Rasayana, Syonaka

putapaka, Syonaka sidda ghrta and Chyavanaprasa Awaleha (Anonymous, 1998;

Balkrishna, 2005; Jabbar et al., 2004; Kumar et al., 2009; Zaveri et al., 2008). In the

composition of drugs like chavanprasha and mentat, different parts of O. indicum are

used (Gupta et al., 2008; Laupattarakasem et al., 2003).

In various tribes of India, bark and seeds of the plant are used in fever, pneumonia and

respiratory troubles (Panghal et al., 2010; Patil et al., 2008). It is also used to cure

various stomach disorders. In Nepal a root decoction is used in diarrhoea and

dysentery. Seeds are used as a digestive. A seed paste is applied to treat boils and

wounds. The root is used as astringent, anti-inflammatory, aphrodisiac, expectorant,

anthelmintic and tonic. The bark is diuretic and stomachic and useful in diarrhoea and

dysentery. Root bark and seeds are carminative, stomachic, tonic, diaphoretic and

astringent. Root bark is also used to treat bile problems, cough, diarrhoea, and

dysentery (Kunwar et al., 2009).

2.6. Phytochemistry

Stem bark of the plant contain flavonoids namely chrysin, oroxylin-A (5, 7-

dihydroxy-6-methoxy flavone) baicalien, its 6 and 7-glucuronide, scutellarin-7-

rutinoside and traces of alkaloid (Nakahara et al., 2002; Sankara et al., 1972 a,b),

hispidulin, oroxyloside methyl ester and chrysin-7- O- methyl glucoside (Rao et al.,

25

2007) tannic acid, sitosterol and galactose, biochanin-A, ellagic acid (Dalal et al.,

2004). Seeds contain ellagic acid (Vasanth et al., 1991). Yan et al. (2011) reported

nineteen different compounds isolated from seeds. Root bark of the plant contains

chrysin, baicalein, biochanin-A, and ellagic acid. Ethyl acetate extract of root is

reported to contain 2, 5-dihydroxy-6,7-dimethoxy flavone, 3, 7, 3 ' ,5

' ,-tetramethoxy-

2-hydroxy flavones, sitosterol, galactose (Zaveri et al., 2008) and a yellow crystalline

coloring matter 5,7-dihydroxy-6-methoxy flavones. Oroxylin A, chrysin, triterpene

carboxylic acid and ursolic acid are also found in fruit pods (Suratwadee et al., 2002).

Basically, O. indicum leaves are known to contain flavones and their glycosides,

baicalein (5, 6, 7-trihydroxy flavone) and its 6 and 7-glucuronides, chrysin (5,7-

dihydroxy flavone), chrysin-7-O-glucuronide, chrysin-diglucoside (Chen et al., 2003;

Chen et al., 2005), scutellarein and its 7-glucuronides, anthraquinone and aloe-

emodin (Dalal et al., 2004; Dey et al.,1978) , chrysin-7-O-glucuronide, chrysin-

diglucoside and irridoids (Yuan et al., 2008 a,b) . Chloroform extraction of defatted

leaves gives solid gummy material which yields anthraquinone and aloe-

emodine (Dey et al., 1978). Heartwood contains prunetin and sitosterol. Seeds

contain oils and flavonoids such as chrysin, oroxylin A, baicalein, baicalein-7-O-

diglucoside (Oroxylin B), baicalein-7-O-glucoside, apigenin, terpenes, alkaloids and

saponins (Tomimori et al., 1988). The seed oil contains caprylic, lauric, myristic,

palmitic, palmotoleic, stearic, oleic and linoleic acids.


Extensive pharmacological investigations have been carried out on the plant and its

phytoconstituents. A summary of the findings of these studies is presented below.


The anti-inflammatory activity has been studied in-vivo in carageenan induced rat

paw oedema model and it was reported that, both root bark and stem bark decoction

produced a considerable suppression in oedema formation against carrageenan in

comparison to the control group. The magnitude of suppression observed in decoction

prepared from stem bark was found to be more than root bark and it was concluded

that stem bark decoction of the plant can be used as anti-inflammatory drug (Doshi et

al., 2012). In another study, aqueous and alcoholic extracts were tested using three

different in vitro systems for anti-inflammatory activity of O. indicum. The aqueous

http://www.ijpsonline.com/article.asp?issn=0250-474X;year=2011;volume=73;issue=5;spage=483;epage=490;aulast=Harminder,#ref7

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26

extracts of O. indicum significantly reduced myeloperoxide release. Zaveri and Jain

(2010) also reported anti-inflammatory and analgesic activity of root bark of O.

indicum. In a study, aqueous extract of O. indicum leaves exhibited significant anti-

inflammatory activity and stem bark extract showed considerable anti-inflammatory

effects against carrageenan injection suggesting that the extract predominantly inhibit

the release of prostaglandin like substances. The anti-inflammatory activity of O.

indicum may be attributed to the presence of different chemical constituents present

within (Upaganlawar et al., 2009). A number of flavonoidal compounds have also

been reported previously as anti- inflammatory agent and in this case too, flavonoids

may be responsible for this activity. All these findings suggest that O. indicum could

be potentially used in management of chronic inflammatory conditions like arthiritis.

2.7.2. Anthelmintic activity

Anthelmintic activity of O. indicum against equine strongyle eggs was tested in-vitro

and been compared with ivermectin, one of the most effective deworming agents. At a

dose of 2×10–5 g/mL and greater, hatching of the strongyle eggs was delayed. 0%

hatching was achieved at 2×10–1 g/mL. The results of the study suggested that O.

indicum may be an appropriate anthelmintic drug against equine strongyles (Downing

et al., 2000).

2.7.3. Antibacterial activity

O. indicum is reported to possess antibacterial activity. The methanolic, ethyl acetate,

and ethanolic extracts of O. indicum stem bark were tested on three different species

of gram positive and gram negative bacteria viz. Bacillus subtilis, Escherichia coli,

and Pseudomonas aeruginosa. All of the extracts were found to possess remarkable

antibacterial properties (Das and Choudhury, 2010). The crude petroleum ether,

methanolic and ethyl acetate extracts of O. indicum root bark and the two compounds

isolated from them, 2,5-dihydroxy 6,1-dimethoxyflavone and 3,7,3‟,5‟-tetramethoxy

4‟-hydroxyflavone have been found to show moderate to good antimicrobial and

antifungal activity (Uddin et al., 2003). The three fractions, hexane, carbon

tetrachloride and chloroform obtained from methanolic stem bark extract of O.

indicum were tested for antibacterial and antifungal activity by standard disc diffusion

method against various gram-positive and gram-negative bacteria and some fungi

such as Bacillus cereus, Bacillus megaterium, Bacillus subtilis, Staphylococcus

27

aureus, and Sarcina lutea, Escherichia coli, Pseudomonas aeruginosa, Salmonella

parathyphii, Salmonella typhi, Shigella boydii, Shigella dysenteriae, Vibrio mimicus,

Saccaromyces cerevaceae, Candida albicans and Aspergillus niger. All the extracts

have been effective against both gram positive and gram negative bacteria as well as

fungi and the properties were comparable with the effectiveness of standard antibiotic

ampicillin (Islam et al., 2009). The antifungal activity of dichloromethane extract has

been studied against dermatophytes and wood rot fungi. The dichloromethane extract

was found to have significant antifungal activity (Ali et al., 1998) The antimicrobial

activity of O. indicum has also been studied against different strains of gram positive

and gram negative bacteria (Thatoi et al., 2008) like staphylococcus aureus and

Escherichia. coli. In acute toxicity test, antibacterial activity of acetone, water and

ethanolic extracts was compared. Ethanolic extract possessed maximum activity

against both strains of bacteria. The results of the study justified the use of this plant

in the management of microbial infection.

2.7.4. Antioxidant activity

The antioxidant activity of ethanol and aqueous extract of O. indicum leaves was

studied in two in-vitro models viz. radical scavenging activity by 1, 1-diphenyl-2-

picrylhydrazyl (DPPH) reduction and nitric oxide radical scavenging activity in

Griess reagent system. Ethanol extract possessed significant antioxidant activity in

both the models. In scavenging DPPH radical, extracts activity was IC 50 =24.22 μg/

ml while in scavenging nitric oxide (NO) radical, the activity was IC 50 =129.81

μg/ml. The result showed that ethanol extract of O. indicum leaves possesses free

radical scavenging activity (Upaganlawar et al., 2007).

2.7.5. Hepatoprotective activity

The hepatoprotective activity of O. indicum was studied against carbon tetrachloride

(CCl 4)-induced hepatotoxicity in mice and rats. Biochemical studies indicated that

alcoholic, petroleum ether and n-butanol extracts significantly lowered the elevated

serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvate

transaminase (SGPT), alkaline phosphatase (ALP) and total bilirubin (TB) levels as

compared to the control group. The increased lipid peroxide (LPO) formation,

reduced glutathione (GSH) and decreased antioxidant enzyme activities of superoxide

dismutase (SOD), catalase (CAT) in the tissues of CCl 4 treated animals were

28

significantly normalized by O. indicum treatment. It is suggested that plant showed

significant antioxidant activity, which might be in turn responsible for its

hepatoprotective activity (Tripathy et al, 2011).

2.7.6. Antiarthritic activity

Aqueous and ethanol extract of O. indicum were tested for in-vitro release of

myeloperoxidase (MPO) from rat peritoneal leukocytes. The results indicated that

aqueous extract had a significant effect i.e. 64% inhibition of release of

MPO (Laupattarakasem et al., 2003).

2.7.7. Immuno-stimulating activity

The immuno-modulatory activity and the mechanism of action of the n-butanol

fraction of the O. Indicum root bark, was reported by Zaveri et al. (2006) in rats using

measures of immune responses to sheep red blood cells (SRBC) haemagglutinating

antibody and delayed-type hypersensitivity (DTH) reactions. In response to SRBC,

treatment with the n-butanol fraction caused a significant rise in circulating HA titers

during secondary antibody responses, indicating a potentiation of certain aspects of

the humoral response. The treatment also resulted in a significant rise in paw edema

formation, indicating increased host DTH response. Furthermore, histopathologic

analysis of lymphoid tissues showed an increase in cellularity (Hu et al., 2010). Based

on the findings, reported immunomodulatory activity of an active fraction of O.

indicum might be attributed to its ability to enhance specific immune responses. This

also justifies the use of plant in various Ayurvedic immuno-modulatory formulations.

2.7.8. Gastro-protective activity

Zaveri and Jain (2007) reported the gastro protective activity of 50% alcoholic extract

of O. indicum root bark and its different fractions in ethanol-induced gastric mucosal

damage. n-butanol fraction was also studied in Water Immersion Plus Restraint Stress

(WIRS)-model. Alcoholic extract and its fractions showed significant reduction in

gastric ulceration against ethanol-induced gastric damage. In WIRS-model, pre-

treatment with n-butanol fraction showed significant antiulcer and antioxidant activity

in gastric mucosal homogenates, where it reversed the increase in ulcer index, lipid

peroxidation and decrease in superoxide dismutase, catalase and reduced glutathione

levels induced by stress. This study reveals significant gastroprotective effect of n-

29

butanol fraction against both ethanol and WIRS-induced gastric ulcers in rats.

Flavonoids present in the plant were found to be responsible for its gastro-protective

activity (Babu et al., 2010).

2.7.9. Anticancer activity

Several studies have proved anticancer potential of O. indicum using various models.

Narisa et al. (2006) extracted the plant with 95% ethanol and tested for cytotoxic

activity to determine the anti-proliferative effects on Hep2 cell lines. Cell proliferation

was measured using a colorimetric method based on the ability of metabolic active

cells to cleave the yellow tetrazolium salt XTT to an orange formazan dye and soluble

formazan dye was directly quantified using a scanning multiwall spectrophotometer

(ELISA plate reader). Ethanol exhibited cytotoxic activity against the Hep2 cell lines

at a concentration of 0.05%. In another study, Roy et al. (2007) reported the in-vitro

effects of baicalein on the viability and induction of apoptosis in the HL-60 cell line.

The cell viability after treating with baicalein for 24 h was quantified by counting

viable cells. It was found that baicalein caused a 50% inhibition of HL-60 cells. The

results indicate that baicalein has anti-tumor effects on human cancer cells, and O.

indicum extract could be used in supplementary cancer therapy. It was also reported

that methanolic extract of O. indicum strongly inhibited the mutagenicity of Trp-P-1

in an Ames test. The potent antimutagenicity of the extract was correlated with the

high content of baicalein (Nakahara et al., 2001).

Tepsuwan et al. (1992) reported the in-vivo genotoxic activity and cell proliferative

activity in stomach mucosa of male F344 rats by in vivo short-term methods after oral

administration of a nitrosated O. indicum fraction, which had been found to be

mutagenic without S9 mix to Salmonella typhi TA98 and TA100. Administration of

the nitrosated O. indicum fraction induced dose-dependent increases, up to 11-fold, in

replicative DNA synthesis in the stomach pyloric mucosa. These results demonstrate

that the plant has genotoxic and cell proliferative activity. On the basis of all these

findings it can be concluded that extracts of O. indicum, could be considered as

potential sources of anticancer compounds. O. indicum showed very promising results

against various diseases in experimental animals, antioxidant properties in in-vitro

and in-vivo studies against various free radicals and reactive oxygen species,

30

antimicrobial properties in in-vitro studies against various microbes and

immunomodulatory effects.

Plant materials are also used as wood, tannins and dyestuffs. Overall, it possesses

economic as well as medicinal importance. But owing to all these properties, O.

indicum has been overexploited exaggeratedly and been listed as a threatened plant

because of the extensive cut-down of this plant for medicinal and commercial

purposes. Conservation should be done on a large scale through both in-situ and ex-

situ methods in order to save this precious plant for the benefit of mankind.

31

3. Holarrhena pubescens Wall. ex G. Don

Holarrhena pubescens Wall. ex G.Don (Kutaj) belonging to family Apocyanaceae is

a small tree. Its bark is used as an astringent, anthelmentic, stomachic, febrifuge,

diuretic, and also useful in piles, dyspepsia, chest infections, amoebic dysentery, and

other gastric disorders. Increasing demand and destructive harvesting of bark has led

to the depletion of this valuable medicinal tree. Ayurveda as well as modern research

highlighted the potential of H. pubescens as an anti-dysenteric agent and have been

recommended for different ailments in various pharmacopoeias including Chinese and

Indian, beside been acknowledged by pharmacopoeias of Thailand and Europe. H.

pubescens is used in several commercial formulations viz. Mahasudarshan tablets,

Dashmularishth (Dabur India Ltd., New Delhi, India), Divya mahamanjistha

(Patanjali Ayurveda, Haridwar, India), Diacare, Diarex PFS, Diarex vet (Himalaya

Drug Co., Bangalore, India) and many others.


H. pubescens is a small tree, up to 13 m high and 1.1 m in girth with clear bole of 3-7

m. Leaves 15-30 x 4-12 cm base obtuse, rounded or acute, nerves 10-14 pairs,

opposite, sessile, elliptic or ovate, oblong, membranous, strong, arched; petiole up to

1.5 cm; cymes 3-6 cm diameter. Corymbose sessile terminal; bracts small, ciliate;

pedicels slender. Flowers inodorous white, in terminal corymbose cyme. Calyxlobe

2.5-3 mm long, oblong-lanceolate, acute, ciliate. Corolla puberulous outside; tube 8-

13 mm long, slightly inflated near the base over the stamens, mouth not closed with

ring of hair; throat hair inside; lobes equalling the tube, oblong, rounded at the apex,

more or less pubescent. Follicle divaricated, cylindrical, 15-45 cm long and 5-10 mm

in diameter, parallel, terete, corecious, obscurely lonelose, usually with dotted white

spots. Seeds 8 mm long or more, linear oblong, tipped with spreading deciduous coma

of brown hair, 22.5 cm long, light brown, 8-12 mm long, 900-1000 seeds weighing

one ounce (Oz.), 25- 30 in a follicle: coma brownish, spreading, 2.5-10 cm long

(Anonymous, 1959; Anonymous, 1982, Chopra, 1958; Collett 1971; Hussain et al.,

1992; Nadkarni,1955).

32


The tree is distributed in Asia, tropical areas of Africa, Madagascar, India, Philippines

and Malayan Peninsula. Growing up to an altitude of 1300 meters in the Himalayas,

often gregariously in deciduous forests, open waste lands and abundant in sub-

Himalayan tracts.

3.3. Phenology

The tree is deciduous in nature. Trees shed leaves during winters (Jan-Feb) and leaf

flush occurs during April. The tree flowers in the months of May-July which is

followed by fruiting (Sep-Oct).


The sectional view of the bark shows that the cork consists of 4-8 layers of

tangentially elongated; brick shaped and thin walled parenchymatous cells measuring

28-62 μ in length and 12-44 μ in width. The cork cambium or phellogen is reported to

be of single layer; the cells are tangentially elongated, 26-54 μ long 12-38 μ wide and

thin walled parenchymatous. Following, the secondary cortex is usually composed of

a wide zone of compact, thin walled, medium sized, polygonal to oval

parenchymatous cells, which measure 58-138 μ. There are strands of stone cells

interspersed in this region. Stone cells are rectangular to somewhat oval with highly

thickened and lignified walls bearing numerous simple pits and have wide lumen,

measuring 65-145 x 26-58 μ; few stone cells are noticed to possess prismatic crystals

of calcium oxalate. Mostly cells of secondary cortex also contain prismatic crystal of

calcium oxalate and they are occasionally attached with crystals fibres. Besides, the

starch grains are found in few cells of secondary cortex, which are small, simple and

oval to round in shape. Laticiferous cells are also studied in the phelloderm containing

latex. The medullary rays are bi- or triseriate in the innermost region of secondary

phloem and uniseriate medullary rays are rarely observed. The ray cells are thin

walled radially elongated parenchyma and individually measures 24- 52 x 12-27 μ but

gradually increasing in dimension towards outer ends. The secondary phloem is

generally represented by sieve tube tissues and companion cells, phloem parenchyma

and stone cells. The phloem parenchyma is thin walled, polygonal and is 16-33 μ long

and 14-26 μ wide in dimension and few of them have simple starch granules. It is also

33

noticed that some ray cells become sclerenchymatous and attached with stone cells so

that it become continuous and extended to 3 to 4 rays in tangential direction. Phloem

fibres are found absent.

3.5. Ethnobotanical/ Ayurvedic uses

The medicinal properties of the plant are well recognised in Ayurveda and almost all

classics mentioned it for the treatment of atisara, prabahika, arsha (haemorrhoids) and

especially in uonitarsha (Sharma and Dash, 2001). Traditional Ayurvedic preprations

include Kutajarishta, Kutajavaleha, Kutajaparpati, Kutajastaka kvatha, Kutajaghana

vati etc. which are used to treat dysentery, diarrhoea, fever and bacterial infections.

Bark is given either alone or with other astringent drugs in piles, colic, dyspepsia,

chest affections and diuretics; also reported to be useful in skin diseases and spleen. A

hot decoction of the drug is used as a gargle in toothache. The bark is considered to

be stomachic, astringent and febrifuge. The dried bark is rubbed over body in case of

dropsy by some tribes (Chopra et al., 1958). Leaves are used in chronic bronchitis and

locally for boils and ulcers (Anonymous 1959). The plant is used by „Santhal‟ tribes

in spleen disorders, anaemia, diarrhoea and cholera.

3.6. Phytochemistry

Most of the known chemical constituents in H. pubescens have been found in the

stem, bark, leaves and a few in the seeds as well. The major constituents are steroidal

alkaloids, flavonoids, triterpenoids, phenolic acids, tannin, resin, coumarins, saponins

and ergostenol (Alauddin and Martin, 1962; Daniel 2006; Dev 2006). The 68

alkaloids which have been discovered from various parts of H. pubescens to date are

listed below.

The major alkaloids present in all the parts of the plant are, conessine/ isoconessine

(C24H40N2), conessimine/ isoconessimine (C23H38N2), conarrhimine (C21H34N2).

In a study, Alauddin and Martin (1962) found that the plant contains conessidine

(C21H32N2), holarrhidine (C21H36N2O), kurchenine (C21H32N2O2),

holarrhessimine (C22H36N2O), holarrhine (C20H38N2O3), conkurchi nine

(C25H36N2), kurchamine (C22H36N2) and 7a-Hydroxyconessine (C24H40N2O).

Keshri et al. (2012) found that along with these alkaloids, stem bark contains,

holarrifine (C24H38N2O2), kurchamide, kurcholessine, trimethylconkurchine

34

(C24H38N2), (3),-N-methylholarrhimine (C22H38 N2O), (20),-N-

Methylholarrhimine (C22H38N2O) and NNN‟N0-tetramethylholarrhimine

(C25H44N2O)., Beside this, kurchilidine (C22H31NO), neoconessine (isomer of

conessine) (C24H40N2), holadysenterine (C23H38N2O3), kurchessine (C25H44N2),

lettocine (C17H25NO2), kurchimine (C22H36N2), holarrhenine (C24H40N2O),

holarrhimine/Kurchicine (C21H36N2O), holacine (C26H44N2O2), holafrine

(C29H46N2O2), holadysone (C21H28O4), holacetine (C21H32N2O3), 3a-

Aminoconan 5-ene (C22H36N2), dihydroisoconessimine(C23H40N2), conamine

(C22H36N2), conkurchine (C20H32N2) are also found in the plant (Chakraborty and

Brantner, 1999; Daniel 2006; Stephenson 1948; Usmani 1995; Tuntiwachwuttikul et

al., 2007). Further, some more constituents from the bark of H. pubescens were found

by Siddiqui et al. (2001) which were, pubadysone (C21H26O3), puboestrene

(C20H24O3), pubamide (C21H27NO3), holadiene (C22H31NO), kurchinidine

(C21H29NO2), kurchinine (C19H24O3), pubescine (C22H26N2O4), norholadiene

(C21H29NO), pubescimine (C24H40N2O). Holonamine, regholarrhenine A

(C22H31NO2), regholarrhenine B (C21H29NO2), regholarrhenine C (C22H34N2),

regholarrhenine D (C23H38N2O), regholarrhenine E (C25H44N2O2) and

regholarrhenine F (C25H44N2O) were some more compounds extracted from the

plant during further studies (Bhutani et al., 1988; Kumar et al., 2007). Dev (2006)

reported holantosine-A (C28H47NO6), holantosine-B (C28H45NO5), holanto sine-C

(C28H47NO6), holantosine-D (C28H45NO5), holantosine-E (C28H47NO6),

holantosine-F (C28H45NO5), holarosine A (C30H47 NO6), holarosine B

(C30H47NO6), holarricine (C21H32N2O3) alkaloids from the plant.

kurchiphyllamine, kurchaline, kurchiphylline (C23H47NO2), conimine (C22H36N2)

and antidysentericine (C23H36N2O) were some of the more alkaloids reported from

the tree (Panda et al., 2012; Verma et al., 2011).


3.7.1. Anti-diabetic efficacy

A recent study reported significant recovery in diabetic rats when they were orally

administered with ethanolic extract of seeds. Treatment showed significant decrease

in levels of blood glucose, serum cholesterol, triglyceride, aspartate transaminase,

alanine transaminase, alkaline transferase, urea, creatinine and uric acid while the

35

weight of the rats increased substantially (Keshri et al., 2012). Methanolic seed

extracts have also shown similar results in streptozotocin-induced rats (Mana et al.,

2010) Inhibition of a-glucosidase was observed in normoglycemic rats when

administered with hydro-methanolic extract of bark. This enzyme helps in absorption

of glucose from intestines and therefore, can play a major role in regulating

postprandial diabetes (Ali et al., 2011).

3.7.2. Anti-diarrhoeal property

Ethanolic seed extracts of H. pubescens in castor oil induced diarrhoea in rats in-vivo

have shown a significant increase in the dry weight of their faeces and reduction in

defecation drops. Aqueous and alcoholic bark extracts are also known to act against

entero invasive E. coli (EIEC), Shigella flexneri, Shigella boydii and Salmonella

enteritidis (Dey and De, 2012). Aqueous and methanolic leaf extracts of H. pubescens

were found to inhibit the growth of diarrhoeal pathogens Salmonella typhimurium,

Vibrio cholerae, Vibrio alginolyticus, E. coli and Salmonella typhi (Panda et al.,

2012).

3.7.3. Anti-inflammatory and analgesic property

Methanolic bark extract of H. pubescens demonstrated decreased nitric oxide and

malondialdehyde levels and increased levels of superoxide dismutase and glutathione

levels in 2, 4-Dinitrobenzene sulfonic acid induced colitis in male albino wistar rats.

The rats also resisted rupture of goblet cells; inflammation in mucosal layers and

inflammatory cellular infiltration (Darji et al., 2012). Furthermore, methanolic leaf

extracts demonstrated inhibition of rat paw oedema in carrageenan induced paw

oedema in Swiss albino mice (Ganapathy et al., 2010). H. pubescens has been

mentioned in Ayurveda to have analgesic effects. Methanol bark extract on Swiss

albino mice and wistar rats showed analgesic effects (Solanki et al., 2010).

3.7.4. Antioxidant/free radical scavenging property

It has been established that the application of free radical scavenging compounds have

healing effect and property of protecting tissue from oxidative damage. Recently in a

study that investigated antioxidant property of H. pubescens, methanolic leaf extracts

were found to scavenge superoxide ions and hydroxyl ions as well as reduced

36

capability of converting Fe3þ / Fe2þ. Further, the efficiency of these effects was

found to be proportional to the concentration of the extract (Ganapathy et al., 2011).

3.7.5. Anti-urolithic property

Crude aqueous methanolic seed extracts of H. pubescens significantly decrease the

size of calcium oxalate crystals and convert them from calcium oxalate monohydrates

(COM) to calcium oxalate dehydrate (COD) in-vitro. The extract suppresses cell

toxicity (induced by COM) and production of lactate dehydrogenase. The extract was

tested in vivo in male wistar rats, which showed substantial decrease in polyurea,

water intake, Caþþ excretion and crystal formation (Khan et al., 2012).

3.7.6. Diuretic property and anti-amoebiasis

Aqueous seed extract of H. pubescens showed a significant increase in urine output of

wistar rats at dosage range of 30-100 mg/kg. Daily intake of the bark powder for 15

days completely cured patients suffering from amoebiasis. Another clinical trial

investigated the therapeutic efficacy of “Amoebin cap”, a medicine for amoebiasis

containing H. pubescens as its major constituent (Shahabuddin et al., 2006).

3.7.7. CNS stimulant activity

Inhibition of acetylcholinesterase is desirable when treating neurological problems

such as Alzheimer‟s disease. Out of five isolated alkaloids (conessine,

isoconessimine, conessimine, conarrhimine and conimine), conessimine exhibited the

most profound effects. The study concluded that these alkaloids can be potentially

used in drugs for treating neurological disorders (Yang et al., 2012). A separate study

investigated the CNS stimulating activity of methanolic bark extract on Swiss albino

mice. The results showed that regardless of the dosage, the extract significantly

decreased and relaxed the gripping capabilities of the muscles and also the

spontaneous locomotive activity, thus indicating a depressing effect on the CNS

(Solanki et al., 2011).

3.7.8. Anthelminthic and anti-microbial activity

In-vitro activity of aqueous and ethanolic extracts bark on Pheretima posthuma

showed significant results (Patil et al., 2012). Ethanolic seed extracts showed

concentration-dependent zones of inhibition against EPEC bacterial cultures. Since

37

EPEC is resistant to many antibiotics, the ethanolic extract is considered as a

promising antibacterial agent. In one study, petroleum ether extract of bark inhibited

E. coli at 50 mg/ ml with a minimum inhibitory concentration (MIC) of 50 mg/ml

while methanol and chloroform extracts did so at higher concentrations. Yet,

compared to other plants, H. pubescens showed moderate activity (Patel et al., 2008).

Antibacterial potential of various types of extracts has been evaluated recently in a

study (Manika et al., 2013b).

3.7.9. Anti-mutagenic activity

A study investigated anti-mutagenic activity of H. pubescens, where methanolic bark

extract of the plant demonstrated anti-mutagenic potency in sodium azide and methyl

methane sulphonate induced mutagenicity in Salmonella typhimurium strains (Aqil et

al., 2008).

3.7.10. Anti-malarial activity

Bark extracts tested for in vitro and in vivo anti-malarial activity against Plasmodium

falciparum isolates and P. berghei infected Swiss mice respectively, showed

significant results (Verma et al., 2011). Compound conessine showed in vitro anti-

plasmodial activity with its IC50 value 1.9 μg/ml and 1.3 μg/ml using schizont

maturation and LDH assay respectively (Dua et al., 2013).

There is a plethora of medicinal properties exhibited by the species and these

properties make it a very useful drug for many ailments. Due to its pharmaceutical

potential, huge quantities of the crude drug has been exploited from the wild. High

levels of exploitation coupled with flawed harvesting techniques and habitat distortion

has posed severe risk to this botanical.

High level of exploitation by herbal industry, market demand and flawed harvesting

techniques coupled with low regeneration rate and habitat devastation has posed

serious threat to this highly useful botanical. Currently, it is among highly traded

species with an annual estimated trade of >2000 million tons

(http://www.nmpb.nic.in/index1.php?level=0andlinkid=90andlid=642) and the

industrial demand of this species is poised to increase owing to the worldwide

buoyancy in the herbal sector engaged in production of health care. Thus there is an

exigent need to conserve this botanical.

38

4. Terminalia arjuna (Roxb.) Wight and Arn.

Several medicinal plants have been described to be beneficial for cardiac ailments in

“Atharva Veda” an ancient treatise from which Ayurveda, the Indian system of

Medicine owes its origin (Shatvalekar 1943). The plant which has shown most

promising and distinct results among these is Terminalia arjuna Wight and Arn.,

popularly known as „Arjun‟ (Dwivedi and Udupa, 1989). The stem bark powder of

this tree has been mentioned to be useful for “hritshool” (angina) and other related

cardiac ailments by the ancient physicians.


T. arjuna is a large tree with a spreading crown and drooping branches. The tree is

usually up to 60-80 feet tall, with a trunk diameter up to 2.0-2.5 m, bole with

buttresses, outer bark flake off in pieces, inner bark whitish, exude red resin, bark

surface smooth. Leaves oblong to ovate-oblong, 8.0-15.0 cm x 4.5-9.0 cm, usually

obliquely subcordate at base, glabrescent, with 15-25 pairs of secondary veins, petiole

0.5-1.5 cm long. Flowers in an axillary or terminal panicle 2.5-6 cm long, calyx tube

glabrous outside. Fruit broadly ellipsoid, truncate at the top, 3.5-5.0 cm x 2.5-3.2 cm,

glabrous, with 5 leathery wings (Cooke 1967; Gupta 1998).

4.2. Natural Habitat

Native to India. Introduced to other countries of South East Asia. The species grows

naturally on banks of streams and rivers in central India. Now a days, cultivated too.

4.3. Phenology

It is an evergreen tree, which blossoms in the months of April-June.


Stem bark is simple, grey and smooth on external surface. The bark is thick, soft and

of red color from inside. Taste is bitter. Transverse section of the stem bark shows

cork, thin walled parenchymatous ground tissue with embedded rosette crystals of

calcium oxalate and secondary phloem with patches of sclenchyma fibres, mucilage

secreting ducts and tanniferous cells. Mature bark shows a broad zone of phloem

fibers and crystal fibres (Mitra 1985).

39

4.5. Ayurvedic/Ethnobotanical uses

T. arjuna is an important cardio-tonic plant, described in the Ayurveda. It is reported

to have Kasaya rasa, laghu guna, Shita virya, Katu vipaka and hridaya prabhav. Many

Ayurvedic formulations are made of the stem bark of plant like Arjunarishtha,

Arjunagruta, Arjnasirpak etc. The bark is said to be bitter, acrid, cooling, aphrodisiac,

expectorant, tonic, styptic, antidysenteric, purgative and laxative.

The bark, leaves and fruits of T. arjuna have been used in indigenous system of

medicine for different ailments (Warrier et al., 1996). The use of bark powder as an

astringent and diuretic finds mention in the works of Charak (Charak Samhita 1941).

The bark powder has been attributed to possess cardioprotective properties. Vagbhatta

was the first to cite this in his book „Astang Hridayam‟ (Lal Chandra 1963).

Subsequently, Chakradutta and Bhawa Prakash Mishra, described its use in chest pain

(Bajpeyee 1959; Bhawa Prakash 1963). Its use has also been advocated in urinary

discharge, strangury, leucoderma, anaemia, asthma and tumours. Traditional method

of its administration was to prepare an alcoholic decoction of its bark stem (asava) or

give it along with clarified butter (ghrita) or along with boiled milk (kshirpak)

(Nadkarni and Nadkarni, 1954; Warrier et al., 1996).

4.6. Phytochemistry

As the bark was considered to be the most important constituent from medicinal point

of view, most of the early studies were limited to bark stem of the plant. It was

initially reported that the bark had 34% ash content consisting entirely of pure

calcium carbonate. The aqueous extract revealed 23% calcium salts and 16% tannins,

whereas the alcoholic extract contained very little colouring matter and tannins

(Dymock et al., 1891). Later chemical analysis of the bark showed evidence of sugar,

tannins (12%), colouring matter, a glycoside, and carbonates of calcium, sodium and

traces of chloride of alkali metals (Ghoshal, 1909). Subsequently presence of an

alkaloid as well as a glycoside was established. Primarily an oleanane triterpenoid

termed, arjunin, and a lactone, arjunetin was isolated from the benzene and alcoholic

extracts of its bark, respectively and two more glucosides namely arjunglucoside I and

arjunglucoside II were identified (Honda et al., 1976a, b). Later on a triterpene

carboxylic acid, terminic acid, and arjunoside III and arjuno side IV were isolated

from the ethyl acetate extract of its root (Anjaneyulu and Prasad, 1982a, b). Isolation

40

of terminic acid from the roots was a very significant finding since it was for the first

time that a lup-20(29)-en derivative was isolated from nature with a hydroxyl free at

the rare C-13 position. It was also the first study of the occurrence of a lupane

derivative in any Terminalia species (Anjaneyulu and Prasad, 1983). Another

oleanane type triterpane, terminoside A has been isolated from the acetone fraction of

the ethanolic extract of its stem bark (Ali et al., 2003a,b). The structure of this new

compound was established as olean-1,3,22-triol-12-en-28- oic acid-3-d

glucopyranoside. It was also demonstrated that terminoside A inhibits nitric oxide

production and decreases inducible nitric oxide synthase levels in lipopolysacchride

stimulated macrophages. Recently another new glucoside named as 2,19-dihydroxy-3-

oxo-olean-12-en28-oic acid 28-O-d-glucopyranoside has been detected from its root

(Choubey and Srivastava, 2001). T. arjuna bark contains very high level of

flavonoids. Flavonoids detected from its bark are, arjunolone, flavones, bicalein,

quercetin, kempferol and pelorgonidin. Recently a new flavonoid named luteolin has

been isolated from 1- butanol extract. In a study it was found that T. arjuna possessed

a high phenolic content (Bajpai et al., 2005). Varieties of tannins have also been

isolated from the bark of T. arjuna. Some of the well known hydrolysable tannins

from the bark are pyrocatechols, punicallin, punicalagin, terchebulin, terflavin C,

castalagin, casuariin and casuarinin. Some 15 types of tannins and related type of

compounds have been isolated from its bark so far (Lin et al., 2001). Tannins are

known to enhance synthesis of nitric oxide and relax vascular segments precontracted

with norepinephrine. It may well be that tannins may be contributing to the reported

hypotensive action of T. arjuna bark (Takahashi et al., 1997). It is also speculated that

tannins may be responsible for its astringent, wound healing and anti microbial

activity (Chaudhari and Mengi, 2006). The bark also contains large amounts of

magnesium, calcium, zinc, copper and silica (Dwivedi and Udupa, 1989).


4.7.1. Cardiotonic activities

Studies revealed that the bark of T. arjuna possess cardio-tonic and stimulant actions

(Ghoshal 1909). Subsequently, it was found that intravenous administration of the

glycoside, obtained from the bark of T. arjuna, resulted in the rise of blood pressure

(Ghosh 1926). Later on it was detected that the bark powder, in addition to

41

cardiotonic property, also possessed diuretic properties (Caius et al., 1930). Studies

have revealed that the aqueous extract of the bark had chronotropic and inotropic

activities (Chopra et al., 1958) and intravenous administration of alcoholic extract of

T. arjuna enhanced auricular and ventricular contraction in rabbits (Gupta et al.,

1976). The cardioprotective effects of T. arjuna has been studied in isoproterenol-

induced myocardial ischemia model in rats, rabbits and mice by several authors. Bark

powder were administered to three different groups of rabbits. Another group was put

on placebo powder along with standard feed. After 90 days of drug pre-treatment the

rabbits were challenged with isoproterenol infusion through intravenous route. The

onset of myocardial ischemia and its severity both were reduced in rabbits pre-treated

with T. arjuna compared to placebo control rabbits (Dwivedi et al., 1988). In another

study, effect of a compound formulation containing T. arjuna, was studied in

isoproterenol-induced myocardial necrosis in rats. Increase in serum CPK, SGOT,

SGPT and GT following myocardial necrosis were significantly reversed. The drug

also showed 90% protection against reduction in glycogen levels in ischemic rats.

(Tandon et al., 1995). Effect of arjunolic acid derived from T. arjuna on antiplatelet

activity, electrocardiographic changes, serum marker enzymes, antioxidant status,

lipid peroxide and myeloperoxidase (MPO) were measured and compared with the

acetyl salicylic acid (ASA). Arjunolic acid treatment prevented the decrease in the

levels of SOD, CAT, glutathione peroxidase, ceruloplasmin, tocopherol, reduced

glutathione (GSH), ascorbic acid, lipid peroxide and MPO. These observations were

corroborated by histopathological studies. Cardioprotection conferred by arjunolic

acid could possibly be due to the protective effect against the damage caused by

myocardial necrosis (Sumitra et al., 2001). Role of T. arjuna as an antioxidant agent

on ischemic perfused rat heart has been studied very recently. It was showed that the

crude bark of T. arjuna augment endogenous antioxidant compounds of rat heart and

prevents it from oxidative stress (Gauthaman et al., 2005). In a subsequent work, low

doses of alcoholic extract of T. arjuna bark were tested for myocardial ischemia

induced by isoproterenol and it was found that the rats had raised myocardial

thiobarbituric acid reactive substances (TBARS) as well as increased glutathione,

superoxide dismutase and catalase levels (Karthikeyan et al., 2003). Recently

arjungenin an oleanane terpenoid derived from T. arjuna bark and its glucoside,

arjunglucoside-II, have been demonstrated to exert free radical scavenging activities

in human polymorphonuclear cells (Pawar and Bhutani, 2005). The issue of selective

42

protection of human plasma LDL against oxidation has also been addressed (Singh et

al., 2005). There are reasonably adequate investigational substantiations that T. arjuna

plays a significant role in the prevention of oxidative injury to the heart as well as to

the LDL cholesterol.

4.7.2. Hypolipidaemic activities

Hypolipidaemic effects of T. Arjuna were determined by a case controlled study in

rabbits fed on high cholesterol diet. It was established that the rabbits had a marked

reduction in total cholesterol than control (Tiwari et al., 1990). In another study a

noteworthy reduction in total and LDL cholesterol were noted in

hypercholesterolemic rabbits. It was also found that fat deposition in heart, liver and

kidney was significantly low in those who received the drug. The extract did not

adversely affect biochemical tests of liver and renal functions and haematological

parameters (Ram et al., 1997). However, it did not show any change in HDL levels.

Besides its hypotensive and potential for LVM reduction its lipid lowering activities

has been subject of recent investigations. The crude drug has been tried alone as well

as in combination with other botanical drugs. In a study it was found to decrease total

cholesterol and triglycerides and increase in HDL-cholesterol (Dwivedi et al., 2000;

Dwivedi and Gupta, 2002). In another work aimed to evaluate the effect on lipids and

nitric oxide, it was found that administration of T. arjuna bark powder along with

statin resulted in the decrease of 15% total cholesterol, 11% triglycerides and 16%

LDL-cholesterol. It emerges that the drug has enormous probabilities to correct

dyslipidemia in conjunction with statin. This proposition gains additional strength

from the recent evidence that equivalent amount of plant sterol and stanol esters when

combined with statins effectively lower the LDL cholesterol in a cost effective

manner (Blair et al., 2000; Martikainen et al., 2007).

4.7.3. Antimutagenic and Cytotoxic properties

Arjunic acid, arjungenin, arjunetin and arjunglucoside-I, were evaluated for cytotoxic

activity. Out of four compounds, arjunic acid was found significantly active against

human oral, ovarian, and liver cancer cell lines suggesting its role in cancer

treatments. Several studies regarding the potential antimutagenic properties of T.

arjuna have also been reported (Pettit et al., 1996; Scassellati et al., 1999; Woodman

43

and Chan, 2004). The effect of aqueous extracts of the plant on antioxidant defence

system in lymphoma bearing mice was evaluated and it was found that the extract

causes significant elevation in the activities of catalase, superoxide and gluthathione S

transferase. It could be inferred that antioxidant activities may play significant role in

anti carcinogenic activity by reducing the oxidative stress along with inhibition of

anaerobic metabolism (Verma and Vinayak, 2009).

4.7.4. Effect on endothelial dysfunction

On account of the rich bioflavonoid content, T. arjuna is considered to be a strong

antioxidant and an ideal agent for correction of endothelial dysfunction. Its effect on

endothelial-dependent flow mediated and endothelium independent nitroglycerine

(NTG) mediated dilatation was studied in smokers and non-smoker healthy males

(Bharani et al., 2004). Significant improvement was observed in flow-mediated

dilation after 2 weeks of T. arjuna therapy.


T. arjuna bark powder significantly reduced formalin induced paw oedema suggesting

its role in prevention of inflammation (Halder et al., 2009).

4.7.6. Anti-bacterial activity

The anti-bacterial activity of the extracts of T. arjuna was tested by agar well

diffusion method against human pathogens (E. coli, Pseudomonas aeruginosa,

Bacillus subtilis, Staphylococcus epidermidis and Staphylococcus aureus) and the

hexane fraction was found to be very potent against the pathogens (Shinde et al.,

2009).

Strong activity was also observed by methanol extracts of the plant against multi drug

resistant Salmonella typhii (Rani and Khullar, 2004). Further investigations proved

that the extracts of the stem bark exhibited potent activity against a wide range of

bacteria (Perumal et al., 1998)

The efficacy of T. arjuna to reduce atherogenic lipid levels, as an anti-ischemic agent

and as a potent antioxidant preventing LDL cholesterol oxidation and reperfusion

ischemic injury to heart have been sufficiently established in diverse investigational

and clinical studies. These properties make it a very useful drug for coronary artery

44

disease, hypertension and ischemic cardio-myopathy. Due to its pharmaceutical

potential, huge quantities of the crude drug has been exploited from the wild, thus

making this species overexploited. Although this species is under cultivation now a

days but still the ratio between demand and supply of the drug is imbalanced.

Therefore, the species need much consideration for the development of a proper

harvest system so that, the sustainable supply of the drug may be maintained.

CHAPTER 3

General Material and Methods

45

GENERAL MATERIAL AND METHODS

1. Collection of the plant materials

Various plant parts (trunk bark, branches, twigs and leaves) of targeted medicinal tree

species were collected from a population from Lucknow (latitude 26.50N and

longitude 80.50E). The samples were pooled accordingly and analyses were

performed from this homogenous sample to minimize the variations.

Trunk barks of different girth sizes were collected to find the optimum size of trunk

where accumulation of active constituent is more in the bark.

To study the effect of seasonal variations on active constituents in the targeted plants

and to see their variation in different plant parts, 50 g of different parts of the plants

were collected every month.

2. Herbarium preparation and identification

The collected plant specimens were allotted field book numbers. Specimens were first

pressed and then dried keeping in between blotting paper sheets. Blotting sheets were

changed every day till the specimens became completely dry. Specimens were then

poisoned by 0.1% mercuric chloride solution (in 70% ethanol) and then they were

pasted on standard herbarium sheets following the common technique of herbarium

prepration. The herbarium specimens were then given accession numbers and were

deposited in the National Herbarium of Medicinal and Aromatic Plants, CIMAP,

Lucknow.

The plant species were identified with the help of characters provided in the regional

and national floras and also by matching with the authentic samples lodged in the

herbaria of National Botanical Research Institute, Lucknow and CIMAP, Lucknow.

Every effort was made to bring the nomenclature up to date in the light of recent

International code on Botanical Nomenclature.

3. Processing

3.1. Drying of the plant materials

The freshly collected plant materials were dried in shade with sufficient air flow till

the equilibrium moisture content was maintained and the constant weight of the plant

46

materials was obtained. Exposure to sunlight was avoided in order to prevent the loss

of active components.

3.2. Powdering

Shade dried plant materials were coarsely ground in motor and pestle followed by fine

grinding in electrical grinder, sieved through 20 mesh stainless steel sieve and powder

of ≤0.841 mm particle size was used for the determination of proper extraction

method. To minimize the variations and to evaluate the influence of sample

preparation, all analyses were performed from this homogenous sample pro-cured

from a single source from shade dried material.

3.3. Extraction

Three types of extracts are preferred in Indian system of medicines i.e. alcoholic

extract, hydro-alcoholic extract and aqueous extract. Thus, these three kinds of

extracts were prepared for the phyto-chemical and pharmacological analysis.

A) Alcoholic extract: 500 gm of each sample was dissolved in one liter of absolute

alcohol and was allowed to stand for three days at room temperature, protected from

sunlight, and were stirred thoroughly several times a day with sterile glass rods. The

mixtures thus obtained were filtered through Whattman No. 1 filter papers. The

extraction procedure was repeated three times and a clear colorless supernatant

extraction liquid was finally obtained. The collective filtrate was concentrated up to

dryness under reduced pressure at 40oC to obtain the final extracts, which were stored

in borosilicate glass vials at 4o C prior to analysis.

B) Hydroalcoholic extract: 500 gm of each sample was dissolved in ethanol and

distilled water which were taken in the ratio of 1:1 and was allowed to stand for three

days with occasionally shaking the material several times a day. The procedure was

repeated thrice and the collective filtrate was concentrated up to dryness under

reduced pressure at 40oC to obtain the final extracts.

C) Aqueous extract: Similar protocol was followed by using distilled water as a

medium of extraction to prepare the aqueous extract. 50 µl of absolute alcohol was

added to the vessel in order to prevent any fungal growth in the medium.

47

For chemical studies (HPLC analysis) all the three kind of extracts of various plant

parts were prepared by percolating 1gm of samples in 30 ml of solvent. Extraction

procedure was repeated three times, final filtrate was concentrated and were made up

to 10 ml to maintain the concentration at 100mg/ml and finally centrifuged at 10,000

rpm for 5 min prior to injection in LC system.

4. Chemicals and reagents

HPLC grade solvents (Merck, Darmstadt, Germany) were used for chromatographic

separation. Trifluoroacetic acid (TFA) from Spectrochem, India was used for pH

adjustment of the eluent. Prior to use, all the solvents were filtered through a 0.45-μm

membrane (Millipore, Billerica, MA, USA).

5. Preparation of standard solution

Different chemical standards were used for each species which were very relevant to

the pharmacological potential of the specific plant. The reference compounds of the

species are as follows:

A. Bauhinia variegata: Apigenin, luteolin, quercetin and rutin were used as

reference compounds among which apigenin and luteolin are potentially more active

in nature. Apigenin, luteolin and quercetin were purchased from Chromadex (Life

Technologies) and rutin was purchased from Sigma-Aldrich (St. Louis, Missouri,

USA).

B. Oroxylum indicum: Oroxylin A, chrysin, baicalein, and hispidulin were used as

marker components. Chrysin and baicalein are major compounds among the four.

Chrysin, baicalein, and hispidulin were procured from Sigma-Aldrich (St. Louis,

Missouri, USA) and oroxylin A was were isolated from the roots of O. indicum in

CIMAP.

C. Holarrhena pubescens: Conessine, the most important alkaloid of the plant, was

used as marker compound which was procured from Chromadex (Life Technologies).

D. Terminalia arjuna: Arjunic acid, is the main bioactive components of T. arjuna

stem bark and reported for various biological activities. Therefore, it was used as a

reference compound for the quantification in the samples of the species. The

compound was purchased from Sigma-Aldrich.

48

6. High Performance Liquid Chromatography (HPLC) analysis

6.1. Bauhinia variegata

HPLC equipment (Shimadzu, Japan), consisting of analytical column (Chromolith

C18, 100 mm x 4.6 mm, 10 µm), pumps (LC-10AT), autoinjector (SIL-10AD) and

Photo Diode Array (PDA) detector (SPD-M10A) was used for analysis. A binary

mobile phase consisting of solvents methanol and water with 0.1% triflouroacetic acid

(40:60, v/v) was selected for the separation and quantification of marker compounds

i.e. Apigenin, luteolin, quercetin and rutin (Fig.3.1). A flow rate of 1.0 ml min-1

with

column temperature 30 C was used throughout the analysis. Photodiode array

detector was set to measure spectra from 200 to 400 nm. Analysis was performed at

the wavelength of 350 nm with a run time of 25 min. A representative chromatogram

of B. variegata is given in Fig. 3.2.

Validation was performed in compliance with ICH guidelines using adequate

statistical estimates. Validation of LC method included the evaluation of parameters

like system suitability, specificity, linearity, sensitivities, robustness, precision and

accuracy in terms of % RSD. The calibration curves were linear in the working range

of 100–500 ng ml-1

with correlation coefficients (r2) = 0.9981, 0.9990 for LU and AP,

respectively. The LOD values were found to be 17.01 and 14.91 ng, whereas LOQ

values were 56.70 and 49.70 ng for LU and AP, respectively. Values of % RSD for

robustness, precision and accuracy of method were well within the range proving

method to be robust, precise and accurate. The developed and validated method was

applied for percent content determination of marker chemicals in various plant parts

of B. variegata.

49

(a) Apigenin (b) Luteolin

(c) Quercetin (d) Rutin

Fig. 3.1. Chemical structures of the bioactive flavonoids of B.variegata.

Fig 3.2. Representative RP-HPLC chromatogram of sample track of B. variegata

measured at λ 350 nm (a) and chromatogram of standard track measured at λ 350

nm (b).

a

b

50

6.2. Oroxylum indicum

HPLC analysis was performed on a HPLC equipment (Shimadzu, Japan) consisting of

analytical column (Chromolith C18, 100 mm 9 4.6 mm, 10 μm), pumps (LC-10AT),

autoinjector (SIL-10AD), and PDA (SPD-M10A). Binary mobile phase consisting of

solvents acetonitrile and water containing 0.1 % TFA (34:66 v/v) was used for the

separation of marker compounds. A flow rate of 1.0 ml min-1 with column

temperature at 30oC was used throughout the analysis. Photo diode array detector was

set to measure spectra from 200 to 400 nm. Analysis was performed at the wavelength

of 270 nm with a run time of 15 min.

Validation was performed in compliance with ICH guidelines using adequate

statistical estimates. To assure the system suitability five successive injections (2 µl)

of standard mixture containing all four markers (100 µg ml-1

) were made. The

specificity was ascertained by analyzing standards and samples. Peak purity for

marker compounds in standard and sample track was [0.998. UV–Vis spectra of

markers in standard track were matched with the UV–Vis spectra of markers in

sample track. Spectral matching was 0.999; thus, rendering the method specificity.

The calibration curves were linear in the working range of 200–500 ng ml-1 with

correlation coefficients (r2) =0.9983, 0.9991, 0.9996, and 0.9994 for Oroxylin A,

chrysin, baicalein and hispidulin, respectively. The LOD values were found to be

22.68, 16.82, 11.44, and 13.07 ng, whereas LOQ values were 75.60, 56.06, 38.15, and

43.59 ng for compounds. Robustness of method was ascertained by introducing some

intentional alterations in certain decisive chromatographic parameters and observing

their effect on performance of the developed method in terms of standard deviations.

The developed and validated method was applied for percent content determination of

marker chemicals (Fig.3.3) in various plant parts of O. indicum. A representative

chromatogram is given in Fig. 3.4.

51

(a) Oroxylin A (b) Chrysin

(c) Baicalein (d) Hispidulin

Fig. 3.3. Chemical structures of the bioactive flavonoids of O. indicum.

Fig. 3.4. Representative RP-HPLC chromatogram of sample track of O.

indicum (a) and chromatogram of standard track (b).

a

b

52

6.3. Holarrhena pubescens

HPLC analysis was performed on a Shimadzu LC-10AD liquid chromatograph

equipped with an SPD-M1 0A VP diode array detector, an SIL-10ADVP auto injector

and a CBM-10 interface module. Data were collected and analyzed using a class LC-

10 Work Station. A pre packed Discovery (R) RP Amide C16 Supelco column (250

µm x 4.6 µm ID) column was selected for HPLC analysis. The mobile phase

consisted of Acetonitrile: Water (95:5 v/v).The flow-rate was 0.6 ml/min throughout

the isocratic run. Column temperature was maintained at 25±1oC.

System suitability was assessed by six replicate analyses of the analyte. The

acceptance criterion was ± 2% for the percentage relative standard deviation (%RSD)

of peak area and retention time. The calibration curve for conessine (Fig. 3.5) was

plotted with five different concentrations from 2.5-20 μg/mL. The detector response

was linear. The intra- and interday precision (expressed in terms of %RSD) was

observed in the range of 0.38–0.98% and 0.33-1.12%, respectively. The recovery was

found to be in the range of 98.80-101.50%. This rapid, precise, accurate and specific

RP-HPLC method was used for qualitative and quantitative analysis of conessine in

H. pubescens (Fig. 3.6).

53

Fig. 3.5. Structure of the steroidal alkaloid „conessine‟.

Fig 3.6. Representative HPLC chromatogram of sample track of

H. pubescens measured at λ 210 nm (a) and chromatogram of

standard track measured at λ 210 nm (b).

Data:25NCS-5.D01 Method:25NCS-5.M01 Ch=1

Chrom:25NCS-5.C01 Atten:9

0 5 10 15 20min

0

200

400

mAbs

Data:28NCST25.D01 Method:28NCST25.M01 Ch=1

Chrom:28NCST25.C01 Atten:9

0 5 10 15min

0

200

400

mAbs

a

b

54

6.4. Terminalia arjuna

HPLC analysis was performed according to the method developed by Verma et al.

(2012). Analysis was carried out on a Shimadzu (Japan) LC-10A gradient high-

performance liquid chromatographic instrument, equipped with two LC-10AD pumps

controlled by a CBM-10 interface module, a model SIL-10ADvp auto injector, an in-

line degasser DGU-14A and a multidimensional UV-VIS detector SPD-10A. Photo

diode array detector SPD-M10Avp (Shimadzu) was used for the peak purity and

similarity test. Solvents were pre-filtered by using a Millipore system and analysis

was performed on a Waters Spherisorb S10 ODS2 reversed- phase column, 10 µm

(250×4.6 mm, ID). The analytical parameters were selected after screening a number

of solvent systems and gradient profiles. Separation was achieved with a two pump

gradient program for pump A (acetonitrile: water, 30:70) and pump B (acetonitrile:

water, 70:30) as follows: initially 30% B, flow rate 0.8 ml/min; then increased

gradually to 50% B until 10.0 min, flow rate 0.8 ml/min; again increased gradually

50–70% B up to 30 min, flow rate 1.2 ml/min; washed the column for 20 min, 30% B,

flow rate 0.8 ml/min. The detection wavelength was 220 nm, the absorption maxima

close to all the compounds. Injection size for standard and sample was 20 µl. Column

temperature was 26 °C. Fig 3.7 and 3.8 illustrates the structure and separation in plant

sample extract, respectively.

55

Fig.3.7. Structure of oleanane triterpenoid „arjunic acid‟.

Fig 3.8. Representative HPLC chromatogram of sample track

measured at λ 220 nm (a) and chromatogram of standard track

measured at λ 220 nm (b).

CHAPTER 4

Ecological Responses to Bark Harvesting In Medicinal Tree

Species

56

ECOLOGICAL RESPONSES TO BARK HARVESTING IN MEDICINAL

TREE SPECIES

1. Introduction

There has been a rise in expectations from developing countries to commit more

towards the issue of biodiversity conservation (Adenle 2012) as they failed to achieve

the target of reducing biodiversity loss by 2010 under Convention on Biological

Diversity (CBD). South Asian centers of world consists of densely populated

developing economies struggling with plethora of problems such as population

density, health, climate change, declining ecosystem services, deforestation and

crucial biodiversity loss (Singh and Bagchi, 2013) and this loss is likely to increase

because of several reasons like weak institutional infrastructures, development

policies destroying rich floral systems, corruptions and unsustainable activities for

survival (Toit 2002). Last few decades have coincided with precipitous declines in

natural resources, especially forests (Gadgil et al., 1993). Illegal trade of NTFP‟s

particularly medicinal plants exerts a heavy cost on biodiversity (TRAFFIC 2008).

Although, this applies for all the plant population but much attention is needed for

tree species whose vital parts like roots and stem bark are harvested unsustainably,

eventually leading to their increased mortality rate. The consequential increase in the

rate of collection of these vital parts for various reasons is posing a negative impact

on their populations. These forest resources are becoming the focus of increasing

conservation concern due to the fact that these resources are being overexploited from

wild and will probably continue to be harvested from the woods itself in foreseeable

future. Therefore, sustainable management practices and appropriate conservation

strategies in addition to gathering are necessary (Cunningham 1996; Delvaux 2009;

Geldenhuys 2007). Although, some scientific principles of sustainable resource

management are relatively well established, but there has been a widespread failure to

apply these to „wild‟ populations (Ludwig 2001; Newton 2008).

The exploitation of medicinal tree species has a variable effect depending on the parts

harvested. For example, harvesting flowers, fruits and leaves has a significant impact

on regeneration and on the population viability (Hall and Bawa, 1993; Peters 1994;

Witkowski et al., 1994; Endress et al., 2004; Siebert 2004; Gaoue and Ticktin, 2008).

However, harvesting bark or roots is more damaging in terms of tree survival

57

(Cunningham 1991; Peters 1994; Witkowski et al., 1994; Davenport and Ndangalasi,

2002; Geldenhuys 2004; Vermeulen 2006; Geldenhuys et al., 2007; Vermeulen 2009).

Moreover, most medicinal plants are harvested for more than one reason (Shackleton

et al. 2002). As suggested for NTFPs (Ticktin 2005), the sustainable management of

medicinal trees requires knowledge of how different species respond to different

harvesting techniques. Not much information is available on the ecological impacts of

bark harvesting (Ticktin 2004), except for a few studies in South Africa (Geldenhuys

2004; Vermeulen 2009) and southern Africa (Geldenhuys et al. 2007).

The exploitation of medicinal plants can also affect many levels of forest ecology

from individual and population to community and ecosystem. We have to keep in

mind that millions of people depend on exploitation of the forest thus the concept of

sustainability means that we should be able to assure the maintenance of viable

populations of tree species that are harvested (Newton 2008). The challenge of the

scientific and economic community is to find a successful equilibrium between the

various needs. It should not be assumed that all species from a forest considered to be

sustainably managed will necessarily themselves be sustainably harvested, in terms of

maintaining viable populations (Ticktin 2004; Newton 2008). Ticktin (2004) reported

that between 1987 and 2003, more than half of the studies that quantitatively evaluate

the ecological inferences of harvesting NTFPs were targeted at the population level.

Smaller number of studies regarding various NTFPs was focused on the individual

tree level. In the case of bark harvesting surveys, very few studies were undertaken

either at population level or individual level.

The vascular cambium is a meristematic tissue that encircles the stem of all woody

plant species. The cambium not only maintains itself, but also generates radial files of

secondary xylem cells to its inside, and radial files of secondary phloem cells to its

outside The phloem together with the periderm forms the bark tissue which is of

primary importance because it shields the xylem from the environment, mechanical

injuries and infectious microorganisms (Biggs 1992). The non-technical term bark

includes all tissues located outside the vascular cambium. Harvesting trees for bark

leaves the sensitive cambium opened which initiates phloem damage by exposing it to

desiccation and parasitic attacks (Cunningham 2001). This interrupts the conduction

of nutrients and hormones involved in floral productions (Primack 1987) and the need

for resources to repair damage to bark could also result in lower resource allocation to

58

reproduction (Gaoue and Ticktin, 2008). Therefore, in terms of tree survival, bark

harvesting is the most dangerous practice (Davenport and Ndangalasi, 2002;

Geldenhuys 2004; Peters 1994, 1996) hence, it is imperative to understand the impact

and response of harvest on the tree before developing a sustainable harvest technique

(Ticktin 2005).

Whether bark harvesting concerns only a piece of bark or girdling (100% of

circumference debarked trunk), wounds damage the food (phloem) and water (xylem)

conducting tissues. Wounds also expose the inside of the tree to micro-organisms,

primarily bacteria and fungi that may infect and cause discoloration and decay of the

wood. Given rapid healing of wounds is vitally important for plants (Mohr and

Schopfer, 1995; Eyles et al., 2003), research on wound responses of trees is required

in order to understand the processes that favor or impede the recovery of the bark.

After bark harvesting, trees react in two ways to heal the wound: a protection reaction

and a wound closure reaction.

Large wounds may never completely close, but they may heal from the inside (Garret

and Shigo, 1978). Trees respond to wounding by “compartmentalizing” the wounded

area to limit the spread of microorganisms which is described in the

compartmentalization of decay in trees model (Shigo 1993). The formation of a

reaction zone composed of modified cells with increased resistance against the inflow

of air, desiccation and attack by microorganisms provides a boundary between

affected and unaffected tissue (Schmitt and Liese, 1993). Chemical barriers keep out

most wood-destroying microorganisms and the nature of chemical products varies

from species to species. Not only do the trees make the existing wood surrounding the

wound unsuitable for spread of decay organisms, inflow of air and desiccation; they

also try to close the injury from the outside and then continue generating new tissues.

When bark is harvested so that underlying wood is completely exposed to air, wound

closure can begin either from the margins of the wound (edge growth) or/and from the

entire exposed surface of the wounded xylem (sheet growth). A variety of living

tissue is involved in the process of wound closure for instance phloem parenchyma,

xylem parenchyma, immature xylem and cambial zone. To date, the wound closure

mechanism was only studied in a few species and all of them came from the

temperate zone (e.g. Li et al., 1982; Rademacher et al., 1984; Li and Cui, 1988; Biggs

59

1992; Lev-Yadun and Aloni, 1993; Novitskaya 1998; Oven and Torelli, 1999; Oven

et al., 1999; Stobbe et al., 2002; Frankenstein et al., 2005). The amount and rate of

tissue production following wounding varies both between and within tree species

(Gallagher and Sydnor, 1983; Martin and Sydnor, 1987; Neely 1988; Geldenhuys

2004; Vermeulen 2006; Geldenhuys et al., 2007; Vermeulen 2009).

This study examined the impact of bark harvesting on trees in order to encourage

sustainable management of medicinal trees. We presuppose that the 4 medicinal tree

species on which the study is done might vary in their capacity to recover from

wounding. In particular, the objectives of the study were to compare the bark

regenerative ability in terms of edge augmentation and sheet growth, to evaluate the

capacity of agony shoot production of the species and finally to come out with a

species-specific method for sustainable management of bark harvesting.

2. Materials and methods

2.1 Study area

The bark regeneration study was conducted in the woods of Bhinga in Uttar Pradesh,

India. This area covers 15828.94 ha which lies between 27o 40‟ 14‟‟ to 27

o 54‟ 10‟‟ N

latitude 81o 51‟ 40‟‟ to 82

o 01‟07‟‟ E longitude (Fig. 4.1) representing a typical Terai

ecosystem. The average annual precipitation is approx. 1298·2 mm. The maximum

and minimum temperatures range between 440 C and 11

0 C.

2.2 Harvest and measurement design

Woodland site, where sufficient numbers of species were available was chosen which

was situated within the forest and away from agricultural activity. Healthy trees,

which were structurally perfect with no prior debarking, were selected. The number of

individual trees per species is given in Table 4.1. The numbers of trees per species

were different due to difficulty in finding trees with an appropriate diameter according

to the species morphology and some species had been heavily harvested for timber

and bark. The selected trees were tagged and locations were marked on GPS device.

Trees were categorized into three size classes, considering the diameter class

distribution of the species as shown in Table 4.1.

60

Table 4.1. Range of diameter at breast height (d.b.h.) values of the studied tree species

Tree species N d.b.h. Categories

Small Medium Large

Bauhinia variegata 175 13.8- 22.5 cm 13-15 cm 16-18 cm >19cm

Oroxylum indicum 116 10.1-34.3 cm 10-17 cm 18-25 cm >25 cm

Holarhenna pubescens 86 4.3- 17.8 cm 4-8 cm 9-12 cm >12 cm

Terminalia arjuna 197 10.8-62.2 cm 10-24 cm 25-38 cm >38 cm N=Number of individual trees, d.b.h.=Diameter at breast height

Fig. 4.1. Location map of the study area of forests of Bhinga, Uttar Pradesh, India.

61

Wound was imposed with a sharp bladed axe cutting the bark down and then

removing it from the trunk by tapping with an upholstery hammer. The harvested area

consisted of 25 cm of bark vertically and lateral extend varied in each which consisted

of 25% of the total circumference of the tree. To compare the different techniques on

bark regeneration capacity, three treatments were used on each tree as shown in Fig.

4.2 and Fig. 4.3.

Total bark removal (TreatmentA): Total bark along with the cambium was removed,

so that the wood was exposed (commercial bark harvesting method),

Partial bark removal (Treatment B): The bark was harvested leaving the sensitive

cambium in-tact with the tree,

Cover treatment (Treatment C): Partial harvesting was followed by covering the

wound immediately with a thin layer of autoclaved wet soil and wrapping it with fine

muslin cloth.

The primary debarking was done at breast height above the ground, and the other two

treatments were made above and below the central wound, respectively, leaving a

distance of 3 cm between each other. The treatments were completely randomized in

design. In case the tree forked below breast height, the trunk with higher d.b.h. was

chosen for treatment. Bark was collected from all species according to the same

protocol. Harvesting was done in May 2009. All trees were monitored every three

months of bark harvesting. In the third treatment, the covering was found frayed and

remnants were attached in most of the trees during the first assessment, which were

removed manually for evaluation. The final data and information was recorded after

two years of harvest.

The effect was observed in terms of sheet development, edge augmentation and

vegetative growth (number of agony shoots). The scale used to estimate the

percentage of trunk debarked as well as the following assessments were adapted from

Vermeulen and Geldenhuys (2004). The measurements included:

Sheet growth: It was recorded as percentage of the harvested area showing phellogen

sheet growth i. e. live tissue development on the wound surface. For bark removal, it

refers to the amount of live tissue developed on the soft remaining inner bark.

62

Edge augmentation: This was recorded as a percentage of the edge of the wound

showing phellogen growth i.e. tissue showing wound recovery from underneath the

bark. The measurements were taken in the terms of six horizontal measurements (cm)

from fixed points drawn on both sides (left and right) of the wound. To calculate the

total edge growth (cm), the mean value of these three measurements was added for

both sides (left and right), calculating the mean edge recovery rate.

Agony shoot development: The presence and number of vegetative shoots developing

on the stem around the wound were recorded.

3. Statistical analysis

For harvest response, data were summarized as Mean ± SD. For each size, the effect

of treatments and periods (months) on edge growth and sheet growth were compared

separately by two factor repeated measures analysis of variance (ANOVA) using

general linear models (GLM) and the significance of mean difference within and

between the groups was done by Tukey‟s post hoc test. For each size and treatment,

the increase (rate of change: slope) in edge growth and sheet growth over the periods

was assessed by simple linear regression analysis using period as independent

variable and response the dependent variable. For each size, the rate of change (i.e.

comparison of slope) between treatments was compared by independent Student t test.

A two-sided (α=2) p<0.05 was considered statistically significant.

63

(a) (b)

(c) (d)

Fig. 4.2.Harvest design and bark regrowth in B. variegata (a,b) and O. indicum

(c,d).

64

(a) (b)

(c) (d)

Fig. 4.3. Harvest design and bark regrowth in H. pubescens (a,b) and T. arjuna

(c,d).

65

4. Results


The present study evaluates the effect of three treatments and periods on edge

augmentation (%) and sheet growth (%) of B. variegata. A total of 189 healthy trees

(d.b.h. 13.08 cm–22.35 cm) were selected and evaluated. Trees were categorized into

three size classes, considering the diameter class distribution of the species as 13-15

cm d.b.h. (small), 16-18 cm d.b.h. (Medium), >19 cm d.b.h. (Large). The effect of

treatments and periods on both edge and sheet growth of different sizes were

evaluated and are summarized below.

4.1.1. Edge augmentation

Small size

The effect of treatments and periods on edge augmentation (growth) of small sized

(d.b.h.13-15 cm) trees of B. variegata are summarized in Table 4.2 and also shown

graphically in Fig. 4.4. The mean edge augmentation in all three treatments increase

with time (month) and the increase was evident highest in treatment C followed by

treatment B and treatment A.

Comparing the effect of both treatments and periods on edge augmentation, ANOVA

revealed significant effect of both, treatments (F=1054.29, p<0.001) and periods

(F=7150.68, p<0.001) on edge augmentation. Further, the interaction effect of both

(treatments x periods) on edge augmentation was also found significant (F=401.83,

p<0.001).

Comparing the mean edge augmentation within the groups (i.e. between periods),

Bonferroni test revealed significant (p<0.001) increase in edge augmentation over the

periods in all three treatments.

Similarly, comparing the mean edge augmentation between the groups, Bonferroni

test revealed significantly (p<0.001) different and higher edge augmentation in both

treatment B and treatment C as compared to treatment A at all periods. Further, the

mean edge augmentation of treatment C was also found significantly (p<0.001)

different and higher as compared to treatment B at all periods except 6 month.

66

Table 4.2. Edge augmentation (%) of three treatments over the periods in small sized

trees (d.b.h. 13-15 cm) of B. variegata

Duration Edge augmentation (%)

Treatment A Treatment B Treatment C

3 Months 5.08 ± 1.06 10.12 ± 1.33 16.82 ± 2.69

6 Months 7.11 ± 1.49 13.70 ± 1.81 21.03 ± 3.36

9 Months 20.04 ± 3.71 31.7 ± 3.27 60.42 ± 2.43

12 Months 21.06 ± 3.58 32.52 ± 2.77 64.50 ± 2.38

15 Months 24.75 ± 5.18 38.01 ± 3.46 64.69 ± 1.81

18 Months 27.15 ± 5.18 40.68 ± 2.57 67.49 ± 2.96

21 Months 33.34 ± 3.92 46.74 ± 3.83 69.80 ± 1.99

24 Months 33.85 ± 3.77 47.75 ± 3.79 70.09 ± 2.03

±=Standard deviation

Fig. 4.4. Mean edge augmentation of three treatments over the periods in small sized

(d.b.h. 13-15 cm) trees of B. variegata.

Size 13-15 cm

Interaction effect (groups x periods): F(14, 546)=401.83, p<0.001

Treatment A

Treatment B

Treatment C3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Periods (months)

-10

0

10

20

30

40

50

60

70

80

Mean e

dge g

row

th (

%)

67

Medium size

The effect of treatments and periods on edge augmentation of medium sized

(d.b.h.16-18 cm) trees of B. variegata are summarized in Table 4.3 and also shown

graphically in Fig. 4.5. Results reveal that the mean edge augmentation in all three

treatments increases with time (month) and the increase was highest in treatment C

followed by treatment B and treatment A.


revealed significant effect of both treatments (F=1400.87, p<0.001) and periods


treatments and periods was also found significant (F=607.51, p<0.001).

Comparing the mean edge augmentation within the groups, Bonferroni test revealed

significant (p<0.001) increase in edge augmentation over the periods in all three

treatments except 18 and 24 month in both treatment B and treatment C, and from 21

to 24 month in treatment C.




mean edge augmentation of treatment C was found moderately (p<0.05) different and

higher as compared to treatment B from 3 to 12 month.

68

Table 4.3. Edge augmentation (%) of three treatments over the periods in medium sized

trees (d.b.h. 13-15 cm) of B. variegata.



3 Months 7.38 ± 1.31 13.58 ± 2.53 17.05 ± 1.67

6 Months 9.71 ± 1.73 17.46 ± 3.25 28.75 ± 2.50

9 Months 24.47 ± 4.35 38.96 ±5.47 74.61 ± 4.51

12 Months 25.25 ± 4.49 42.15± 5.75 76.51 ± 3.52

15 Months 29.52 ± 5.25 48.27 ± 4.03 79.11 ± 3.54

18 Months 31.89 ± 5.67 51.87 ± 4.22 79.80 ± 3.37

21 Months 37.71 ± 3.16 56.40 ± 3.99 81.27 ± 2.30

24 Months 38.84 ± 2.76 58.02 ± 3.98 81.53 ± 2.35


Size 16-18 cm

Interaction effect (groups x periods): F(14, 777)=607.51, p=0.001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Periods (months)

-10

0

10

20

30

40

50

60

70

80

90

100

Mea

n e

dge

gro

wth

(%

)

Fig. 4.5. Mean edge augmentation of three treatments over the periods in medium sized


69

Large size

The effect of treatments and periods on edge augmentation of large sized (d.b.h.>19

cm) trees of B. variegata are summarized in Table 4.4 and shown graphically in Fig.

4.6. Data shows that the mean edge augmentation in all three treatments increase with

time which was again highest in treatment C followed by treatment B and treatment

A.




on edge augmentation was also found significant (F=1116.14, p<0.001).


periods in treatment during comparison of the mean edge augmentation within the

groups. In treatment C, the edge increase significantly (p<0.001) up to 21 month and

then showed no significant change during the last 3 months in contrary to treatment A

and B, in which increase was noted throughout the experimental period.

Comparing the mean edge augmentation between the groups, Bonferroni test revealed

significantly (p<0.001) different and higher edge augmentation in both treatment B

and treatment C as compared to treatment A at all periods.

70

Table 4.4. Edge augmentation (%) of three treatments over the periods in large sized trees

(d.b.h.>19 cm) of B. variegata



3 Months 17.99 ± 1.57 19.32 ± 1.57 21.96 ± 1.10

6 Months 20.33 ± 1.31 22.77 ± 1.15 33.53 ± 1.55

9 Months 34.40 ± 3.00 51.47 ± 3.07 81.74 ± 2.82

12 Months 35.18 ± 2.77 53.20 ± 2.91 83.77 ± 2.14

15 Months 41.26 ± 3.18 61.89 ± 3.61 84.83 ± 2.14

18 Months 42.60 ± 2.44 63.76 ± 3.01 88.78 ± 3.17

21 Months 46.90 ± 2.58 68.03 ± 2.66 89.84 ± 2.84

24 Months 48.07 ± 2.59 69.00 ± 2.86 90.42 ± 2.99


Size >19 cm


Treatment A

Treatment B


Periods (months)

0

10

20

30

40

50

60

70

80

90

100

Mea

n e

dg

e g

row

th (

%)

Fig. 4.6. Mean edge augmentation of three treatments over the periods in large sized

(d.b.h. >19 cm) trees of B. variegata.

71

Total edge augmentation

For each Small (13-15 cm), Medium (16-18 cm), Large (>19cm) and total size of B.

variegata, the data on the effect of three treatments (treatment A, B and C) and

periods (3-24 month) on edge growth is given in Table 4.5 and the result is

summarized graphically in Fig. 4.7.

The result shows that the improvement was evident in size, treatment and time. For

each size, comparing the effect of treatments and periods on edge growth, ANOVA

revealed significant effect of treatments (Small: F=1054.29, p<0.001; Medium:

F=1400.87, p<0.001; Large: F=1292.28, p<0.001; Total: F=581.31, p<0.001) and

periods (Small: F=7150.68, p<0.001; Medium: F=8814.57, p<0.001; Large:

F=16337.86, p<0.001; Total: F=11320.12, p<0.001) on edge growth. Further, the

interaction effect (treatments x Periods) of both on edge growth was also found to be

significant (Small: F=401.83, p<0.001; Medium: F=607.51, p<0.001; Large:

F=1116.14, p<0.001; Total: F=725.97, p<0.001).

72

Table 4.5. Edge augmentation (%) of three treatments over the periods inclusive of all

size class in B. variegata



3 Months 9.25 ± 5.26 13.89 ± 3.97 18.38 ± 2.83

6 Months 11.49 ± 5.40 17.58 ± 4.16 27.49 ± 5.45

9 Months 25.50 ± 6.64 39.75 ± 8.55 71.89 ± 9.03

12 Months 26.36 ± 6.57 41.83 ± 8.84 73.25 ± 9.60

15 Months 30.89 ± 7.87 48.37 ± 9.65 75.98 ± 8.47

18 Months 33.01 ± 7.35 51.26 ± 9.29 78.13 ± 8.67

21 Months 38.58 ± 6.07 56.21 ± 8.72 79.76 ± 7.94

24 Months 39.53 ± 6.14 57.48 ± 8.73 80.11 ± 8.05


Total edge growth



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Periods (months)

0

10

20

30

40

50

60

70

80

90

Mean

ed

ge g

row

th (

%)

Fig. 4.7. Mean edge augmentation of three treatments over the periods in all tree size

(d.b.h. 13->19 cm) class in B. variegata.

73

4.1.2. Sheet growth

Small size

The effect of treatments and periods on sheet growth of small sized (d.b.h. 13-15 cm)

trees of B. variegata are summarized in Table 4.6 and also shown graphically in Fig.

4.8. It was noted that the mean sheet growth in all three treatments increase with time

(month) and the increase was highest in treatment A followed similarly by treatment

B and treatment C.

Comparing the effect of both treatments and periods on sheet growth, ANOVA




p<0.001).

Comparing the mean sheet growth within the groups (i.e. between periods),

Bonferroni test revealed significant (p<0.001) increase in sheet growth of treatment A

and C up to the cease of experimental duration and treatment B up to 18 month.

Similarly, comparing the mean sheet growth between the groups, Bonferroni test

revealed significantly (p<0.001) different and higher sheet growth in both treatment B

and treatment C from 3 to 15 month while significantly (p<0.001) lower from 15 to

24 month as compared to treatment A, whereas, treatment A showed consistency in

the recovery throughout the period.

74

Table 4.6. Sheet growth (%) of three treatments over the periods in small sized trees

(d.b.h. 13-15 cm) of B. variegata

Duration Sheet growth (%)


3 Months 0.22 ± 0.17 0.63 ± 0.22 0.63 ± 0.27

6 Months 0.39 ± 0.22 0.94 ± 0.33 1.30 ± 0.33

9 Months 0.57 ± 0.21 1.33 ± 0.29 1.75 ± 0.27

12 Months 0.82 ± 0.22 1.48 ± 0.24 1.90 ± 0.29

15 Months 0.99 ± 0.30 1.71 ± 0.31 2.00 ± 0.31

18 Months 1.03 ± 0.31 1.76 ± 0.29 2.05 ± 0.31

21 Months 1.09 ± 0.29 1.78 ± 0.28 2.18 ± 0.30

24 Months 1.10 ± 0.31 1.79 ± 0.31 2.28 ± 0.29


Size 13-15 cm


Treatment A

Treatment B


Periods (months)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Mea

n s

heet

gro

wth

(%

)

Fig. 4.8. Mean sheet growth of three treatments over the periods in small sized


75

Medium size

The effect of treatments and periods on sheet growth of medium sized (d.b.h. 16-18

cm) trees of B. variegata are summarized in Table 4.7 and also shown graphically in

Fig. 4.9. Results show that the mean sheet growth in all three treatments increases

with time (month) and the increase was evident highest in treatment A followed

similarly by treatment B and treatment C.





p<0.001).

Bonferroni test revealed significant (p<0.001) increase in sheet growth of all the

treatments constantly throughout the experimental duration.

While comparing the mean sheet growth between the groups, Bonferroni test revealed

significantly (p<0.001) different and higher sheet growth in both treatment B and

treatment C from 3 to 15 month while significantly (p<0.001) lower from 21 to 24

month as compared to treatment A.

76

Table 4.7. Sheet growth (%) of three treatments over the periods in medium sized trees

(d.b.h. 16-18 cm) of B. variegata



3 Months 0.24 ± 0.12 0.81 ± 0.26 1.05 ± 0.29

6 Months 0.43 ± 0.21 1.24 ± 0.22 1.70 ± 0.28

9 Months 0.66 ± 0.19 1.83 ± 0.32 2.36 ± 0.33

12 Months 0.98 ± 0.24 1.95 ± 0.27 2.42 ± 0.30

15 Months 1.09 ± 0.21 2.17 ± 0.22 2.52 ± 0.35

18 Months 1.12 ± 0.20 2.20 ± 0.21 2.57 ± 0.34

21 Months 1.17 ± 0.19 2.22 ± 0.23 2.72 ± 0.30

24 Months 1.20 ± 0.20 2.23 ± 0.26 2.78 ± 0.32


Size 16-18 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Periods (months)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Mea

n s

hee

t gro

wth

(%

)

Fig. 4.9. Mean Sheet growth of three treatments over the periods in medium sized (d.b.h.

16-18 cm) trees of B. variegata.

77

Large size

The effect of treatments and periods on sheet growth of large sized (d.b.h. >19 cm)

trees of B. variegata are summarized in Table 4.8 and also shown graphically in Fig.

4.10. Figure shows that the mean sheet growth in all three treatments increases with

time (month) and the increase was evident highest in treatment C followed similarly

by treatment B and treatment A.





p<0.001).

Comparing the mean sheet growth within the groups, Bonferroni test revealed

significant (p<0.001) increase in sheet growth of treatment A ups to 21 month,

treatment B up to 18 month and treatment C up to 12 month while in rest of the

periods it remains similar (p>0.05) between the periods i.e. not differed statistically.

78

Table 4.8. Sheet growth (%) of three treatments over the periods in large sized trees

(d.b.h. >19 cm) of B. variegata



3 Months 0.78 ± 0.14 0.98 ± 0.34 1.42 ± 0.27

6 Months 1.09 ± 0.25 1.52 ± 0.21 2.35 ± 0.34

9 Months 1.35 ± 0.18 2.04 ± 0.30 2.80 ± 0.39

12 Months 1.62 ± 0.21 2.11 ± 0.28 2.86 ± 0.40

15 Months 1.72 ± 0.18 2.27 ± 0.25 2.94 ± 0.41

18 Months 1.75 ± 0.20 2.33 ± 0.26 2.95 ± 0.41

21 Months 1.79 ± 0.22 2.37 ± 0.29 3.04 ± 0.47

24 Months 1.80 ± 0.23 2.40 ± 0.32 33.14 ± 0.44


Size >19 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Periods (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Mea

n s

heet

grow

th (

%)

Fig. 4.10. Mean Sheet growth of three treatments over the periods in large sized

(d.b.h. >19 cm) trees of B. variegata.

79

Total sheet growth

For each Small (13-15 cm), Medium (16-18 cm), Large (>19cm) and Total size of B.

variegata trees, the effect of three treatments and periods on sheet growth are

summarized in Table 4.9 and graphically in Fig. 4.11 to get a clear picture of the

same.

For each size, comparing the effect of treatments and periods on sheet growth,

ANOVA revealed significant effect of treatments (Small: F=100.87, p<0.001;

Medium: F=368.34, p<0.001; Large: F=101.88, p<0.001; Total: F=222.78, p<0.001)

and periods (Small: F=1253.47, p<0.001; Medium: F=1768.25, p<0.001; Large:

F=698.98, p<0.001; Total: F=3275.03, p<0.001) on sheet growth. Further, the

interaction effect of both on sheet growth was also found to be significant (Small:

F=35.53, p<0.001; Medium: F=49.62, p<0.001; Large: F=15.91, p<0.001; Total:

F=84.64, p<0.001).

4.1.3. Agony shoots

Only 4 trees were able to produce agony shoot by the end of observation period. It

could be inferred that the species is deficient in producing vegetative shoots in

response to wounding.

80

Table 4.9. Sheet growth (%) of three treatments over the periods inclusive of all size class in

B. variegata



3 Months 0.36 ± 0.27 0.79 ± 0.30 1.01 ± 0.41

6 Months 0.58 ± 0.37 1.21 ± 0.34 1.73 ± 0.50

9 Months 0.80 ± 0.36 1.72 ± 0.41 2.27 ± 0.51

12 Months 1.08 ± 0.39 1.84 ± 0.36 2.36 ± 0.48

15 Months 1.21 ± 0.38 2.05 ± 0.34 2.46 ± 0.50

18 Months 1.25 ± 0.37 2.09 ± 0.34 2.50 ± 0.49

21 Months 1.30 ± 0.36 2.12 ± 0.35 2.63 ± 0.48

24 Months 1.31 ± 0.37 2.13 ± 0.37 2.71 ± 0.47


Total sheet growth



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Periods (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Mea

n s

hee

t gro

wth

(%

)

Fig.4.11. Mean sheet growth of three treatments over the periods in all tree size class

in B. variegata.

81

4.1.4. Correlation and regression

The three treatments showed significant increase in both edge augmentation and sheet

growth in small size, medium size and large size; and total size (small + medium +

large) of all B. variegata over the periods. To see the change or rate of change in

both edge augmentation and sheet growth between the treatments, the overall mean

(small + medium + large) of both edge augmentation and sheet growth were regressed

against the time (month) and summarized in Table 4.10 and also shown graphically in

Fig. 4.12. The edge augmentation and sheet growth both showed significant

(p<0.001) and positive (direct) correlation with time in all the three treatments.

The slope (b) of regression analysis which express rate of change (i.e. improvement)

showed highest improvement in edge growth of treatment C followed by treatment B

and treatment A and increases with the size (Table 4.11). For each size, comparing

the slopes between the treatments, t test revealed significantly (p<0.01 or p<0.001)

different and higher slope at all sizes of both treatment B and treatment C as

compared to treatment A. Further, the rate of change of treatment C in every size was

also found to be significantly (p<0.05 or p<0.01) different and higher as compared to

treatment B except, Large.

The regression analysis revealed highest improvement (b: rate of change) in sheet

growth of treatment C followed by treatment B and the least in treatment A and

increases with the size. For each size, comparing the slopes between the treatments, t

test revealed significantly (p<0.01 or p<001) different and higher rate of change or

improvement in sheet growth of all sizes of treatment C as compared to treatment A,

except Large. Further, the rate of change in sheet growth of treatment B in Medium

and Total was also found to be significantly (p<0.01) different and higher as

compared to treatment A. However, improvement in sheet growth at all sizes did not

differed (p>0.05) between treatment B and treatment C i.e. found to be statistically

the same.

82

Table 4.10. Correlation and simple linear regression analysis of total edge augmentation and sheet

growth with time in B. variegata.

Total

growth

Treatment r R2 b Regression equation

Edge

A 0.97 0.94 1.64 y= 1.64x + 4.21

B 0.95 0.91 2.40 y= 2.40x + 7.41

C 0.88 0.78 3.39 y= 3.39x + 15.45

Sheet

A 0.95 0.90 0.05 y= 0.05x + 0.22

B 0.90 0.80 0.08 y= 0.08x + 0.58

C 0.87 0.77 0.10 y= 0.10x + 0.80

Table 4. 11. Comparison of rate of change (regression slope: b) in total edge augmentation and

sheet growth in B. variegata between the treatments by t test.

Comparisons Total edge augmentation Total sheet growth

Treatment A vs. TreatmentB 6.98***

3.89***

Treatment A vs. TreatmentC 6.43***

5.04***

Treatment B vs. TreatmentC 3.17**

1.57ns

ns- p>0.05, **- p<0.01, ***- p<0.001

83

Total edge growth (%)

0 3 6 9 12 15 18 21 24

0

10

20

30

40

50

60

70

80

90

100Treatment A

Treatment B

Treatment C

Treatment A: y= 1.64x + 4.21

Treatment B: y= 2.40x + 7.41

Treatment C: y= 3.39x + 15.45

Periods (month)

Mea

n

Total sheet growth (%)

0 3 6 9 12 15 18 21 24

0

1

2

3

4

5Treatment A

Treatment B

Treatment C




Periods (month)

Mea

n

Fig. 4.12. Regression analysis summary of Total edge augmentation and sheet growth

in B. variegata

Total edge augmentation (%)

84


The present study evaluates the effect of three treatments and periods on edge

augmentation (%) and sheet growth (%) of O. indicum. A total of 116 trees were

selected and evaluated. Further these were devided into three size classes according to

their sizes i.e. small size (d.b.h.10-17cm), medium size (d.b.h.17-25 cm) and large

size (d.b.h.>25 cm). The effect of treatments and periods on both edge and sheet

growth of different sizes of O. indicum trees are summarized below.


Small size

The effect of treatments and periods on edge augmentation (growth) of small sized

(d.b.h. 10-17 cm) trees of O. indicum are summarized in Table 4.12 and also shown

graphically in Fig. 4.13. Results showed that the mean edge augmentation in all three

treatments increase with time (month) and the increase was evident highest in

treatment C followed by treatment B and treatment A, the least.





p<0.001).

Comparing the mean edge augmentation within the groups (i.e. between periods),







different and higher as compared to treatment B at all periods except 3 month and 24

month.

85

Table 4.12. Edge augmentation (%) of three treatments over the periods in small

sized (d.b.h. 10-17 cm) trees of O. indicum



3 Months 8.96 ± 1.56 20.10 ± 4.41 24.00 ± 3.96

6 Months 15.54 ± 1.99 30.33 ± 3.89 41.42 ± 6.35

9 Months 24.83 ± 1.91 43.07 ± 2.04 54.61 ± 6.18

12 Months 32.92 ± 1.74 54.17 ± 4.16 69.53 ± 5.00

15 Months 42.90 ± 2.96 64.58 ± 4.47 82.77 ± 5.04

18 Months 53.65 ± 4.59 75.48 ± 2.48 93.37 ± 3.05

21 Months 62.72 ± 3.07 85.98 ± 4.24 98.08 ± 1.09

24 Months 69.4 ± 3.74 97.5 ± 1.97 100.0 ± 0.00


Size 10-17 cm

Interaction effect (groups x period): F(14, 483)=42.591, p< 0.001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-10

0

10

20

30

40

50

60

70

80

90

100

110

120

Me

an

ed

ge

gro

wth

(%

)


(d.b.h. 10-17 cm) trees of O. indicum.

86

Medium size

The effect of treatments and periods on edge augmentation of medium sized (d.b.h.

17-25 cm) trees of O. indicum are summarized in Table 5.13 and also shown

graphically in Fig. 5.14. Results showed that the mean edge augmentation in all three

treatments increase with time (month) and the increase was apparent to be highest in

treatment C followed by treatment B while treatment A was found to be least

effective.






significant (p<0.001) increase in edge augmentation over the periods in all three

treatments except 21 and 24 month in both treatment A and treatment B, and from 18

to 24 month in treatment C.




mean edge augmentation of treatment C was also found moderately (p<0.05) different

and higher as compared to treatment B from 3 to 12 month.

87

Table 4.13. Edge augmentation (%) of three treatments over the periods in medium

sized (d.b.h. 17-25 cm) trees of O. indicum



3 Months 12.11 ± 2.87 22.81 ± 3.09 29.65 ± 3.45

6 Months 23.01 ± 0.86 43.06 ± 3.11 51.06 ± 2.53

9 Months 37.24 ± 3.65 60.90 ± 3.07 66.00 ± 3.43

12 Months 48.09 ± 3.13 75.53 ± 1.71 78.57 ± 3.05

15 Months 58.36 ± 1.68 90.23 ± 2.81 93.04 ± 1.43

18 Months 64.27 ± 3.04 96.29 ± 2.58 97.29 ± 2.76

21 Months 70.83 ± 3.13 99.41 ± 0.74 99.71 ± 0.69

24 Months 73.8 ± 3.13 100.0 ± 0.00 100.0 ± 0.07


Size 17-25 cm

Interaction effect (groups x period): F(14, 420)=52.035, p>0.0001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

90

100

110

Mea

n e

dg

e g

row

th (

%)



88

Large size

The effect of treatments and periods on edge augmentation of large sized (d.b.h.>25

cm) trees of O. indicum are summarized in Table 4.14 and also shown graphically in

Fig. 4.15. Data showed that the mean edge augmentation in all three treatments

increase with time (month) and the increase was evident maximum in treatment C







periods in treatment during comparison of the mean edge augmentation within the

groups. On the contrary, in treatment B, it increase significantly (p<0.001) up to 18

month and was constant till end of the experimental period i.e. remain statistically the

same. In contrast, in treatment C, it increase significantly (p<0.001) only up to 15

month.





dissimilar and higher as compared to treatment B from 3 to 15 month and rest of the

periods it was similar between the treatments.

89

Table 4.14. Edge augmentation (%) of three treatments over the periods in large sized

(d.b.h. >25 cm) trees of O. indicum



3 Months 13.79 ± 1.69 26.42 ± 3.14 35.37 ± 3.13

6 Months 25.98 ± 3.14 45.91 ± 2.60 53.29 ± 3.52

9 Months 39.30 ± 2.68 62.39 ± 2.83 67.86 ± 2.85

12 Months 51.00 ± 1.74 78.00 ± 3.14 83.44 ± 2.96

15 Months 60.62 ± 2.84 93.58 ± 1.69 98.02 ± 1.52

18 Months 69.53 ± 2.80 98.42 ± 1.40 99.52 ± 0.95

21 Months 75.5 ± 3.52 99.3 ± 1.21 100.0 ± 0.00

24 Months 79.9 ± 1.615 100.0 ± 0.00 100.0 ± 0.00


Size >25 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

90

100

110

Me

an

ed

ge

gro

wth

(%

)


(d.b.h. >25 cm) trees of O. indicum.

90

Total size

The effect of treatments and periods on sheet growth of total trees of O. indicum,

irrespective of tree size is summarized in Table 4.15 and has been shown graphically

in Fig. 4.16. Data showed that the mean edge augmentation in all three treatments

increase with time (month) and the increase was evident maximum in treatment C

followed by treatment B and treatment A was found to be the least effective method.






significant (p<0.001) increase in edge augmentation over the periods in both

treatment A and treatment B. However, in treatment C, it increase significantly

(p<0.001) only up to 18 month.





different and higher as compared to treatment B from 3 to 18 month and rest of the

periods it was similar between the treatments.

91

Table 4.15. Total edge augmentation (%) of three treatments over the periods in all

size class of O. indicum



3 Months 11.39 ± 2.91 22.81 ± 4.43 29.13 ± 5.83

6 Months 21.01 ± 4.95 39.02 ± 7.69 48.02 ± 6.96

9 Months 33.10 ± 7.15 54.54 ± 9.45 62.19 ± 7.53

12 Months 43.14 ± 8.47 68.10 ± 11.50 76.52 ± 6.99

15 Months 53.11 ± 8.51 81.41 ± 13.77 90.55 ± 7.24

18 Months 61.73 ± 7.30 88.97 ± 10.92 96.43 ± 4.28

21 Months 69.09 ± 6.23 94.27 ± 7.09 99.17 ± 1.16

24 Months 73.87 ± 5.25 99.03 ± 1.73 99.99 ± 0.04


Total edge growth



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

90

100

110

Mean e

dge g

row

th (

%)

Fig. 4.16. Mean edge augmentation of three treatments over the periods in all size class

of O. indicum.

92

4.2.2. Sheet growth

Small size

The effect of treatments and periods on sheet growth of small sized (d.b.h. 10-17 cm)

trees of O. indicum are summarized in Table 4.16 and also shown graphically in Fig.

4.17. Result revels that the mean sheet growth in all three treatments increase with

time (month) and the increase was evident highest in treatment A followed similarly

by treatment B and treatment C.





p<0.001).

Comparing the mean sheet growth within the groups (i.e. between periods),

Bonferroni test revealed significant (p<0.001) increase in sheet growth of treatment A

up to 21 month, treatment B up to 15 month and treatment C up to 12 month while in

rest of the periods it remains similar (p>0.05) between the periods i.e. did not change

statistically.




24 month as compared to treatment A. Further, the mean sheet growth of treatment C

was also found significantly (p<0.001) higher from 9 to 12 month as compared to

treatment B; however, in rest of the periods it not differed (p>0.05) between the two

groups i.e. found to be statistically the same.

93

Table 4.16. Sheet growth (%) of three treatments over the periods in small sized

(d.b.h. 10-17 cm) trees of O. indicum



3 Months 0.50 ± 0.03 0.45 ± 0.02 0.47 ± 0.10

6 Months 0.76 ± 0.03 1.05 ± 0.02 1.07 ± 0.07

9 Months 1.12 ± 0.07 1.39 ± 0.02 1.57 ± 0.06

12 Months 1.45 ± .07 1.56 ± .13 1.71 ± .03

15 Months 1.97 ± 0.03 1.72 ± 0.06 1.71 ± 0.02

18 Months 2.66 ± 0.03 1.70 ± 0.07 1.71 ± 0.01

21 Months 3.12 ± 0.07 1.69 ± 0.06 1.71 ± 0.00

24 Months 3.13 ± 0.01 1.69 ± 0.07 1.71 ± 0.00


Size 10-17 cmInteraction effect (groups x period): F(14, 483)=1650.9, p< 0.001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Mean s

heet

gro

wth

(%

)

Fig. 4.17. Mean sheet growth of three treatments over the periods in small sized


94

Medium size


cm) trees of O. indicum are summarized in Table 4.17 and also shown graphically in

Fig. 4.18. The mean sheet growth in all three treatments increase with time (month)

and the increase was evident highest in treatment A followed similarly by treatment B

and treatment C.





p<0.001).


significant (p<0.001) increase in sheet growth of treatment A up to 21 month,








treatment B.

95

Table 4.17. Sheet growth (%) of three treatments over the periods in medium sized

(d.b.h. 17-25 cm) trees of O. indicum



3 Months 0.40 ± 0.04 0.51 ± 0.05 0.45 ± 0.00

6 Months 0.81 ± 0.02 0.94 ± 0.06 1.12 ± 0.02

9 Months 1.14 ± 0.02 1.26 ± 0.04 1.50 ± 0.01

12 Months 1.52 ± 0.02 1.58 ± 0.05 1.72 ± 0.01

15 Months 2.05 ± 0.01 1.76 ± 0.02 1.73 ± 0.01

18 Months 2.72 ± 0.06 1.76 ± 0.01 1.73 ± 0.01

21 Months 3.14 ± 0.06 1.77 ± 0.02 1.73 ± 0.03

24 Months 3.16 ± 0.02 1.76 ± 0.00 1.73 ± 0.00


Size 17-25 cmInteraction effect (groups x period): F(14, 420)=3737.4, p>0.0001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Me

an s

heet

gro

wth

(%

)

Fig. 4.18. Mean sheet growth of three treatments over the periods in medium sized


96

Large size


trees of O. indicum are summarized in Table 4.18 and has also been represented as

graph in Fig. 4.19. All three treatments increase with time (month) and the increase

was evident highest in treatment A followed similarly by treatment B and treatment C.





p<0.001).






revealed significantly (p<0.001) different and higher sheet growth in treatment B at 3

month as compared to treatment A. However, in rest of the periods it not differed

between the two groups and treatment C from 6 to 12 month while significantly

(p<0.001) lower from 15 to 24 month as compared to treatment A. Further, the mean

sheet growth of treatment C was also found significantly (p<0.001) higher from 6 to

12 month as compared to treatment B.

97

Table 4.18. Sheet growth (%) of three treatments over the periods in large sized

(d.b.h. >25 cm) trees of O. indicum



3 Months 0.43 ± 0.01 0.48 ± 0.02 0.47 ± 0.01

6 Months 0.82 ± 0.02 0.85 ± 0.02 1.16 ± 0.03

9 Months 1.11± 0.02 1.13 ± 0.03 1.54 ± 0.03

12 Months 1.51 ± 0.03 1.46± 0.00 1.73 ± 0.01

15 Months 2.05 ± 0.06 1.72 ± 0.04 1.73 ± 0.02

18 Months 2.73 ± 0.05 1.72 ± 0.02 1.73 ± 0.02

21 Months 3.16 ± 0.02 1.78 ± 0.02 1.73 ± 0.02

24 Months 3.16 ± 0.03 1.79 ± 0.03 1.73 ± 0.02


Size >25 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Me

an

sh

ee

t gro

wth

(%

)

Fig. 4.19. Mean sheet growth of three treatments over the periods in large sized (d.b.h.

>25 cm) trees of O. indicum.

98

Total size

The effect of treatments and periods on sheet growth of total trees of O. indicum,

irrespective of tree size is summarized in Table 4.19 and also shown graphically in

Fig. 4.20. It was found that the mean sheet growth in all three treatments increase with

time (month) and the increase was found highest in treatment A followed similarly by

treatment B and treatment C.





p<0.001).










treatment B while rest of the periods it did not differed significantly (p>0.05) between

the two groups.

4.2.3. Agony shoots

Trees were not able to produce agony shoot by the end of observation period. It could

be stated that the species is deficient in producing vegetative shoots in response to

wounding.

99

Table 4.19. Total sheet growth (%) of three treatments over the periods in O. indicum.



3 Months 0.45 ± 0.05 0.48 ± 0.04 0.46 ± 0.06

6 Months 0.79 ± 0.04 0.96 ± 0.09 1.12 ± 0.06

9 Months 1.12 ± 0.05 1.27 ± 0.11 1.54 ± 0.05

12 Months 1.49 ± 0.06 1.54 ± 0.10 1.72 ± 0.02

15 Months 2.02 ± 0.05 1.73 ± 0.05 1.72 ± 0.02

18 Months 2.70 ± 0.06 1.73 ± 0.05 1.73 ± 0.02

21 Months 3.14 ± 0.06 1.73 ± 0.05 1.72 ± 0.02

24 Months 3.15 ± 0.03 1.73 ± 0.05 1.72 ± 0.02


Total sheet growthInteraction effect (groups x period):F(14, 1302)=4177, p>0.0001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Me

an

sh

ee

t g

row

th (

%)

Fig. 4.20. Total mean sheet growth of three treatments over the periods in O. indicum.

100




large) of all O. indicum over the periods. To see the change or rate of change in both

edge augmentation and sheet growth between the treatments, the overall mean (small

+ medium + large) of both edge augmentation and sheet growth were regressed

against the time (month) and summarized in Table 4.20 and also shown graphically in

Fig. 4.21. The edge augmentation and sheet growth both showed significant

(p<0.001) and positive (direct) correlation with time in all the three treatments with

highest being in treatment A (edge augmentation: r=1.00; sheet growth: r=0.99)

followed by treatment B (edge augmentation: r=0.98; sheet growth: r=0.91) and

treatment C (edge augmentation: r=0.95; sheet growth: r=0.85).

Further, regression analysis (Table 4.21) showed that the mean edge augmentation in

treatment A, treatment B and treatment C increase (or rate of change: regression b

coefficient) by 3.17%/month, 4.10%/month and 4.08%/month, respectively and the

coefficient of determination (R2) of these were 99.0%, 95.0% and 96.0%;

respectively. Moreover, the rate of change (or increase) in mean edge augmentation

over the periods was significantly (p<0.001) different and 1.3 fold higher in both

treatment B and treatment C as compared to treatment A while it did not differed

(p>0.05) between treatment B and treatment C.

Conversely, the mean sheet growth in treatment A, treatment B and treatment C

increase (or rate of change: regression b coefficient) by 0.14%/month, 0.07%/month

and 0.07%/month, respectively and the coefficient of determination (R2) of these were

98.0%, 82.0% and 72.0%; respectively. Moreover, the rate of change (or increase) in

mean sheet growth over the periods lowered significantly (p<0.001) by 0.5 fold in

both treatment B and treatment C as compared to treatment A while it did not differed

(p>0.05) between treatment B and treatment C.

101


growth with time in O. indicum

Total

growth


Edge

A 1.00***

0.99 3.17 3.17x + 2.71

B 0.98***

0.95 4.10 4.10x + 11.76

C 0.95***

0.96 4.08 4.08x + 17.87

Sheet

A 0.99***

0.98 0.14 0.14x - 0.04

B 0.91***

0.82 0.07 0.07x + 0.40

C 0.85***

0.72 0.07 0.07x + 0.50

Table 4. 21. Comparison of rate of change (regression slope: b) of total edge augmentation and

sheet growth between the treatments by t test in O. indicum.



11.39***


9.30***

Treatment B vs. TreatmentC 0.07ns

0.00ns

ns- p>0.05, **- p<0.01, ***- p<0.001

102


0 3 6 9 12 15 18 21 24

0

10

20

30

40

50

60

70

80

90

100Treatment A

Treatment B

Treatment C




Periods (month)

Mea

n


0 3 6 9 12 15 18 21 24

0

1

2

3

4

5Treatment A

Treatment B

Treatment C

Treatment A: y= 0.14x - 0.04



Periods (month)

Mea

n

Fig. 4.21. Correlation and simple linear regression analysis of total edge augmentation

and sheet growth with time in O. indicum.

103


A total of 86 trees were selected and evaluated for edge augmentation (%) and sheet

growth (%) for H. pubescens which were further divided into three groups i.e. small

size (d.b.h. 4-8 cm), medium size (d.b.h. 9-12 cm) and 12 large sized (d.b.h. >13 cm).

The effect of treatments and periods on both edge and sheet growth of different size

H. pubescens are summarized below in section A and B, respectively.

4.3.1 Edge augmentation

Small size

The effect of treatments and periods on edge augmentation (%) of small size (d.b.h.

10-17 cm) H. pubescens are summarized in Table 4.22 and also shown graphically in

Fig. 4.22. Result shows that the mean edge augmentation in all three treatments

increase over the periods (month) and the increase was evident highest in treatment B

followed by treatment A and it was minimum in treatment C.




(treatments x periods) on edge augmentation was also found to be significant (F=6.76,

p<0.001).

Further, comparing the mean edge augmentation within the groups (i.e. between

periods), Bonferroni test revealed significant (p<0.001) increase in edge

augmentation over the periods in all three treatments.


test revealed significantly (p<0.01 or p<0.001) different and higher edge

augmentation in treatment B as compared to both treatment A and treatment C from 9

to 24 months. However, the increase in mean edge augmentation not differed

(p>0.05) between treatment A and treatment C at all periods, i.e. found to be

statistically the same.

104

Table 4.22. Edge augmentation (%) of three treatments over the periods in small

sized (d.b.h. 4-8 cm) trees of H. pubescens



3 Months 0.66 ± 0.04 0.67 ± 0.05 0.65 ± 0.06

6 Months 1.06 ± 0.07 1.07 ± 0.06 1.02 ± 0.09

9 Months 1.31 ± 0.06 1.41 ± 0.05 1.28 ± 0.06

12 Months 1.59 ± 0.07 1.75 ± 0.07 1.55 ± 0.06

15 Months 1.83 ± 0.04 1.95 ± 0.06 1.80 ± 0.05

18 Months 2.06 ± 0.06 2.18 ± 0.06 2.03 ± 0.09

21 Months 2.26 ± 0.04 2.42 ± 0.05 2.22 ± 0.07

24 Months 2.39 ± 0.03 2.51 ± 0.06 2.35 ± 0.04


Size 4-8 cm

interaction effect (groups x period): F(14, 294)=6.7588, p<0.001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

Mean e

dge a

ugm

enta

tion


(d.b.h. 4-8 cm) trees of H. pubescens.

105

Medium size

The effect of treatments and periods on edge augmentation of medium sized (d.b.h. 9-

12 cm) trees of H. pubescens are summarized in Table 4.23 and also depicted

graphically in Fig. 4.23. Data showed that the mean edge augmentation in all three


treatment B followed by treatment A and treatment C, the least.



(F=4374.25, p<0.001) on edge augmentation. However, the interaction effect of both

(treatments x periods) on edge augmentation was found insignificant (F=1.73,

p>0.05).


periods), Bonferroni test revealed significant (p<0.01 or p<0.001) increase in edge

augmentation over the periods in all three treatments except from 21 months to 24

months in both treatment A and treatment C.


test revealed significantly (p<0.05 or p<0.01 or p<0.001) different and higher edge

augmentation in treatment B as compared to treatment A from 15 months to 24

months and also as compared to treatment C from 21 months to 24 months. However,

the increase in mean edge augmentation not differed (p>0.05) between treatment A

and treatment C at all periods, i.e. found to be statistically the same.

106


sized (d.b.h. 9-12 cm) trees of H. pubescens



3 Months 0.71 ± 0.05 0.75 ± 0.03 0.72 ± 0.05

6 Months 1.09 ± 0.06 1.14 ± 0.09 1.13 ± 0.06

9 Months 1.45 ± 0.05 1.49 ± 0.14 1.50 ± 0.05

12 Months 1.81 ± 0.06 1.84 ± 0.08 1.81 ± 0.06

15 Months 2.05 ± 0.04 2.15 ± 0.07 2.11 ± 0.05

18 Months 2.29 ± 0.06 2.39 ± 0.07 2.32 ± 0.05

21 Months 2.50 ± 0.05 2.61 ± 0.06 2.52 ± 0.06

24 Months 2.59 ± 0.05 2.73 ± 0.08 2.60 ± 0.05


Size 9-12 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Me

an

ed

ge

au

gm

en

tatio

n



107

Large size

The effect of treatments and periods on edge augmentation of large sized (d.b.h. >13

cm) trees of H. pubescens are summarized in Table 4.24 and also shown graphically

in Fig. 4.24. Table 5.24 and Fig. 5.24 both showed that the mean edge augmentation

in all three treatments increase with time (month) and the increase was evident highest

in treatment B followed by treatment A and treatment C, the least.





p<0.001).



augmentation over the periods in all three treatments except from 21 months to 24

months in treatment B.


test revealed significantly (p<0.01 or p<0.001) different and higher edge

augmentation in treatment B as compared to both treatment A and treatment C from

12 months to 15 months. However, in rest of the periods, the mean edge augmentation

not differed (p>0.05) between three groups i.e. found to be statistically the same.

108


(d.b.h.>13 cm) trees of H. pubescens.



3 Months 0.77 ± 0.04 0.81 ± 0.04 0.79 ± 0.03

6 Months 1.13 ± 0.03 1.17 ± 0.02 1.13 ± 0.03

9 Months 1.54 ± 0.03 1.56 ± 0.04 1.52 ± 0.03

12 Months 1.88 ± 0.04 1.96 ± 0.08 1.84 ± 0.03

15 Months 2.17 ± 0.05 2.27 ± 0.03 2.15 ± 0.03

18 Months 2.44 ± 0.03 2.49 ± 0.06 2.41 ± 0.04

21 Months 2.63 ± 0.06 2.68 ± 0.06 2.63 ± 0.03

24 Months 2.73 ± 0.02 2.70 ± 0.05 2.71 ± 0.06


Size >13 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.5

1.0

1.5

2.0

2.5

3.0

Me

an

ed

ge

au

gm

en

tati

on


(d.b.h. >13 cm) trees of H. pubescens.

109

Total size

The effect of treatments and periods on edge augmentation in total trees (irrespective

of size) of H. pubescens are summarized in Table 4.25 and also shown graphically in

Fig. 4.25. Results obtained from the study illustrates that the mean edge augmentation

in all three treatments increase with time (month) and the increase was evident highest

in treatment B followed by treatment A and treatment C, the least.


revealed significant effect of both treatments (F=7.47, p=0.001) and periods



p<0.001).





test revealed significantly (p<0.05) different and higher edge augmentation in

treatment B as compared to both treatment A and treatment C from 15 months to 21

months. However, in rest of the periods, the mean edge augmentation not differed

(p>0.05) between three groups i.e. found to be statistically the same.

110

Table 4.25. Total edge augmentation (%) of three treatments over the periods in H.

pubescens



3 Months 0.71 ± 0.06 0.74 ± 0.07 0.72 ± 0.07

6 Months 1.09 ± 0.06 1.12 ± 0.08 1.08 ± 0.08

9 Months 1.43 ± 0.11 1.48 ± 0.11 1.41 ± 0.11

12 Months 1.75 ± 0.14 1.84 ± 0.11 1.72 ± 0.15

15 Months 2.00 ± 0.15 2.11 ± .014 1.99 ± 0.16

18 Months 2.25 ± 0.16 2.34 ± 0.15 2.24 ± 0.18

21 Months 2.45 ± 0.16 2.56 ± 0.12 2.44 ± 0.19

24 Months 2.56 ± 0.14 2.64 ± 0.12 2.54 ± 0.16





3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

Me

an

ed

ge

au

gm

en

tatio

n

Fig. 4.25. Total edge augmentation of three treatments over the periods in H. pubescens.

111

4.3.2. Sheet growth

Small size

The effect of treatments and periods on sheet growth (%) of small sized (d.b.h. 4-8

cm) trees of H. pubescens are summarized in Table 4.26 and has been illustrated

graphically in Fig. 4.26. Analysis explained that the mean sheet growth in all three


treatment B followed by treatment A and treatment C, the least.



(F=7642.25, p<0.001) on sheet growth. Further, the interaction effect of both

(treatments x periods) on sheet growth was also found to be significant (F=33.78,

p<0.001).

Further, comparing the mean sheet growth within the groups (i.e. between periods),

Bonferroni test revealed significant (p<0.05 or p<0.001) increase in sheet growth

over the periods in all three treatments except 21 months to 24 months in treatment C.


revealed significantly (p<0.01 or p<0.001) different and higher sheet growth in

treatment B as compared to both treatment A and treatment C at all periods. Further,

the mean sheet growth of treatment A was also found to be significantly (p<0.01 or

p<0.001) different and higher as compared to treatment C from 15 months to 24

months.

112

Table 4.26. Sheet growth (%) of three treatments over the periods in small sized (d.b.h.

4-8 cm) trees of H. pubescens



3 Months 5.22 ± 1.03 8.05 ± 0.98 5.54 ± 1.10

6 Months 11.13 ± 1.70 15.21 ± 1.12 10.96 ± 1.48

9 Months 17.53 ± 0.96 24.81 ± 0.88 17.97 ± 1.08

12 Months 26.21 ± 1.49 37.68 ± 2.37 24.87 ± 1.92

15 Months 38.43 ± 1.23 44.82 ± 1.43 34.91 ± 1.48

18 Months 43.60 ± 1.26 53.38 ± 1.74 40.83 ± 1.26

21 Months 49.68 ± 1.84 56.66 ± 1.72 47.21 ± 1.72

24 Months 51.70 ± 1.77 61.07 ± 1.41 49.04 ± 2.05


Size 4-8 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-10

0

10

20

30

40

50

60

70

Mean s

heet gro

wth

Fig. 4.26. Mean sheet growth of three treatments over the periods in small sized (d.b.h.

4-8 cm) trees of H. pubescens.

113

Medium size


cm) trees of H. pubescens are summarized in Table 4.27 and also shown graphically

in Fig. 4.27. Results of the studt made it clear that the mean sheet growth in all three

treatments increased with time (month) and this increase was evident similar and

higher in both treatment A and treatment B as compared to treatment C.

Comparing the effect of both treatments and periods, ANOVA revealed significant

effect of both treatments (F=720.36, p<0.001) and periods (F=15287.10, p<0.001) on

sheet growth. Further, the interaction effect of both (treatments x periods) on sheet

growth was also found to be significant (F=11.04, p<0.001).


Bonferroni test revealed significant (p<0.001) increase in sheet growth over the



revealed significantly (p<0.01 or p<0.001) different and higher sheet growth in

treatment B as compared to both treatment A and treatment C at all periods except

treatment B and treatment A at 15 months. Further, the mean sheet growth of

treatment A was also found to be significantly (p<0.05 or p<0.01 or p<0.001)

different and higher as compared to treatment C from 9 months to 24 months.

114


(d.b.h. 9-12 cm) trees of H. pubescens



3 Months 11.89 ± 0.80 14.16 ± 0.90 12.08 ± 0.67

6 Months 23.57 ± 1.37 28.01 ± 1.23 21.90 ± 1.97

9 Months 34.84 ± 2.13 39.30 ± 1.85 31.53 ± 2.21

12 Months 57.51 ± 0.61 61.21 ± 0.65 54.41 ± 1.09

15 Months 71.14 ± 1.42 70.61 ± 1.69 66.23 ± 1.62

18 Months 73.99 ± 1.37 77.54 ± 1.00 70.96 ± 1.19

21 Months 77.59 ± 1.18 81.15 ± 1.27 75.69 ± 1.51

24 Months 83.18 ± 1.18 84.21 ± 0.88 78.15 ± 1.09


Size 9-12 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

90

100

Mean s

heet

gro

wth

Fig. 4.27. Mean sheet growth of three treatments over the periods in medium sized


115

Large size


trees of H.pubescens are summarized in Table 4.28 and also shown graphically in Fig.

4.28. Results from the amalysis showed that the mean sheet growths in all three

treatments increase with time (month) and the increase was evident higher and similar

in both treatment A and treatment B as compared to treatment C.





p<0.001).


Bonferroni test revealed significant (p<0.01 or p<0.001) increase in sheet growth

over the periods in all three treatments except 21 months to 24 months in treatment B.


revealed significantly (p<0.001) different sheet growth among the three groups

especially from 15 months to 24 months. However; from 6 months to 9 months, the

increase in mean sheet growth of treatment A was significantly (p<0.001) different

and higher than both treatment B and treatment C.

116

Table 4.28. Sheet growth (%) of three treatments over the periods in large sized (d.b.h.

>13 cm) trees of H. pubescens



3 Months 15.94 ± 0.32 16.05 ± 068 17.21 ± 0.96

6 Months 37.22 ± 1.22 34.11 ± 0.45 33.54 ± 1.13

9 Months 51.43 ± 1.79 48.78 ± 1.28 47.90 ± 1.46

12 Months 64.12 ± 0.90 67.04 ± 0.98 65.78 ± 1.48

15 Months 78.16 ± 2.20 81.44 ± 1.16 74.86 ± 1.13

18 Months 83.67 ± 1.16 87.67 ± 1.16 78.81 ± 1.47

21 Months 87.74 ± 1.53 92.36 ± 1.37 82.66 ± 1.37

24 Months 89.98 ± 1.37 93.65 ± 1.32 87.25 ± 1.34


Size >13 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

90

100

110

Me

an

sh

ee

t g

row

th

Fig. 4.28. Mean sheet growth of three treatments over the periods in large sized (d.b.h.

>25 cm) trees of H. pubescens.

117

Total size

The effect of treatments and periods on sheet growth of total size class in H.

pubescens are summarized in Table 4.29 and also shown graphically in Fig. 4.29.

Results demonstrated that the mean sheet growth in all three treatments increase with

time (month) and the increase was evident highest in treatment B followed by

treatment A and treatment C.


revealed insignificant effect of treatments (F=2.43, p>0.093) while significant effect

of periods (F=2687.10, p<0.001) on sheet growth. Further, the interaction effect of

both (treatments x periods) on sheet growth was also found to be significant (F=3.38,

p<0.001).


Bonferroni test revealed significant (p<0.001) increase in sheet growth over the

periods in all three treatments except 21 months to 24 months.

Nevertheless, comparing the mean sheet growth between the groups, Bonferroni test

revealed insignificant (p<0.001) increase in sheet growth among the three groups i.e.

not differed statistically.

4.3.3. Agony shoots

In the case of H. pubescens, only few trees were able to produce agony shoots.

Though, in this case the vegetative shoots were mostly found near treatment A but the

count was statistically insignificant thus, it could be inferred that the tree is not well

suited for coppice management.

118

Table 4.29. Total sheet growth (%) of three treatments over the periods in all size class

of H. pubescens



3 Months 10.64 ± 4.54 12.48 ± 3.59 11.19 ± 4.89

6 Months 23.01 ± 10.75 25.11 ± 8.06 21.30 ± 9.36

9 Months 33.36 ± 13.98 36.77 ± 10.05 31.36 ± 12.33

12 Months 47.99 ± 16.99 54.31 ± 13.09 46.93 ± 17.63

15 Months 61.23 ± 17.83 64.34 ± 15.70 57.30 ± 17.62

18 Months 65.70 ± 17.48 71.66 ± 14.70 62.23 ± 16.80

21 Months 70.35 ± 16.48 75.47 ± 15.22 67.31 ± 15.78

24 Months 73.65 ± 17.16 78.50 ± 13.99 70.16 ± 16.72


Total sheet growth



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

90

100

Me

an

sh

ee

t g

row

th

Fig. 4.29. Total sheet growth of three treatments over the periods in H. pubescens

irrespective of tree size class.

119




large) of all trees in H. pubescens over the periods. To see the change or rate of

change in both edge augmentation and sheet growth between the treatments, the

overall mean (small + medium + large) of both edge augmentation and sheet growth

were regressed against the time (month) and summarized in Table 4.30 and also

shown graphically in Fig. 4.30.

The correlation analysis revealed a significant and high positive (direct) correlation of

both mean edge augmentation (treatment A: r=0.768, p<0.001; treatment B: r=0.974,

p<0.001; treatment C: r=0.977, p<0.001) and sheet growth with time (treatment A:

r=0.983, p<0.001; treatment B: r=0.980, p<0.001; treatment C: r=0.983, p<0.001).

Further, regression analysis showed that the mean edge augmentation in treatment A,

treatment B and treatment C increase (or rate of change: regression b coefficient) by

0.102%/month, 0.106%/month and 0.101%/month, respectively with coefficient of

determination (R2) 95.3%, 95.0% and 95.4%; respectively. Moreover, the rate of

change (or increase) in mean edge augmentation over the periods was found similar

(p>0.05) among the three groups though it was 1.04 and 1.05 fold higher in treatment

B as compared to both treatment A and treatment C; and 1.01 fold higher in treatment

A as compared to treatment C.

Similarly, the mean sheet growth in treatment A, treatment B and treatment C

increase (or rate of change: regression b coefficient) by 3.261%/month,

3.465%/month and 3.093%/month, respectively with coefficient of determination (R2)

of these were 98.3%, 98.0% and 98.3.0%; respectively. Moreover, the rate of change

(or increase) in mean edge augmentation over the periods was significantly (p<0.01)

different and 1.12 fold higher in treatment B as compared to treatment C, but not

differed with treatment A though it was 1.06 fold higher in treatment B as compared

to treatment A. Further, the rate of change (or increase) in mean edge augmentation

also not differed (p>0.05) between treatment A and treatment C though it was 1.05

fold higher in treatment A as compared to treatment C (Table 4.31).

120

Table 4.30. Correlation and linear regression analysis of total edge augmentation and sheet growth

with time by t test in H. pubescens

Total

growth


Edge

A 0.976***

0.953 0.102 0.102x + 0.359

B 0.974***

0.950 0.106 0.106x + 0.376

C 0.977***

0.954 0.101 0.101x + 0.357

Sheet

A 0.983***

0.965 3.261 3.261x + 3.749

B 0.980***

0.961 3.465 3.465x + 4.938

C 0.983***

0.967 3.093 3.093x + 3.744

Table 4.31. Comparison of rate of change (regression slope: b) of total edge augmentation and

sheet growth between the treatments by t test in H. pubescens.


Treatment A vs. TreatmentB 0.84ns

1.53ns

Treatment A vs. TreatmentC 0.22ns

1.40ns


2.88**

ns- p>0.05, **- p<0.01, ***- p<0.001

121


0 3 6 9 12 15 18 21 24

0

1

2

3

4

5Treatment A

Treatment B

Treatment C




Periods (month)

Mea

n


0 3 6 9 12 15 18 21 24

0

100Treatment A

Treatment B

Treatment C

Treatment A: y= 3.2614x + 3.749



Periods (month)

Mea

n


and sheet growth with time in differently treated H. pubescens.

122


The effect of treatments and periods on edge augmentation (%) and sheet growth (%)

were evaluated in T. arjuna. A total of 197 trees were selected and evaluated. Like the

other cases, it was also devided into three class sizes i.e. small size (d.b.h. 4-8 cm),

medium size (d.b.h. 9-12 cm) and large size (d.b.h. >13 cm). The effect of treatments

and periods on both edge and sheet growth of different size T. arjuna are summarized

below in section A and B, respectively.


Small size

The effect of treatments and periods on edge augmentation (%) of small sized (d.b.h.

10-24 cm) trees of T. arjuna are summarized in Table 4.32 and has also been

presented graphically in Fig. 4.31. Analysis reveals that the mean edge augmentation

(growth) in all three treatments increase with time (month) and the increase was

evident highest in treatment C followed by treatment B and treatment A, the least.




(treatments x periods) on edge augmentation was also found to be significant

(F=12.98, p<0.001).



augmentation over the periods in all three treatments except 21 months to 24 months

in both treatment B and treatment C.




mean edge augmentation of treatment C was also found to be significantly (p<0.01 or

p<0.001) different and higher as compared to treatment B from 9 months to 24

months.

123

Table 4.32. Edge augmentation (%) of three treatments over the periods in small sized

(d.b.h. 10-24 cm) trees of T. arjuna



3 Months 0.16 ± 0.05 0.55 ± 0.10 0.67 ± 0.11

6 Months 0.29 ± 0.09 0.84 ± 0.05 0.97 ± 0.05

9 Months 0.58 ± 0.10 1.14 ± 0.07 1.34 ± 0.07

12 Months 1.01 ± 0.09 1.56 ± 0.07 1.77 ± 0.07

15 Months 1.15 ± 0.16 1.74 ± 0.11 1.98 ± 0.11

18 Months 1.33 ± 0.15 1.86 ± 0.12 2.23 ± 0.12

21 Months 1.48 ± 0.16 2.17 ± 0.13 2.42 ± 0.11

24 Months 1.63 ± 0.14 2.27 ± 0.14 2.47 ± 0.12


Size 10-24 cm

Interaction effect (groups x period): F(14, 273)=12.985, p<0.001


3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Mean e

dge a

ugm

enta

tion


(d.b.h. 10-24 cm) trees of T. arjuna.

124

Medium size

The effect of treatments and periods on edge augmentation of medium sized (d.b.h.

25-38 cm) trees of T. arjuna are summarized in Table 4.33 and also demonstrated

graphically in Fig. 4.32. Results show that the mean edge augmentation in all three


treatment C followed by treatment B and treatment A, the least.





p<0.001).



augmentation in all three treatments at all periods.



treatment C as compared to both treatment A and treatment B at all periods. However,

the increase in mean edge augmentation did not differed significantly (p>0.05) among

treatment A and treatment B at all periods i.e. found to be statistically the same.

125


sized (d.b.h. 25-38 cm) trees of T. arjuna



3 Months 0.12 ± 0.04 0.20 ± 0.09 0.42 ± 0.11

6 Months 0.23 ± 0.08 0.35 ± 0.09 0.64 ± 0.06

9 Months 0.53 ± 0.10 0.63 ± 0.09 0.97 ± 0.08

12 Months 0.95 ± 0.09 1.07 ± 0.08 1.34 ± 0.07

15 Months 1.09 ± 0.15 1.20 ± 0.15 1.55 ± 0.13

18 Months 1.27 ± 0.15 1.38 ± 0.13 1.72 ± 0.13

21 Months 1.43 ± 0.18 1.53 ± 0.14 1.91 ± 0.12

24 Months 1.57 ± 0.13 1.69 ± 0.13 1.99 ± 0.13


Size 25-38 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

Me

an e

dge a

ugm

enta

tio

n



126

Large size

The effect of treatments and periods on edge augmentation of large sized (d.b.h. >39

cm) trees of T. arjuna are summarized in Table 4.34 and also shown graphically in

Fig. 4.33. It was observed that the mean edge augmentation in all three treatments

increase with time (month) and the increase was evident highest in treatment B

followed by treatment C and treatment A.





(F=28.20, p<0.001).



augmentation in all three treatments at all periods.



treatment B as compared to both treatment A and treatment C at all periods. Further,

the mean edge augmentation of treatment C was also found to be significantly

(p<0.01) different and higher as compared to treatment A from 15 months to 24

months.

127


(d.b.h. >39 cm) trees of T. arjuna.



3 Months 0.19 ± 0.11 0.78 ± 0.05 0.26 ± 0.12

6 Months 0.32 ± 0.05 1.14 ± 0.03 0.36 ± 0.10

9 Months 0.61 ± 0.07 1.53 ± 0.03 0.69 ± 0.08

12 Months 1.01 ± 0.07 1.91 ± 0.08 1.12 ± 0.09

15 Months 1.09 ± 0.11 2.18 ± 0.06 1.29 ± 0.14

18 Months 1.27 ± 0.12 2.44 ± 0.03 1.48 ± 0.11

21 Months 1.42 ± 0.11 2.63 ± 0.05 1.62 ± 0.12

24 Months 1.58 ± 0.12 2.73 ± 0.02 1.78 ± 0.13


Size >39 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Me

an

ed

ge

au

gm

en

tatio

n


(d.b.h. >39 cm) trees of T. arjuna.

128

Total size

The effect of treatments and periods on edge augmentation in total trees (irrespective

of size) of T. arjuna are summarized in Table 4.35 and also shown graphically in Fig.

4.34. Results revealed that the mean edge augmentation in all three treatments

increase with time (month) and the increase was apparent to be highest in treatment B

followed by treatment C and lastly in treatment A.





(F=13.77, p<0.001).






treatment B and treatment C as compared treatment A at all periods. However, the

increase in mean edge augmentation not differed significantly (p>0.05) between

treatment B and treatment C at all periods i.e. found to be statistically the same.

129

Table 4.35. Total edge augmentation (%) of three treatments over the periods in T.

arjuna.



3 Months 0.15 ± 0.05 0.50 ± 0.26 0.45 ± 0.20

6 Months 0.28 ± 0.09 0.76 ± 0.34 0.65 ± 0.26

9 Months 0.57 ± 0.11 1.09 ± 0.38 1.00 ± 0.28

12 Months 0.99 ± 0.10 1.50 ± 0.36 1.41 ± 0.28

15 Months 1.11 ± 0.17 1.70 ± 0.42 1.60 ± 0.31

18 Months 1.29 ± 0.16 1.88 ± 0.45 1.80 ± 0.33

21 Months 1.44 ± 0.17 2.10 ± 0.47 1.98 ± 0.35

24 Months 1.59 ± 0.15 2.21 ± 0.45 2.08 ± 0.32





3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Mea

n e

dg

e a

ug

men

tation

Fig. 4.34. Total edge augmentation of three treatments over the periods in T. arjuna.

130

4.4.2. Sheet growth

Small size

The effect of treatments and periods on sheet growth (%) of small sized (d.b.h. 10-24

cm) trees of T. arjuna are summarized in Table 4.36 and also shown graphically in

Fig. 4.35. Results reveal that the mean sheet growth in all the three treatments

increases with time (month) and the increase was evident highest in treatment C






p<0.001).


Bonferroni test revealed significant (p<0.05 or p<0.01 or p<0.001) increase in sheet

growth in all three treatments over the periods except from 18 months to 24 months.



and treatment C as compared treatment A at all periods. However, the increase in

mean sheet growth not differed significantly (p>0.05) between treatment B and

treatment C at all periods except from 12 months to 16 months at which it was

significantly (p<0.05 or p<0.01) different and higher in treatment C as compared to

treatment B.

131

Table 4.36. Sheet growth (%) of three treatments over the periods in small sized (d.b.h.

10-24 cm) trees of T. arjuna.



3 Months 9.81 ± 1.27 19.35 ± 1.66 22.50 ± 1.59

6 Months 17.78 ± 2.81 33.32 ± 3.13 36.07 ± 2.08

9 Months 24.20 ± 3.13 41.86 ± 3.32 44.71 ± 2.10

12 Months 31.22 ± 3.29 53.58 ± 3.41 57.72 ± 2.23

15 Months 39.80 ± 3.49 57.53 ± 2.49 62.41 ± 2.22

18 Months 46.06 ± 3.21 61.57 ± 2.26 65.68 ± 2.50

21 Months 47.92 ± 3.38 63.16 ± 2.31 66.84 ± 2.66

24 Months 48.71 ± 3.43 64.65 ± 2.35 67.74 ± 3.10


Size 10-24 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

Me

an

sh

ee

t g

row

th

Fig. 4.35. Mean sheet growth of three treatments over the periods in small sized (d.b.h.:


132

Medium size


cm) trees of T. arjuna are summarized in Table 4.37 and Fig. 4.36. Analysis results

showed that the mean sheet growth in all three treatments increase with time (month)

and the increase was evident highest in treatment C followed by treatment B and

treatment A, the least.





p<0.001).



growth in all three treatments over the periods except from 18 months to 24 months in

treatment C and 21 months to 24 months in both treatment A and treatment B.



and treatment C as compared treatment A from 6 months to 24 months. Further, the

increase in mean sheet growth of treatment C was also differed and higher

significantly (p<0.001) as compared to treatment B from 12 months to 24 months.

133





3 Months 14.04 ± 1.21 17.64 ± 2.12 18.99 ± 2.31

6 Months 18.65 ± 2.86 30.28 ± 2.08 32.96 ± 2.90

9 Months 25.22 ± 3.16 37.75 ± 3.08 44.13 ± 2.78

12 Months 33.61 ± 3.29 47.68 ± 3.58 55.17 ± 2.86

15 Months 45.32 ± 3.45 50.94 ± 3.58 61.50 ± 2.84

18 Months 49.07 ± 3.36 55.62 ± 3.02 65.75 ± 2.59

21 Months 51.77 ± 2.29 58.56 ± 3.01 66.29 ± 3.02

24 Months 53.88 ± 2.29 61.00 ± 3.28 66.62 ± 2.59


Size 25-38 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

Me

an

sh

ee

t g

row

th

Fig. 4.36. Mean sheet growth of three treatments over the periods in medium sized (d.b.h.


134

Large size

The effect of treatments and periods on sheet growth of large size (d.b.h. >39 cm) T.

arjuna are summarized in Table 4.38 and also represented graphically in Fig. 4.37. It

was observed that the mean sheet growth in all three treatments increases with time

(month) and the increase was found to be higher and similar in both treatment B and

treatment C as compared to treatment A.





p<0.001).



growth in all three treatments over the periods; except from 21 months to 24 months

in both treatment B and treatment C, and from 15 months to 24 months in treatment

A.



and treatment C as compared treatment A at all periods. However, the increase in

mean sheet growth not differed (p>0.05) between treatment B and treatment C at all

periods i.e. found to be statistically the same.

135

Table 4.38. Sheet growth (%) of three treatments over the periods in large size (d.b.h.

>39 cm) T. arjuna.



3 Months 6.43 ± 1.23 19.41 ± 1.73 20.83 ± 1.54

6 Months 13.29 ± 1.43 31.99 ± 2.83 35.09 ± 1.69

9 Months 20.23 ± 1.56 38.84 ± 3.25 42.93 ± 2.55

12 Months 27.06 ± 1.24 50.39 ± 3.52 51.69 ± 2.87

15 Months 33.50 ± 1.24 54.52 ± 2.50 58.62 ± 2.41

18 Months 35.80 ± 1.25 58.90 ± 3.05 61.73 ± 2.28

21 Months 37.32 ± 1.31 61.60 ± 2.68 64.90 ± 2.44

24 Months 38.08 ± 1.43 61.79 ± 2.58 64.84 ± 3.10


Size >39 cm



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

-10

0

10

20

30

40

50

60

70

80

Mea

n s

hee

t g

row

th

Fig. 4.37. Mean sheet growth of three treatments over the periods in large size (d.b.h.

>39 cm) T. arjuna.

136

Total size

The effect of treatments and periods on sheet growth of total size class in T. arjuna

are summarized in Table 4.39 and Fig. 4.38. Analysis showed that the mean sheet

growth in all three treatments increase with time (month) and the increase was evident

highest in treatment C followed by treatment B and treatment A.





p<0.001).


Bonferroni test revealed significant (p<0.001) increase in sheet growth in all three

treatments over the periods except from 21 months to 24 months.



and treatment C as compared treatment A at all periods. Further, the increase in mean

sheet growth of treatment C was also found significantly (p<0.01 or p<0.001)

different and higher as compared to treatment B from 9 months to 24 months.

4.4.3. Agony shoots

No agony shoots were noted near the harvested area of bark. However, few were

noticed in upper part of the bole but were distant from the treatments. Another very

interesting observation was made in the species that mucilaginous substance covers

the wound area after debarking, but, we did not investigate the phenomenon further.

137

Table 4.39. Total sheet growth (%) of three treatments over the periods in T. arjuna

irrespective of size class.



3 Months 10.18 ± 3.39 18.78 ± 1.99 20.73 ± 2.33

6 Months 16.62 ± 3.38 31.82 ± 2.92 34.67 ± 2.60

9 Months 23.26 ± 3.44 39.44 ± 3.60 43.93 ± 2.55

12 Months 30.70 ± 3.87 50.48 ± 4.21 54.86 ± 3.60

15 Months 39.68 ± 5.69 54.25 ± 3.96 60.86 ± 2.94

18 Months 43.77 ± 6.35 58.62 ± 3.69 64.42 ± 3.06

21 Months 45.81 ± 6.63 61.05 ± 3.27 66.02 ± 2.78

24 Months 47.05 ± 7.10 62.45 ± 3.14 66.41 ± 3.10


Total sheet growth



3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M

Period (months)

0

10

20

30

40

50

60

70

80

Me

an

she

et

gro

wth

Fig.4.38. Total mean sheet growth of three treatments over the periods in T. arjuna

irrespective of size class.

138




large) of all trees in T. arjuna over the periods. To see the change or rate of change

in both edge augmentation and sheet growth between the treatments, the overall mean

(small + medium + large) of both edge augmentation and sheet growth were regressed

against the time (month) and summarized in Table 4.40 and has also been

demonstrated graphically in Fig. 4.39.

The correlation analysis revealed a significant and high positive (direct) correlation of

both mean edge augmentation (treatment A: r=0.990, p<0.001; treatment B: r=0.985,

p<0.001; treatment C: r=0.986, p<0.001) and sheet growth with time (treatment A:

r=0.980, p<0.001; treatment B: r=0.945, p<0.001; treatment C: r=0.936, p<0.001).

Further, regression analysis revealed that the mean edge augmentation in treatment A,

treatment B and treatment C increase (or rate of change: regression b coefficient) by

0.071%/month, 0.092%/month and 0.088%/month, respectively with highest being in

treatment B followed by treatment C and treatment A and with coefficient of

determination (R2) 97.9%, 97.1% and 97.2%; respectively. Further, the rate of

increase in mean edge augmentation over the periods of both treatment B and

treatment C was found significantly (p>0.001) different and 1.30 and 1.24 fold higher

respectively as compared to treatment A. However, the rate of increase in mean edge

augmentation not differed between treatment B and treatment C though it was 1.05

fold higher in treatment B as compared to treatment C (Table 4.41).

Similarly, the mean sheet growth in treatment A, treatment B and treatment C

increase (or rate of change: regression b coefficient) by 2.032%/month,

2.472%/month and 2.655%/month, respectively with highest being in treatment C

followed by treatment B and treatment A and with coefficient of determination (R2)

96.0%, 89.4% and 87.7%; respectively. Further, the rate of increase in mean sheet

growth over the periods of both treatment C and treatment B was found significantly

(p>0.001) different and 1.31 and 1.22 fold higher respectively as compared to

treatment A. However, the rate of increase in mean sheet growth not differed between

treatment B and treatment C though it was 1.07 fold higher in treatment C as

compared to treatment B (Table 4.41).

139


growth with time in T arjuna.

Total

growth


Edge

A 0.990***

0.979 0.071 0.071x + 0.028

B 0.985***

0.971 0.092 0.092x + 0.206

C 0.986***

0.972 0.088 0.088x + 0.164

Sheet

A 0.980***

0.960 2.032 2.032x + 4.178

B 0.945***

0.894 2.472 2.472x + 12.210

C 0.936***

0.877 2.655 2.655x + 13.904

Table 4.41. Comparison of rate of change (regression slope: b) of total edge augmentation and

sheet growth between the treatments by t test in T arjuna.



3.25***


4.04***


0.98ns

ns- p>0.05, **- p<0.01, ***- p<0.001

140


0 3 6 9 12 15 18 21 24

0

1

2

3Treatment A

Treatment B

Treatment C




Periods (month)

Mea

n


0 3 6 9 12 15 18 21 24

0

10

20

30

40

50

60

70

80

90

100Treatment A

Treatment B

Treatment C

Treatment A: y= 2.0324x + 4.178

Treatment B: y= 2.472x + 12.210

Treatment C: y= 2.655x + 13.904

Periods (month)

Mea

n


and sheet growth with time in differently treated T. arjuna.

141

5. Discussion

The tree bark provides protection against external attacks and desiccation and plays a

key role in the transportation of nutrients. Removal of bark thus negatively affects the

species either directly or indirectly. Therefore, it is imperative to study the effects of

bark harvesting on any species before developing any harvest prescriptions.

The results of this study established the theory that tree response to bark harvesting is

species-specific. Though, partial harvest with moisture treatment supported the

regeneration rate but over a period of 2 years after bark harvesting, complete bark re-

growth was rarely attained, in any case except for some of O. indicum trees.

It was a clear observation that the harvesting technique based on total bark removal

which is also a general practice, did not promote bark regeneration by any means i.e.

either edge augmentation or sheet growth.

The results of this study strengthens the theory that response to harvesting depends

upon various ecological factors (Ticktin 2004), parts harvested, tree girth intensity of

debarking and species to species (Cunningham 2001; Delvaux et al., 2009, 2010;

Ticktin et al., 2002). Our experimental harvesting demonstrated very significant

variation between three types of harvest techniques. The bark regeneration was found

to be treatment as well as size dependent but overall, it was observed that the

commercial harvest method of total bark removal i.e. Treatment A, posed most

detrimental effects on tree. The cambial layer was removed in the first treatment

making it deprived of the fundamental requisite of wound closure. Lenticels, which

are present near the cambial region, determine bark regrowth (Romberger et al.,

1993). Due to paucity of this tissue, the treatment lacked sufficient wound closure

whereas partial harvesting supported the phenomenon of recovery due to the

availability of cambial layer on surface which develops phellogen, induces callus

formation after wounding (Fahn 1985) and act as a protective layer. This result is in

accordance with previous observations of tremendous regeneration rate in partially

removed bark in comparison to total bark removal (Delvaux et al. 2009, 2010;

Cunningham 2001; Vermeulen 2006, 2009).

Preeminent bark regrowth was achieved from the third treatment where the wound

surface was covered instantaneously to maintain humidity. Several earlier reports

142

showed that higher regrowth could be achieved by covering the wound immediately

after bark harvest (Neely 1988; McDougall and Blanchette, 1996; Stobbe et al. 2002).

Chungu et al. (2007) and Kirejtshuk (1990) added to these findings by reporting the

benefits of covering the wound site with mud which considerably supported in bark

recovery and protected the trees from wood discoloration as well as insect damage by

reducing the dissemination of plant volatiles which eventually provides protection

from infestations of insects. Though we did not examine this phenomenon in details,

but overall, it could be inferred that covering the wounds may assist in accelerating

the phenomenon of wound closure. Noel (1968), also stressed that maintaining moist,

dark conditions over wounds would promote the differentiation of replacement bark.

The faster recovery in the experimental wounds supported the previous studies in all

inclusive manners.

Size of the tree also had a significant influence on the bark recovery rate but this

factor again, varies from species to species. It was interesting to note that, in three out

of four cases i.e. B. variegata, O. indicum and H. pubescens, the trees with higher

d.b.h. exhibited expeditious recovery in terms of edge augmentation. However, size of

the tree has least correlation with recovery through sheet growth or edge

augmentation because two species (B. variegata and O. indicum) recovered the

wound mostly by edge augmentation while on the other hand H. pubescens recovered

through sheet growth. Wound closure from edge growth has previously been reported

from many species (Chudnoff 1971; Oven and Torelli, 1999; Vermeulen 2006).

Large trees recovered efficiently in comparison to younger trees which were more

affected by debarking due to steady recovery rate. This may be due to the presence of

higher metabolite content and recovery hormones in older trees that helped in

inducing the process of compartmentalization (Shigo 1993) which ultimately fostered

the process of wound healing. However, in contrast with this finding, it was also

observed that no such difference was found in case of T. arjuna. Earlier studies have

also revealed that the size class of trees showing the best bark recovery was different

for each species (Delvaux et al., 2010; Gaoue and Ticktin, 2007, Vermeulen 2006).

Coppicing has traditionally been used as a silvicultural management system and has

been viewed as a specialist activity mainly conducted for nature conservation benefits

(Broome et al., 2011; Mitchell 1992). The ability of a species to develop agony shoots

is specifically associated with the ability of the species to produce copious shoots

143

(Geldenhuys et al., 2007). But not every species generate vegetative regrowth in terms

of agony shoots and the studied species were not found active in producing the same.

Thus this technique has insignificant relevance in context to the management of these

particular trees. Overall it could be inferred that the observations on different

ecological responses of debarked tree could assist in the development of a proper

harvesting strategy in woodlands.

These findings conform to the results of other studies of different tree species in

southern Africa (Delvaux 2009). A number of experiments demonstrated that one of

the most vital factors for successful recovery is the humidity of the exposed surface

instantaneously after the cut was made (Neely 1988; McDougall and Blanchette,

1996; Stobbe et al., 2002). Our results supported these findings and it was observed

that the highest recovery was found in treatment C (Partial harvest with moisture

treatment) in almost all the studied tree species. However, for a wide practical

approach, applying this technique could be a difficult task therefore; partial harvesting

(treatment B) in which the cambial layer was left intact with the tree could also be

used. These two methods were found to be many folds superior to the total bark

removal technique (treatment A).

Following the methodology of Vermeulen (2006), our results offer the fundamentals

essential to characterize a stratagem that can facilitate forest managers to opt for the

most apposite bark-harvesting scheme for different medicinal tree species. Managers

need to take objective decisions on the most appropriate harvest options for a

particular species to ensure that bark harvesting is sustainable and to optimize socio-

economic benefits from the resources used.

CHAPTER 5

Assessing the Effect of Storage on Bio-Deterioration

of Secondary Metabolites in Crude Herbal Drugs

144

ASSESSING THE EFFECT OF STORAGE ON BIO-DETERIORATION OF

SECONDARY METABOLITES IN CRUDE HERBAL DRUGS

1. Introduction

Herbal medicines are commonly used by different communities of the world. In

developing countries, these are extensively used for primary health care. During the

last decade, these medicines have shown resurgence even in the developed countries

because of their time tested efficacy, safety and lesser side effects. Currently, herbal

medicines are very high in demand throughout the world and have excellent export

value. However, it has been observed that several of the herbal drugs lack standard

quality control profile including their shelf life. This acts as a barrier for their wider

application.

Biological activities of herbal drugs are attributed to their active constituents that are

stored in different plant parts. These active constituents and their storage organs are

species specific. Concentrations of these constituents may vary in the plant during

different times of the day, month and growth stages. Based on these observations,

harvesting of the drug part of the plant is undertaken at appropriate time. Bioactive

nature of many secondary metabolites suggests that these could be highly labile.

Previous work has shown that the yields of secondary metabolites can be changed by

biochemical activity (de Scisciolo et al. 1990, Goodrich et al. 1990, Kleiner 1991),

heat (Cork and Krockenberger, 1991, Newman et al., 1992), light (Cork and

Krockenberger, 1991), vacuum (Hay et al., 1988), extraction solvent (Hagerman

1988, Carlson et al., 1989, Muzika et al., 1990, Manika et al., 2013b), drying

procedure (Lindroth et al., 1987, Hagerman 1988, Cork and Krockenberger, 1991),

and duration of extraction (Lindroth and Pajutee, 1987).

These active constituents tend to break down or may transform into different

compounds, after the drug parts are harvested, which may or may not possess the

desired medicinal value. Changes are dependent upon their chemical nature and the

part of the plant where they are stored. Since, most of the herbal drugs are not used

fresh; they require some specific post harvest processing and storage before being

utilized for the manufacture of diverse pharmaceutical preparations. Special cares are

required for the harvested materials to preserve their active constituents and

145

therapeutic properties. Several factors are involved to obtain high quality of starting

herbal materials for the preparation pharmaceutical end products. Quality of herbal

drugs improves with Good Agricultural Practices (GAP). This includes proper seed

selection, growth conditions, use of fertilizers, harvesting, drying and storage. Even if

the proper agricultural practices have been undertaken and the harvested materials are

of high quality based on active constituents, the post harvest methodologies

undertaken were also equally vital. Unscientific methodology hampers the final

quality of the starting materials for the manufacture of drug.

The irrational methods of harvesting, collection, storage of raw materials, processing

and poor storage of herbal drugs in unhygienic conditions, are the main causes of

deterioration in the raw materials which are usually prone to microbial and insect

attack. This deteriorates the medicinal potency of the herbal drugs further. Besides,

secondary metabolites produced by these microbes particularly the fungus often

causes toxicity in humans. Therefore, studies on the deterioration of herbal drugs

especially during storage leading to the loss of active constituents and production of

inactive/ toxic constituents are important to develop an appropriate methodology to

protect the efficacy of our herbal drugs and to know their shelf life.

Because many factors can affect the measurement of ecologically important

secondary metabolites, and most of the work has been done on the extraction efficacy,

solvent biochemical alterations, here we tested how several commonly used storage

methods alters the stability of these components. Our endeavour focuses on how does

duration and method of storage affects the compound stability and quantity within

drug.


2.1. Plant material

Stem bark of Bauhinia variegata, Oroxylum indicum, Holarrhena pubescens and

Terminalia arjuna were collected from the respective population in 2010, dried in

oven at 25oC and were pooled accordingly, after complete drying was achieved.

Samples (20gms each) were then packed in different storage mediums (Glass-GL,

polypropylene-PP and polystyrene-PS) and were kept at three temperature conditions

(4ºC, 15ºC, and 30ºC) in triplicates. Samples were subjected to HPLC analysis in

146

every third month for the quantification of their respective bioactive constituents i.e.

apigenin and luteolin for B. variegata, chrysin and baicalein for O. indicum, conessine

for H. pubescens and arjunic acid for T. arjuna. At the commencement of the

experiment, the content of these biomarkers were analysed and treated as control (0

Month).

2. 2. Preparation of standard solution

Stock solutions of apigenin, luteolin, chrysin, baicalein, conessine and arjunic acid (1

mg/ml) was prepared in methanol as a standard reference.

2.3. Chromatographic analysis (HPLC)

High performance liquid chromatography (HPLC) was used to quantify the

biologically active compounds of respective tree species according to the method

described in chapter 3.

2.4. Statistical analysis

Data in triplicates were summarized as Mean ± SD. Groups were compared by three

factor (temperature x medium x periods) analysis of variance (ANOVA) and the

significance of mean difference within and between the groups was done by

Bonferroni test for multiple contrasts after ascertaining the normality by Shapiro-Wilk

test and homogeneity of variances by Levene‟s test. Correlation and regression

analysis was done to see the rate of change in metabolite concentrations over the

periods. A two-sided (α=2) p value less than 0.05 (p<0.05) was considered

statistically significant. All the analysis was performed on STATISTICA (StatSoft,

Inc., USA, version 7.1) software.

3. Results

The present study determines the effect of three different temperatures (40C, 15

0C and

300C) and medium (Glass, PS and PP) on deterioration in the content of six

metabolite (apigenin, luteolin chrysin, baicalein, conessine and arjunic acid) over 24

months in per three months periods (i.e. 0, 3, 6, 9, 12, 15, 18, 21 and 24 month). The

comparative evaluation of six metabolites from four tree species is summarized below

in section 1 to 4, respectively.

147

3. 1. Bauhinia variegata

3.1.1. Apigenin

The effect of temperature, medium and time (periods) on apigenin yield are

summarized in Table 5.1 and also shown graphically in Fig. 5.1. Results revealed that

the mean apigenin yield (%) decreases with increasing temperature and time and the

decrease were highest in PS followed by Glass and PP containers. Evaluating the

effect of temperature, medium and time all together on mean yield of apigenin,

ANOVA revealed significant effect of time (F=106886.03, p<0.001), medium

(F=7314.69, p<0.001) and temperature (F=52831.13, p<0.001) on apigenin yield.

Further, the interaction effect of time and medium (F=462.19, p<0.001), time and

temperature (F=4652.11, p<0.001), medium and temperature (F=1038.98, p<0.001),

and time, medium and temperature (F=104.87, p<0.001) was also found significant on

apigenin yield.Furthermore, at lower temperature (40C), Bonferroni test revealed

significantly (p<0.001) different and higher mean apigenin yield in Glass medium at

all durations (3-24 months) as compared to both PP and especially PS (Fig. 5.2). In

contrast, at medium temperature (150C), the mean apigenin yield in Glass and PP

mediums were similar (p>0.05) at all the periods but were higher significantly

(p<0.001) as compared to PS (Fig. 5.2). Conversely, at higher temperature (300C) and

durations (6-24 month), the mean Apigenin yield in PP was significantly (p<0.001)

different and higher as compared to both Glass and PS (Fig. 5.2). However, at this

temperature PP performed better than the glass medium.

148

Table 5.1. Effect of different temperature and mediums on apigenin content over the period of 24 months.

Temperature

(0C)

Medium

Time period

0 month 3 month 6 month 9 month 12 month 15 month 18 month 21 month 24 months

Apigenin content (%)

40C GL 0.0585 ±

0.002

0.0582 ±

0.0001

0.0576 ±

0.0001

0.0568 ±

0.0001

0.0552 ±

0.0002

0.0532 ±

0.0001

0.0507 ±

0.0002

0.0476 ±

0.0002

0.0435 ±

0.0001

PS 0.0585 ±

0.002

0.0576 ±

0.0001

0.0564 ±

0.0001

0.0549 ±

0.0001

0.0523 ±

0.0002

0.0495 ±

0.0001

0.0459 ±

0.0003

0.0414 ±

0.0002

0.0362 ±

0.0002

PP 0.0585 ±

0.002

0.0581 ±

0.0003

0.0570 ±

0.0002

0.0556 ±

0.0001

0.0537 ±

0.0003

0.0515 ±

0.0003

0.0480 ±

0.0002

0.0442 ±

0.0001

0.0395 ±

0.0002

150C GL 0.0585 ±

0.002

0.0579 ±

0.0001

0.0568 ±

0.0001

0.0548 ±

0.0002

0.0524 ±

0.0001

0.0491 ±

0.0002

0.0451 ±

0.0002

0.0403 ±

0.0002

0.0353 ±

0.0001

PS 0.0585 ±

0.002

0.0573 ±

0.0001

0.0554 ±

0.0002

0.0531 ±

0.0002

0.0500 ±

0.0002

0.0459 ±

0.0001

0.0409 ±

0.0001

0.0351 ±

0.0002

0.0279 ±

0.0002

PP 0.0585 ±

0.002

0.0576 ±

0.0002

0.0563 ±

0.0003

0.0542 ±

0.0001

0.0516 ±

0.0001

0.0482 ±

0.0003

0.0434 ±

0.0002

0.0380 ±

0.0001

0.0313 ±

0.0003

300C GL 0.0585 ±

0.002

0.0571 ±

0.0001

0.0551 ±

0.0002

0.0519 ±

0.0001

0.0477 ±

0.0001

0.0426 ±

0.0001

0.0362 ±

0.0001

0.0281 ±

0.0002

0.0190±

0.0002

PS 0.0585 ±

0.002

0.0568 ±

0.0001

0.0539 ±

0.0002

0.0502 ±

0.0001

0.0453 ±

0.0002

0.0394 ±

0.0002

0.0327 ±

0.0001

0.0247 ±

0.0001

0.0154 ±

0.0002

PP 0.0585 ±

0.002

0.0572 ±

0.0002

0.0552 ±

0.0001

0.0525 ±

0.0002

0.0491 ±

0.0001

0.0447 ±

0.0002

0.0391 ±

0.0002

0.0322 ±

0.0002

0.0237 ±

0.0002 GL= Borosilicate glass; PS= Polystyrene; PP= polypropylene; ±=Standard deviation

149

Apigenin

Periods*Storage medium*Temp (0C); LS Means

Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass PSPP

Control

40C

150C

300C

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Me

an

with

95

.0%

CI

3 Months

40C

150C

300C

6 Months

40C

150C

300C

9 Months

40C

150C

300C

12 Months

40C

150C

300C

15 Months

40C

150C

300C

18 Months

40C

150C

300C

21 Months

40C

150C

300C

24 Months

40C

150C

300C

Fig.5.1. Effect of storage conditions, medium and time on apigenin content of B. variegata

150

Apigenin

Periods*Storage medium; LS Means at 40C

Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

Mean w

ith 9

5.0

% C

I

Apigenin


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

Mean

with

95

.0%

CI

(a) (b)

Apigenin


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass

PS

PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Me

an

with

95

.0%

CI

(c)

Fig.5.2. Degradation of apigenin in different mediums over the period at 40C (a), 15

0C (b) and 30

0C (c).

151

3.1.2. Luteolin

The effect of temperature, medium and time on luteolin yield are summarized in Table

5.2 and also shown graphically in Fig. 5.3. Analysis revealed that the mean luteolin

yield (%) also decreases with increasing temperature and time and the decrease was

evident highest in PS followed by PP and Glass the least. Evaluating the effect of

temperature, medium and time all together on yield of luteolin, ANOVA revealed

significant effect of time (F=4868.20, p<0.001), medium (F=1636.15, p<0.001) and

temperature (F=2123.28, p<0.001) on luteolin yield. Further, the interaction effect of

time and medium (F=98.20, p<0.001), time and temperature (F=112.33, p<0.001),

medium and temperature (F=75.11, p<0.001), and time, medium and temperature

(F=5.25, p<0.001) was also found significant on Luteolin yield.

In addition, at all temperature and periods, Bonferroni test revealed analogous

(p>0.05) mean luteolin content in Glass and PP mediums but were higher

significantly (p<0.001) as compared to PS (Fig. 5.4).

152

Table 5.2. Effect of different temperature and mediums on luteolin content over the period of 24 months.

Temperature

(0C)

Medium

Time period

0 month 3 month 6 month 9 month 12 month 15 month 18 month 21 month 24 month

Luteolin content (%)

40C GL 0.0099 ±

0.0003

0.0098 ±

0.0001

0.0097 ±

0.0002

0.0095 ±

0.0002

0.0090 ±

0.0001

0.0086 ±

0.0001

0.0080 ±

0.0001

0.0074 ±

0.0001

0.0069 ±

0.0002

PS 0.0099 ±

0.0003

0.0096 ±

0.0002

0.0093 ±

0.0001

0.0085 ±

0.0001

0.0079 ±

0.0002

0.0071 ±

0.0002

0.0062 ±

0.0001

0.0050 ±

0.0002

0.0043 ±

0.0002

PP 0.0099 ±

0.0003

0.0097 ±

0.0001

0.0094 ±

0.0001

0.0091 ±

0.0001

0.0089 ±

0.0002

0.0084 ±

0.0001

0.0080 ±

0.0001

0.0073 ±

0.0002

0.0064 ±

0.0001

150C GL 0.0099 ±

0.0003

0.0097 ±

0.0001

0.0093 ±

0.0002

0.0087 ±

0.0001

0.0081 ±

0.0001

0.0074 ±

0.0001

0.0068 ±

0.0001

0.0056 ±

0.0002

0.0045 ±

0.0001

PS 0.0099 ±

0.0003

0.0094 ±

0.0001

0.0089 ±

0.0002

0.0084±

0.0001

0.0074 ±

0.0001

0.0064 ±

0.0001

0.0053 ±

0.0002

0.0041 ±

0.0002

0.0030 ±

0.0002

PP 0.0099 ±

0.0003

0.0095 ±

0.0001

0.0091 ±

0.0001

0.0086 ±

0.0002

0.0081 ±

0.0002

0.0072 ±

0.0001

0.0066 ±

0.0001

0.0055 ±

0.0002

0.0044 ±

0.0002

300C GL 0.0099 ±

0.0003

0.0092 ±

0.0001

0.0088 ±

0.0001

0.0083 ±

0.0002

0.0079 ±

0.0002

0.0072 ±

0.0001

0.0062 ±

0.0001

0.0052 ±

0.0001

0.0039 ±

0.0002

PS 0.0099 ±

0.0003

0.0090 ±

0.0001

0.0083 ±

0.0001

0.0071 ±

0.0002

0.0059 ±

0.0001

0.0048 ±

0.0002

0.0036 ±

0.0001

0.0023 ±

0.0002

0.0008 ±

0.0001

PP 0.0099 ±

0.0003

0.0095 ±

0.0001

0.0089 ±

0.0001

0.0084 ±

0.0001

0.0077 ±

0.0001

0.0068 ±

0.0001

0.0060 ±

0.0001

0.0047 ±

0.0001

0.0032 ±

0.0002

GL= Borosilicate glass; PS= Polystyrene; PP= polypropylene; ±=Standard deviation

153

Luteolin


Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass PS PP

Control

40C

15

0C

30

0C

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

Mean w

ith 9

5.0

% C

I

3 Months

40C

15

0C

30

0C

6 Months

40C

15

0C

30

0C

9 Months

40C

15

0C

30

0C

12 Months40C

15

0C

30

0C

15 Months

40C

15

0C

30

0C

18 Months

40C

15

0C

30

0C

21 Months

40C

15

0C

30

0C

24 Months

40C

15

0C

30

0C

Fig.5.3. Effect of different temperature and mediums on luteolin content over the period of 24 months.

154

Luteolin


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

Mean

with

95

.0%

CI

Luteolin


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

Mean

with

95

.0%

CI

(a) (b)

Luteolin


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

Mean w

ith 9

5.0

% C

I

(c)

Fig.5.4. Degradation of luteolin in different mediums over the period at 40C (a), 15

0C (b) and 30

0C (c).

155

3. 2. Oroxylum indicum

3.2.1. Chrysin

The effect of temperature, medium and time on chrysin yield are summarized in Table

5.3 and also shown graphically in Fig. 5.5. Result shows that the mean chrysin yield

(%) also decreases with increasing temperature and time and the decrease was

evidently highest in PS followed by Glass and PP the least. Evaluating the effect of

temperature, medium and time all together on yield of Chrysin, ANOVA revealed

significant effect of time (F=1196087.72, p<0.001), medium (F=185762.74, p<0.001)

and temperature (F=965036.65, p<0.001) on chrysin yield. Further, the interaction

effect of time and medium (F=13456.00, p<0.001), time and temperature

(F=102602.39, p<0.001), medium and temperature (F=16679.59, p<0.001), and time,

medium and temperature (F=2199.07, p<0.001) was also found significant on chrysin

yield.

Moreover, at lower temperature (40C), Bonferroni test revealed a significantly

(p<0.001) different and higher mean chrysin yield in Glass medium from 6-24 months

as compared to both PS and PP mediums (Fig. 5.6). However, at medium temperature

(150C), the mean yield of chrysin was similar (p>0.05) in Glass and PP mediums and

were higher significantly (p<0.001) as compared to PS at all periods (Fig. 3.6). In

contrast, at higher temperature (300C) and durations (9-24 months), the mean chrysin

yield in PP was significantly (p<0.001) different and higher as compared to both

Glass and especially PS (Fig. 5.6).

156

Table 5.3. Effect of different temperature and mediums on chrysin content over the period of 24 months.

Temperature

(0C)

Medium

Time period


Chrysin content (%)

40C GL 0.6107 ±

0.0002

0.6102 ±

0.0001

0.6086 ±

0.0001

0.6060 ±

0.0001

0.6023 ±

0.0002

0.5976 ±

0.0002

0.5925 ±

0.0002

0.5853 ±

0.0003

0.5781 ±

0.0002

PS 0.6107 ±

0.0002

0.6084 ±

0.0001

0.6046 ±

0.0002

0.5992 ±

0.0001

0.5922 ±

0.0002

0.5813 ±

0.0002

0.5677 ±

0.0003

0.5534 ±

0.0003

0.5373 ±

0.0002

PP 0.6107 ±

0.0002

0.6089 ±

0.0002

0.6053 ±

0.0001

0.6006 ±

0.0001

0.5938 ±

0.0001

0.5841 ±

0.0002

0.5737 ±

0.0001

0.5581 ±

0.0002

0.5433 ±

0.0002

150C GL 0.6107 ±

0.0002

0.6085 ±

0.0002

0.6044±

0.0004

0.5973 ±

0.0002

0.5882 ±

0.0001

0.5763 ±

0.0002

0.5618 ±

0.0001

0.5454 ±

0.0003

0.5276 ±

0.0002

PS 0.6107 ±

0.0002

0.6050 ±

0.0001

0.5957 ±

0.0001

0.5832 ±

0.0002

0.5699 ±

0.0002

0.5552 ±

0.0003

0.5382 ±

0.0002

0.5207 ±

0.0003

0.5022 ±

0.0002

PP 0.6107 ±

0.0002

0.6078 ±

0.0002

0.6015 ±

0.0002

0.5922 ±

0.0002

0.5813 ±

0.0002

0.5673 ±

0.0001

0.5526 ±

0.0002

0.5355 ±

0.0002

0.5193 ±

0.0002

300C GL 0.6107 ±

0.0002

0.6069 ±

0.0002

0.5994 ±

0.0002

0.5873 ±

0.0001

0.5723 ±

0.0002

0.5542 ±

0.0002

0.5282 ±

0.0003

0.4983 ±

0.0002

0.4636 ±

0.0002

PS 0.6107 ±

0.0002

0.6032 ±

0.0002

0.5938 ±

0.0001

0.5795 ±

0.0001

0.5577 ±

0.0002

0.5318 ±

0.0001

0.4974 ±

0.0002

0.4581 ±

0.0002

0.4144 ±

0.0001

PP 0.6107 ±

0.0002

0.6067 ±

0.0002

0.5994 ±

0.0002

0.5873 ±

0.0002

0.5724 ±

0.0003

0.5544 ±

0.0003

0.5280 ±

0.0001

0.4983 ±

0.0001

0.4637 ±


157

Chrysin


Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass PS PP

Control

40 C

15

0 C

30

0 C

0.38

0.40

0.42

0.44

0.46

0.48

0.50

0.52

0.54

0.56

0.58

0.60

0.62

0.64

Mean w

ith 9

5.0

% C

I

3 Months

40 C

15

0 C

30

0 C

6 Months

40 C

15

0 C

30

0 C

9 Months

40 C

15

0 C

30

0 C

12 Months

40 C

15

0 C

30

0 C

15 Months

40 C

15

0 C

30

0 C

18 Months

40 C

15

0 C

30

0 C

21 Months

40 C

15

0 C

30

0 C

24 Months

40 C

15

0 C

30

0 C

Fig. 5.5. Effect of different storage conditions, mediums and time on chrysin content of O.indicum

158

Chrysin


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.52

0.53

0.54

0.55

0.56

0.57

0.58

0.59

0.60

0.61

0.62

Me

an

with 9

5.0

% C

I

Chrysin


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.48

0.50

0.52

0.54

0.56

0.58

0.60

0.62

0.64

Me

an

with 9

5.0

% C

I

(a) (b)

Chrysin


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.38

0.40

0.42

0.44

0.46

0.48

0.50

0.52

0.54

0.56

0.58

0.60

0.62

0.64

Mean w

ith 9

5.0

% C

I

(c)

Fig.5.6. Temperature wise concentration of chrysin at (a) 40C (b) 15

0C (c) 30

0C.

159

3.2.2. Luteolin

The effect of temperature, medium and time on luteolin yield are summarized in Table

5.4 and also shown graphically in Fig. 5.7. Analysis revealed that the mean luteolin

yield (%) also decreases with increasing temperature and time and the decrease was

evident highest in PS followed by PP and Glass the least. Evaluating the effect of

temperature, medium and time all together on yield of luteolin, ANOVA revealed

significant effect of time (F=4868.20, p<0.001), medium (F=1636.15, p<0.001) and

temperature (F=2123.28, p<0.001) on luteolin yield. Further, the interaction effect of

time and medium (F=98.20, p<0.001), time and temperature (F=112.33, p<0.001),

medium and temperature (F=75.11, p<0.001), and time, medium and temperature

(F=5.25, p<0.001) was also found significant on Luteolin yield.

In addition, at all temperature and periods, Bonferroni test revealed analogous

(p>0.05) mean luteolin content in Glass and PP mediums but were higher

significantly (p<0.001) as compared to PS (Fig. 5.8).

160

Table 5.4. Effect of different temperature and mediums on luteolin content over the period of 24 months.

Temperature

(0C)

Medium

Time period


Luteolin content (%)

40C GL 0.0099 ±

0.0003

0.0098 ±

0.0001

0.0097 ±

0.0002

0.0095 ±

0.0002

0.0090 ±

0.0001

0.0086 ±

0.0001

0.0080 ±

0.0001

0.0074 ±

0.0001

0.0069 ±

0.0002

PS 0.0099 ±

0.0003

0.0096 ±

0.0002

0.0093 ±

0.0001

0.0085 ±

0.0001

0.0079 ±

0.0002

0.0071 ±

0.0002

0.0062 ±

0.0001

0.0050 ±

0.0002

0.0043 ±

0.0002

PP 0.0099 ±

0.0003

0.0097 ±

0.0001

0.0094 ±

0.0001

0.0091 ±

0.0001

0.0089 ±

0.0002

0.0084 ±

0.0001

0.0080 ±

0.0001

0.0073 ±

0.0002

0.0064 ±

0.0001

150C GL 0.0099 ±

0.0003

0.0097 ±

0.0001

0.0093 ±

0.0002

0.0087 ±

0.0001

0.0081 ±

0.0001

0.0074 ±

0.0001

0.0068 ±

0.0001

0.0056 ±

0.0002

0.0045 ±

0.0001

PS 0.0099 ±

0.0003

0.0094 ±

0.0001

0.0089 ±

0.0002

0.0084±

0.0001

0.0074 ±

0.0001

0.0064 ±

0.0001

0.0053 ±

0.0002

0.0041 ±

0.0002

0.0030 ±

0.0002

PP 0.0099 ±

0.0003

0.0095 ±

0.0001

0.0091 ±

0.0001

0.0086 ±

0.0002

0.0081 ±

0.0002

0.0072 ±

0.0001

0.0066 ±

0.0001

0.0055 ±

0.0002

0.0044 ±

0.0002

300C GL 0.0099 ±

0.0003

0.0092 ±

0.0001

0.0088 ±

0.0001

0.0083 ±

0.0002

0.0079 ±

0.0002

0.0072 ±

0.0001

0.0062 ±

0.0001

0.0052 ±

0.0001

0.0039 ±

0.0002

PS 0.0099 ±

0.0003

0.0090 ±

0.0001

0.0083 ±

0.0001

0.0071 ±

0.0002

0.0059 ±

0.0001

0.0048 ±

0.0002

0.0036 ±

0.0001

0.0023 ±

0.0002

0.0008 ±

0.0001

PP 0.0099 ±

0.0003

0.0095 ±

0.0001

0.0089 ±

0.0001

0.0084 ±

0.0001

0.0077 ±

0.0001

0.0068 ±

0.0001

0.0060 ±

0.0001

0.0047 ±

0.0001

0.0032 ±


161

Luteolin


Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass PS PP

Control

40C

15

0C

30

0C

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

Mean w

ith 9

5.0

% C

I

3 Months

40C

15

0C

30

0C

6 Months

40C

15

0C

30

0C

9 Months

40C

15

0C

30

0C

12 Months40C

15

0C

30

0C

15 Months

40C

15

0C

30

0C

18 Months

40C

15

0C

30

0C

21 Months

40C

15

0C

30

0C

24 Months

40C

15

0C

30

0C

Fig. 5.7. Effect of different temperature and mediums on luteolin content over the period of 24 months.

162

Luteolin


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

Mean

with

95

.0%

CI

Luteolin


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

Mean

with

95

.0%

CI

(a) (b)

Luteolin


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

Mean w

ith 9

5.0

% C

I

(c)

Fig.5.8. Temperature wise concentration of luteolin at (a) 40C (b) 15

0C (c) 30

0C

163

3. 2. Oroxylum indicum

3.2.1. Chrysin

The effect of temperature, medium and time on chrysin yield are summarized in Table

5.5 and also shown graphically in Fig. 5.9. Result shows that the mean chrysin yield

(%) also decreases with increasing temperature and time and the decrease was

evidently highest in PS followed by Glass and PP the least. Evaluating the effect of

temperature, medium and time all together on yield of Chrysin, ANOVA revealed

significant effect of time (F=1196087.72, p<0.001), medium (F=185762.74, p<0.001)

and temperature (F=965036.65, p<0.001) on chrysin yield. Further, the interaction

effect of time and medium (F=13456.00, p<0.001), time and temperature


medium and temperature (F=2199.07, p<0.001) was also found significant on chrysin

yield.

Moreover, at lower temperature (40C), Bonferroni test revealed a significantly

(p<0.001) different and higher mean chrysin yield in Glass medium from 6-24 months

as compared to both PS and PP mediums (Fig. 5.10). However, at medium

temperature (150C), the mean yield of chrysin was similar (p>0.05) in Glass and PP

mediums and were higher significantly (p<0.001) as compared to PS at all periods

(Fig. 5.10). In contrast, at higher temperature (300C) and durations (9-24 months), the

mean chrysin yield in PP was significantly (p<0.001) different and higher as

compared to both Glass and especially PS (Fig. 5.10).

164

Table 5.5. Effect of different temperature and mediums on chrysin content over the period of 24 months.

Temperature

(0C)

Medium

Time period


Chrysin content (%)

40C GL 0.6107 ±

0.0002

0.6102 ±

0.0001

0.6086 ±

0.0001

0.6060 ±

0.0001

0.6023 ±

0.0002

0.5976 ±

0.0002

0.5925 ±

0.0002

0.5853 ±

0.0003

0.5781 ±

0.0002

PS 0.6107 ±

0.0002

0.6084 ±

0.0001

0.6046 ±

0.0002

0.5992 ±

0.0001

0.5922 ±

0.0002

0.5813 ±

0.0002

0.5677 ±

0.0003

0.5534 ±

0.0003

0.5373 ±

0.0002

PP 0.6107 ±

0.0002

0.6089 ±

0.0002

0.6053 ±

0.0001

0.6006 ±

0.0001

0.5938 ±

0.0001

0.5841 ±

0.0002

0.5737 ±

0.0001

0.5581 ±

0.0002

0.5433 ±

0.0002

150C GL 0.6107 ±

0.0002

0.6085 ±

0.0002

0.6044±

0.0004

0.5973 ±

0.0002

0.5882 ±

0.0001

0.5763 ±

0.0002

0.5618 ±

0.0001

0.5454 ±

0.0003

0.5276 ±

0.0002

PS 0.6107 ±

0.0002

0.6050 ±

0.0001

0.5957 ±

0.0001

0.5832 ±

0.0002

0.5699 ±

0.0002

0.5552 ±

0.0003

0.5382 ±

0.0002

0.5207 ±

0.0003

0.5022 ±

0.0002

PP 0.6107 ±

0.0002

0.6078 ±

0.0002

0.6015 ±

0.0002

0.5922 ±

0.0002

0.5813 ±

0.0002

0.5673 ±

0.0001

0.5526 ±

0.0002

0.5355 ±

0.0002

0.5193 ±

0.0002

300C GL 0.6107 ±

0.0002

0.6069 ±

0.0002

0.5994 ±

0.0002

0.5873 ±

0.0001

0.5723 ±

0.0002

0.5542 ±

0.0002

0.5282 ±

0.0003

0.4983 ±

0.0002

0.4636 ±

0.0002

PS 0.6107 ±

0.0002

0.6032 ±

0.0002

0.5938 ±

0.0001

0.5795 ±

0.0001

0.5577 ±

0.0002

0.5318 ±

0.0001

0.4974 ±

0.0002

0.4581 ±

0.0002

0.4144 ±

0.0001

PP 0.6107 ±

0.0002

0.6067 ±

0.0002

0.5994 ±

0.0002

0.5873 ±

0.0002

0.5724 ±

0.0003

0.5544 ±

0.0003

0.5280 ±

0.0001

0.4983 ±

0.0001

0.4637 ±

0.0001

GL= Borosilicate glass; PS= Polystyrene; PP= polypropylene; ±=Standard deviation

165

Chrysin

Period*Medium*Temperature; LS Means

Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass

PS

PP

0 Month

40C

15

0C

30

0C

0.38

0.40

0.42

0.44

0.46

0.48

0.50

0.52

0.54

0.56

0.58

0.60

0.62

0.64

Mean w

ith 9

5.0

% C

I

3 Month

40C

15

0C

30

0C

6 Month

40C

15

0C

30

0C

9 Month

40C

15

0C

30

0C

12 Month4

0C

15

0C

30

0C

15 Month

40C

15

0C

30

0C

18 Month

40C

15

0C

30

0C

21 Month

40C

15

0C

30

0C

24 Month

40C

15

0C

30

0C

Fig. 5.9. Effect of different temperature and mediums on the yield of chrysin over the period of 24 months.

166

Luteolin


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

Mean

with

95

.0%

CI

Luteolin


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

Mean

with

95

.0%

CI

(a) (b)

Luteolin


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

Mean w

ith 9

5.0

% C

I

(c)

Fig. 5.10. Degradation of chrysin in different mediums over the period at 40C (a), 15

0C (b) and 30

0C (c).

167

3.2.2. Baicalein

The effect of temperature, medium and time on baicalein yield are summarized in

Table 5.6 and also been represented graphically in Fig. 5.11. Data showed that the

mean baicalein yield (%) also decreases with increasing temperature and time and the

decrease was found to be highest in PS followed by Glass and PP the least. Evaluating

the effect of temperature, medium and time all together on yield of baicalein, ANOVA

revealed significant effect of time (F=688851.64, p<0.001), medium (F=79163.18,

p<0.001) and temperature (F=505064.36, p<0.001) on baicalein yield. Further, the

interaction effect of time and medium (F=7366.43, p<0.001), time and temperature


medium and temperature (F=1184.79, p<0.001) was also found significant on

baicalein yield.

Furthermore, at both lower (40C) and medium (15

0C) temperature, Bonferroni test

revealed similar (p>0.05) mean baicalein yield in both Glass and PS mediums and

were significantly (p<0.001) different and higher as compare to PP at all periods (Fig.

5.12). However, at higher temperature (300C) and durations (3-24 months), the mean

yield of baicalein in PP medium was significantly (p<0.01 or p<0.001) different and

higher as compared to both Glass and PS (Fig.5.12).

168

Table 5.6. Effect of different temperature and mediums on baicalein content of O.indicum over the period of 24 months.

Temperature

(0C)

Medium

Time period


Baicalein content (%)

40C GL

0.1762 ±

0.0002

0.1754 ±

0.0003

0.1735 ±

0.0001

0.1705 ±

0.0001

0.1665 ±

0.0002

0.1617 ±

0.0002

0.1554 ±

0.0002

0.1482 ±

0.0001

0.1397 ±

0.0001

PS

0.1762 ±

0.0002

0.1744 ±

0.0002

0.1716 ±

0.0001

0.1682 ±

0.0002

0.1632 ±

0.0002

0.1572 ±

0.0002

0.1497 ±

0.0002

0.1406 ±

0.0001

0.1298 ±

0.0001

PP

0.1762 ±

0.0002

0.1754 ±

0.0003

0.1732 ±

0.0002

0.1696 ±

0.0002

0.1657 ±

0.0001

0.1606 ±

0.0002

0.1538 ±

0.0001

0.1463 ±

0.0002

0.1373 ±

0.0002

150C GL

0.1762 ±

0.0002

0.1740 ±

0.0002

0.1690 ±

0.0003

0.1606 ±

0.0001

0.1517 ±

0.0001

0.1395 ±

0.0001

0.1262 ±

0.0001

0.1115 ±

0.0003

0.0953 ±

0.0002

PS

0.1762 ±

0.0002

0.1722 ±

0.0002

0.1657 ±

0.0003

0.1562 ±

0.0001

0.1436 ±

0.0002

0.1287 ±

0.0002

0.1111 ±

0.0001

0.0915 ±

0.0002

0.0669 ±

0.0002

PP

0.1762 ±

0.0002

0.1737 ±

0.0002

0.1688 ±

0.0001

0.1605 ±

0.0001

0.1509 ±

0.0002

0.1378 ±

0.0001

0.1245 ±

0.0001

0.1092 ±

0.0002

0.0934 ±

0.0003

300C GL

0.1762 ±

0.0002

0.1733 ±

0.0002

0.1670 ±

0.0001

0.1572 ±

0.0002

0.1448 ±

0.0001

0.1302 ±

0.0002

0.1145 ±

0.0001

0.0975 ±

0.0001

0.0798 ±

0.0001

PS

0.1762 ±

0.0002

0.1705 ±

0.0002

0.1622 ±

0.0002

0.1513 ±

0.0002

0.1362 ±

0.0003

0.1175 ±

0.0001

0.0956 ±

0.0003

0.0700 ±

0.0002

0.0407 ±

0.0002

PP

0.1762 ±

0.0002

0.1735 ±

0.0001

0.1685 ±

0.0002

0.1605 ±

0.0004

0.1488 ±

0.0001

0.1351 ±

0.0003

0.1204 ±

0.0001

0.1046 ±

0.0002

0.0881 ±


169

Baicalein


Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass P PP

Control

40C

150C

300C

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

Mean w

ith 9

5.0

% C

I

3 Months

40C

150C

300C

6 Months

40C

150C

300C

9 Months

40C

150C

300C

12 Months

40C

150C

300C

15 Months

40C

150C

300C

18 Months

40C

150C

300C

21 Months

40C

150C

300C

24 Months

40C

150C

300C

Fig. 5.11. Effect of different temperature and mediums on the yield of baicalein over the period of 24 months.

170

Baicalein


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.12

0.13

0.14

0.15

0.16

0.17

0.18

0.19

Me

an

with

95

.0%

CI

Baicalein


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

Me

an

with 9

5.0

% C

I

(a) (b)

Baicalein


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20M

ean

with 9

5.0

% C

I

(c)

Fig. 5.12. Degradation of baicalein in different mediums over the period at 40C (a), 15

0C (b) and 30

0C (c).

171

3. 3. Holarrhena pubescens

3.3.1. Conessine

The effect of temperature, medium and time on conessine yield are summarized in

Table 5.7 and also shown graphically in Fig. 5.13. Results obtained after analysis

reveals that the mean conessine yield (%) also decreases with increasing temperature

and time and the decrease was found to be highest in PS followed by Glass and PP the

least. Evaluating the effect of temperature, medium and time all together on yield of

conessine, ANOVA revealed significant effect of time (F=69026.26, p<0.001),

medium (F=54222.80, p<0.001) and temperature (F=34410.16, p<0.001) on

conessine yield. Further, the interaction effect of time and medium (F=3505.64,

p<0.001), time and temperature (F=2369.92, p<0.001), medium and temperature

(F=1271.16, p<0.001), and time, medium and temperature (F=123.95, p<0.001) was

also found significant on conessine yield.

Furthermore, at lower temperature (40C) and higher durations (12-24 months),

Bonferroni test revealed significantly (p<0.05 or p<0.001) different and higher mean

conessine yield in Glass medium as compared to both PP and especially PS medium

(Fig. 3.10). In contrast, at medium temperature (150C) and higher durations (9-21

months), the mean conessine yield in PP medium was significantly (p<0.01 or

p<0.001) different and higher as compared to both Glass and especially PS (Fig.

5.14). Conversely, at higher temperature (300C) and durations (3-24 month), the mean

conessine yield in PP was significantly (p<0.05 or p<0.01 or p<0.001) different and

higher as compared to both Glass and PS (Fig. 5.14).

172

Table 5.7. Effect of different temperature and mediums on conessine yield of H. pubescens over the period of 24 months.

Temperature

(0C)

Medium

Time period


Conessine content (%)

40C GL

1.0073 ±

0.0002

1.0073 ±

0.0002

1.0072 ±

0.0001

1.0069 ±

0.0002

1.0060 ±

0.0002

1.0049 ±

0.0002

1.0026 ±

0.0003

0.9984 ±

0.0003

0.9922 ±

0.0003

PS

1.0073 ±

0.0002

1.0065 ±

0.0002

1.0039 ±

0.0003

1.0016 ±

0.0002

0.9970 ±

0.0003

0.9917 ±

0.0002

0.9874 ±

0.0002

0.9814 ±

0.0003

0.9765 ±

0.0004

PP

1.0073 ±

0.0002

1.0073 ±

0.0002

1.0072 ±

0.0001

1.0063 ±

0.0002

1.0043 ±

0.0002

1.0021 ±

0.0003

1.0002 ±

0.0004

0.9955 ±

0.0002

0.9900 ±

0.0003

150C GL

1.0073 ±

0.0002

1.0073 ±

0.0002

1.0060 ±

0.0003

1.0031 ±

0.0003

0.9992 ±

0.0001

0.9955 ±

0.0002

0.9915 ±

0.0001

0.9874 ±

0.0003

0.9832 ±

0.0003

PS

1.0073 ±

0.0002

1.0063 ±

0.0002

1.0023 ±

0.0002

0.9973 ±

0.0002

0.9894 ±

0.0003

0.9833 ±

0.0002

0.9773 ±

0.0002

0.9701 ±

0.0003

0.9622 ±

0.0002

PP

1.0073 ±

0.0002

1.0073 ±

0.0002

1.0052 ±

0.0002

1.0032 ±

0.0003

1.0005 ±

0.0003

0.9969 ±

0.0002

0.9922 ±

0.0001

0.9865 ±

0.0002

0.9795 ±

0.0001

300C GL

1.0073 ±

0.0002

1.0073 ±

0.0002

1.0042 ±

0.0001

1.0005 ±

0.0003

0.9951 ±

0.0003

0.9912 ±

0.0004

0.9853 ±

0.0002

0.9802 ±

0.0003

0.9747 ±

0.0002

PS

1.0073 ±

0.0002

1.0056 ±

0.0003

1.0005 ±

0.0002

0.9939 ±

0.0002

0.9861±

0.0002

0.9776 ±

0.0002

0.9682 ±

0.0001

0.9603 ±

0.0002

0.9512 ±

0.0003

PP

1.0073 ±

0.0002

1.0073 ±

0.0002

1.0052 ±

0.0001

1.0024 ±

0.0003

0.9984 ±

0.0003

0.9949 ±

0.0002

0.9902 ±

0.0002

0.9846 ±

0.0001

0.9789 ±


173

Conessine


Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass PS PP

Control

40C

150C

30

0C

0.94

0.95

0.96

0.97

0.98

0.99

1.00

1.01

1.02

Mean w

ith 9

5.0

% C

I

3 Months

40C

150C

30

0C

6 Months

40C

150C

30

0C

9 Months

40C

150C

30

0C

12 Months

40C

150C

30

0C

15 Months

40C

150C

30

0C

18 Months

40C

150C

30

0C

21 Months

40C

150C

30

0C

24 Months

40C

150C

30

0C

Fig 5.13. Effect of different temperature and mediums on the yield of conessine over the period of 24 months.

174

Conessine


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.970

0.975

0.980

0.985

0.990

0.995

1.000

1.005

1.010

1.015

Mean w

ith 9

5.0

% C

I

Conessine


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.95

0.96

0.97

0.98

0.99

1.00

1.01

1.02

Mean w

ith 9

5.0

% C

I

(a) (b)

Conessine


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.94

0.95

0.96

0.97

0.98

0.99

1.00

1.01

1.02M

ean w

ith 9

5.0

% C

I

(c)

Fig. 5.14. Degradation of conessine in different mediums over the period at 40C (a), 15

0C (b) and 30

0C (c).

175

3. 4. Terminalia arjuna

3.4.1. Arjunic acid

The effect of temperature, medium and time on arjunic acid yield is summarized in

Table 5.8 and has been represented graphically in Fig. 5.15. It was analyzed that the

mean arjunic acid yield (%) also decreases with increasing temperature and time and

the decrease was evidently highest in PS followed by PP and Glass the least.

Evaluating the effect of temperature, medium and time all together on yield of Arjunic

acid, ANOVA revealed significant effect of time (F=26381.24, p<0.001), medium

(F=3996.77, p<0.001) and temperature (F=3335.91, p<0.001) on arjunic acid yield.

Further, the interaction effect of time and medium (F=171.29, p<0.001), time and

temperature (F=166.62, p<0.001), medium and temperature (F=290.01, p<0.001), and

time, medium and temperature (F=10.93, p<0.001) was also found significant on

arjunic acid yield.

Furthermore, at both lower (40C) and medium (15

0C) temperature, Bonferroni test

revealed similar (p>0.05) mean yield of arjunic acid in both Glass and PS mediums at

all periods and the yield of both the mediums were significantly (p<0.05 or p<0.01 or

p<0.001) different and higher at all periods (3-24 month) as compared to PP (Fig.

5.16). However, at higher temperature (300C) and all periods (3-24 month), the mean

yield of arjunic acid in Glass medium was significantly (p<0.05 or p<0.01 or

p<0.001) different and higher as compared to both PS and PP mediums (Fig. 5.16).

176

Table 5.8. Effect of different temperature and mediums on arjunic acid yield of T. arjuna over the period of 24 months.

Temperature

(0C)

Medium

Time period


Arjunic acid content (%)

40C GL

0.5763 ±

0.0002

0.5763 ±

0.0002

0.5763 ±

0.0002

0.5749 ±

0.0001

0.5742 ±

0.0001

0.5723 ±

0.0002

0.5703 ±

0.0002

0.5673 ±

0.0002

0.5642 ±

0.0001

PS

0.5763 ±

0.0002

0.5763 ±

0.0002

0.5763 ±

0.0002

0.5739 ±

0.0002

0.5730 ±

0.0002

0.5710 ±

0.0002

0.5682 ±

0.0001

0.5643 ±

0.0002

0.5607 ±

0.0003

PP

0.5763 ±

0.0002

0.5763 ±

0.0002

0.5751 ±

0.0001

0.5745 ±

0.0002

0.5739 ±

0.0002

0.5721 ±

0.0002

0.5691 ±

0.0002

0.5662 ±

0.0001

0.5633 ±

0.0002

150C GL

0.5763 ±

0.0002

0.5761±

0.0001

0.5752 ±

0.0001

0.5749 ±

0.0002

0.5739 ±

0.0002

0.5714 ±

0.0002

0.5693 ±

0.0002

0.5661 ±

0.0002

0.5623 ±

0.0002

PS

0.5763 ±

0.0002

0.5749 ±

0.0002

0.5741 ±

0.0002

0.5731 ±

0.0001

0.5719 ±

0.0001

0.5684 ±

0.0003

0.5663 ±

0.0002

0.5622 ±

0.0001

0.5585 ±

0.0002

PP

0.5763 ±

0.0002

0.5760 ±

0.0002

0.5753 ±

0.0002

0.5743 ±

0.0001

0.5733 ±

0.0002

0.5704 ±

0.0002

0.5678 ±

0.0003

0.5642 ±

0.0001

0.5604 ±

0.0003

300C GL

0.5763 ±

0.0002

0.5759 ±

0.0001

0.5753 ±

0.0001

0.5746 ±

0.0001

0.5732 ±

0.0002

0.5708 ±

0.0001

0.5683 ±

0.0002

0.5652 ±

0.0002

0.5613 ±

0.0002

PS

0.5763 ±

0.0002

0.5743 ±

0.0001

0.5729 ±

0.0003

0.5711 ±

0.0002

0.5692 ±

0.0001

0.5663 ±

0.0001

0.5634 ±

0.0003

0.5594 ±

0.0003

0.5544 ±

0.0003

PP

0.5763 ±

0.0002

0.5754 ±

0.0001

0.5740 ±

0.0002

0.5731 ±

0.0001

0.5718 ±

0.0001

0.5692 ±

0.0001

0.5660 ±

0.0003

0.5626 ±

0.0002

0.5585 ±


177

\

Arjunic acid


Wilks lambda=.00000, F(192, 936.45)=87.554, p=0.0000

Glass PS PP

Control

40 C

15

0 C

300 C

0.550

0.555

0.560

0.565

0.570

0.575

0.580

Mean w

ith 9

5.0

% C

I

3 Months

40 C

15

0 C

300 C

6 Months

40 C

15

0 C

300 C

9 Months

40 C

15

0 C

300 C

12 Months

40 C

15

0 C

300 C

15 Months

40 C

15

0 C

300 C

18 Months

40 C

15

0 C

300 C

21 Months

40 C

15

0 C

300 C

24 Months

40 C

15

0 C

300 C

Fig. 5.15. Effect of different temperature and mediums on the yield of arjunic acid over the period of 24 months.

178

Arjunic acid


Wilks lambda=.00000, F(96, 284.43)=53.171, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.558

0.560

0.562

0.564

0.566

0.568

0.570

0.572

0.574

0.576

0.578

0.580

Mean w

ith 9

5.0

% C

I

Arjunic acid


Wilks lambda=.00000, F(96, 284.43)=85.842, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.556

0.558

0.560

0.562

0.564

0.566

0.568

0.570

0.572

0.574

0.576

0.578

0.580

Me

an

with 9

5.0

% C

I

(a) (b)

Arjunic acid


Wilks lambda=.00000, F(96, 284.43)=119.97, p=0.0000

Glass PS PP

Control3 Months

6 Months9 Months

12 Months15 Months

18 Months21 Months

24 Months

Periods

0.550

0.555

0.560

0.565

0.570

0.575

0.580

Mean w

ith 9

5.0

% C

I

(c)

Fig. 5.16. Degradation of arjunic acid in different mediums over the period at 40C (a), 15

0C (b) and 30

0C (c).

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4. Discussion

Decrease in active constituent of any medicinal product commonly reduces its efficacy.

Therefore, it is important to determine their optimum storage condition and time, to know

the period up to which the drug may be stored without losing much of their efficacy. The

results of this investigation reveal considerable degradation in the amount of

phytoconstituent which was time, medium and temperature dependent.

The biomarkers used for quantitative analysis of B. variegata were apigenin and luteolin.

The foremost reason for selection of these biomarkers was their direct relation with the

anti-inflammatory potential of the plant. The compounds are known to possess potential

anti-inflammatory activity (Ueda et al., 2002; Seelinger et al., 2008; Ziyan et al. 2007)

and it is well established that due to the presence of these bioactive compounds, the plant

is used for anti-inflammatory purposes. It was interesting to note that these active

principles showed considerable degradation from 9th

and 12th

months, respectively.

Likewise, chrysin and baicalein, the major bioactive compounds of O. indicum (Gautam

and Jachak, 2009; Hong et al., 2002; Kavimani et al., 2000; Kim et al., 2004; Lin and

Shieh, 1996; Mueller et al., 2010; Song et al., 2012; Woo et al., 2005) also degraded in

quantity with time. Though, these bioactive constituents were found to be more stable

than that of constituents of B. variegata because deterioration in these compounds started

to a notably large extent from 12th

and 15th

month, respectively. Conessine, the bioactive

component of H. pubescens, however showed rapid deterioration which started from the

very 6th

month and the rate was highest than other compounds used in the study. This

may be due to the alkaloid nature of the compound which makes it unstable. The

terpenoid compound arjunic acid from T. arjuna also degraded with time but it was found

to be far more stable than any other compound.

The bioactive nature of many secondary metabolites may arise from the presence of

highly reactive functional groups. Secondary metabolites may deteriorate because they

react with and disrupt the functions of physiologically important molecules such as

enzymes or DNA. Because of this reactivity, these compounds also may undergo

reactions that lead to their deterioration or conversion. Compound decomposition and

conversion can be problematic because they mislead quantitative data and could diminish

the magnitude of metabolite activities in bioassays. Our results show that methods of

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storing can significantly affect yields of biologically and ecologically important

compounds. The study reveals that commonly used containers made up of polystyrene

material leads to highest detrimental effects on the stability of compounds. Based on the

results of our investigation, we suggest that, containers made up of borosilicate glass or

polypropylene material could be used instead of polystyrene containers. Again, as it is

evident that glass is highly fragile in nature, thus, polypropylene could be the best

recommended material to repress the deterioration of the bioactive constituents.

CHAPTER 6

Testing the Suitability of Plant Part Substitution Method for Sustainability of Tree Species

181

TESTING THE SUITABILITY OF PLANT PART SUBSTITUTION METHOD

FOR SUSTAINABILITY OF TREE SPECIES

1. Introduction

India, a megadiversity country in terms of both biodiversity and people, is battling

environmental problems in many fronts like dependence on natural resources and

biodiversity crisis (Singh and Bagchi, 2013). Population growth, urbanization and

unrestricted collection of medicinal plants (especially tree species) from wild are

resulting in overexploitation of natural resources (Zschoke et al., 2000). One of the key

factors which contribute in the same is the growing commercial trade of natural products

particularly for neutraceuticals and plant derived pharmaceuticals (Cunningham 1991).

Due to an increasingly critical attitude towards the chemical industries and synthetic

products there is an inclination towards the herbal medicines, especially as over-the-

counter medication. In India, however medicinal plants are cultivated on large scale to

meet this growing demand but still, popular species which are slow growing and slow

reproducing are especially vulnerable to excessive collection and due to unsustainable

collection and over exploitation more and more indigenous species are becoming

threatened (Cunningham and Mbenkum, 1993; Ticktin, 2004) which includes more of

tree species. The destructive harvesting for the plant parts like bark and root is of great

concern for resource managers. Optimistically, studies on methods and impact of

harvesting tree species (Cunningham and Mbenkum, 1993; Delvaux et al., 2009)

contributes crucially for management of the same but again, we cannot favor one level

but have to make a study focusing on all levels of forest management (Ticktin, 2004).

Some strategies to solve this problem, is to establish conservation areas and restrict bark

collection but again, these are not practically applicable in many cases. Yet another

would be large scale cultivation but cultivation is not always a solution for the woody

species as they take years to grow to produce desired secondary metabolite. In order to

withstand heavy harvest new management practices are necessary for these species

(Ticktin 2004). In the backdrop of these situations, we propose an interdisciplinary

approach which can help minimize these challenges by adding insight and novel

182

perspectives which is above the much debated „species or ecosystem approach‟ (Likens

and Lindenmayer, 2012) or „conservation through use approach‟ (Dickinson et al., 1996;

Johnson and Cabarle, 1993; Plotkin and Famolare, 1992). Here, we emphasize on a

strategy which would fulfill the market demand for health care as well as satisfy the

requirement of sustainable harvesting. As it is known that ethno-pharmacology is

inextricably interconnected with biodiversity which constitutes its resource base and

should play a more active role in determining actions needed to assess, monitor and

conserve them (Heywood, 2011). An attempt has been made to establish its necessary

linkage for utilizing the valuable resource sensibly, thus contributing equally to the

conservation aspect. This could be achieved by applying biopharmaceutical equivalence

approach to the issue. Encouraging the collection of alternative plant parts instead of vital

parts like roots and stem bark could be a plausible solution. Zschoke et al. (2000) also

emphasized on this technique. However, it is imperative that the part used should be

chemically and pharmacologically validated for the concerned activity. Which means it

should contain the same active substance or therapeutic moiety and clinically shows the

same effectiveness as traditionally used plant parts, whose efficacy have been

established. In this way, the plant part substitution (PPS) method could be a more focused

and practical approach towards sustainability. The study adumbrates the concept of PPS

method using the four tree species viz. Bauhinia variegata, Oroxylum indicum,

Holarrhena pubescens and Terminalia arjuna. In the present study, we have evaluated

the chemical similarities (qualitative and quantitative) in terms of major bioactive

constituent(s) and pharmacological activity of various parts of the species to justify the

substitution of root and stem bark with other plant parts in order to make the use of these

overexploited trees more tenable.


2.1 Plant material and sample preparation

Various plant parts (Bark, branches, twigs and leaves) of the species were collected from

their respective population from Lucknow (latitude 26.50N and longitude 80.50E).

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2.2 HPLC analysis

HPLC analysis was performed according to the respective methods for each species as

described in chapter 3 to quantify all the biomarkers present in each plant i.e. rutin

apigenin, luteolin and quercetin in B.variegata, oroxylin A, chrysin, baicalein, and

hispidulin in O. indicum, conessine in H. pubescence and arjunic acid in T. arjuna.

2.3 Pharmacological potential

2.3.1 Bauhinia variegata and Oroxylum indicum (anti-inflammation)

Animals

Healthy male Charles Foster (CF) rats, 4–6 weeks old, 150–175g (6 rats/group), were

used for the study. All animals were kept in pathogen free condition, fed with standard

laboratory diet and tap water throughout the experiments. Laboratory temperature was 24

± 1oC and relative humidity was 50–70%. Rats were divided into control and treated

groups. Animal experiments were carried out as per the approved protocol (AH-2012-05)

by the Institutional Animal Ethics Committee (IAEC) followed by the Committee for the

Purpose of Control and Supervision of Experimental Animals (CPCSEA), Government of

India (Registration No: 400/01/AB/CPCSEA).

Carrageenan-induced paw oedema in rats

The anti-inflammatory activity was performed according to the protocol of Winter et al.

(1962). CF rats (6 rats /group) were injected a 100 μl saline containing 1% w/v

carrageenan as a phlogistic agent into the sub plantar injection of the left hind footpad to

initiate an acute inflammation. Vehicle treated group of rats received the same volume of

vehicle at the same time. Paw volumes were determined using an animal plethysmometer

(Ugo Basil, Italy). Before injecting carrageenan, the volume of each left footpad was

measured and the reading of the footpad swelling after injection was carried out at 3hr.

To test the effect of various plant part extracts, the rats were orally treated with the

compounds (100 mg/kg) one hour prior to the injection of carrageenan. Rats treated with

Indomethacin (15mg/kg) serve as positive control. Increase in paw volume was

calculated as the difference between the paw volume reading before and 3 hr after the

184

injection of carrageenan and the percentage inhibition of oedema was calculated as

follow:

Percent inhibition of the percentage edema= (Vc− Vt)/Vc x 100

Where, Vc = Increase in Paw Volume (ml) in vehicle treated rats

Vt = Increase in Paw Volume (ml) in extract treated rats

2.3.2 Holarrhena pubescens (Antibacterial assay)

The antibacterial activity of all the extracts was determined against eleven strains of

pathogenic bacteria by disc diffusion assay (DDA) and furthermore by micro broth

dilution method (MIC) to find out the sensitivity of the bacterial strains. The activity was

analyzed using strains procured as microbial type culture collections (MTCC) from the

Institute of Microbial Technology, Chandigarh, India. The bacterial strains used were

Streptococcus mutans (MTCC497), Micrococcus luteus (MTCC 2470), Bacillus subtilis

(MTCC121), Klebsiella pneumoniae (MTCC109), Pseudomonas aeruginosa (MTCC

741), Streptococcus aureus (MTCC 96), Escherichia coli (MTCC 723), Streptococcus

epidermidis (MTCC 435) and Salmonella typhi (MTCC 733).

Antibacterial activity of H. pubescens was determined by Micro dilution broth assay

using 96 „U‟ bottom micro-titer plates as per CLSI guidelines (2006). The extracts were

serially diluted two folds (1000-7.8125 µg/mL) in Muellar Hinton Broth (MHB). The

broth was inoculated with 10.0 µL of diluted 24h grown culture of test organism with a

titre equivalent to 0.5 McFarland standards. The inoculated plates were then incubated at

37ºC for 16-24h and the growth was recorded spectrophotometrically at 600 nm using

spectramax 190-microplate reader (Molecular Devices, CA, and USA). The MIC value

was determined from the turbidimetric data as the lowest concentration of extracts

showing growth inhibition equal to or greater than 80% as compared to control. The

Minimum Bactericidal Concentration (MBC) was detected from the turbidimetric data as

the lowest concentration of extract where 99% of killing was observed. Experimental

observations were performed in triplicate to rule out any error during the procedure.

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2.3.3 Terminalia arjuna (Hypolipidemia)

Animals

Animal study was performed with the approval of Animal Care Committee of Division of

Laboratory Animals; Central Drug Research Institute, Lucknow, India and confirmed to

the guide for the Care and Use of Laboratory Animals (CDRI, Lucknow). Male adult rats

of Charle Foster strain (200–225 g) bred in the animal house of the Institute were used.

A group of six animals in a cage were kept in controlled conditions, temperature 25–

260C, relative humidity 60–80% and 12/12 h light/dark cycle (light from 08:00 a.m. to

08:00 p.m.) and provided with standard pellet diet (Lipton India, Ltd) and water ad

libitum.

In-vivo hypolipidemic activity

Hypolipidemic activity of different plant parts of T. arjuna was tested in vivo against

Triton treated hyperlipemic rats. Hyperlipidemia in rats was induced by a single injection

of triton WR-1339 (400 mg/kg body weight). Triton was diluted with normal saline and

injected to each rat intraperitoneally. The extracts as well as gemfibrozil were macerated

with 2% aqueous gum acacia and fed orally at dose of 50 mg/kg and 100 mg/kg body

weight simultaneously with triton. The effect was observed in the percent decrease in the

total cholesterol, phospholipids and triglycerides of serum lipid. Total cholesterol (TC),

phospholipids (PL) and triglyceride (TG) were determined according to the methods

reported earlier (Rizvi et al., 2003)

2.4 In-vitro cytotoxicity assay

Effect of extracts on cell cytotoxicity was carried out in peritoneal macrophage cells

using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium) (Sigma–Aldrich,

India) assay as per described by Sharma et al., 2012. Peritoneal macrophage cells (0.5 x

106 cells/well ) isolated from mice were suspended in RPMI 1640 medium (Sigma, USA)

containing 10% heat-inactivated fetal bovine serum (Gibco, USA) and incubated in a

culture 96 well plate at 37ºC in 5% CO2 in an incubator and left overnight to attach. Cells

treated with 1% DMSO served as a vehicle control for cell cytotoxicity study. Cells were

186

treated (100 µg/ml) and incubated for 24 h at 37ºC in 5% CO2. After incubating cells

with treatment, 20 μl aliquots of MTT solution (5mg/ml in PBS) were added to each well

and left for 4 hours .Then, the MTT containing medium was carefully removed and the

cells were solubilised in DMSO (100µl) for 10 minutes. The culture plate was placed on

a micro-plate reader (Spectramax; Molecular Devices, USA) and the absorbance was

measured at 550 nm. The amount of color produced is directly proportional to the number

of viable cells. Cell cytotoxicity was calculated as the percentage of MTT absorption as

follows: Percentage (%) of survival = (mean experimental absorbance/mean control

absorbance×100).

2.5. Statistical analysis

The data were expressed as mean, SD and statistically assessed by one analysis of

variance (ANOVA). The difference between drug treated groups and control group was

evaluated by Tukey-Kramer Multiple Comparisons Test. p<0.05 was considered

significant.

3. Results

3.1 Bauhinia variegata

3.1.1 Chemical analysis

The chemical composition of different parts of B.variegata and their alcoholic, hydro

alcoholic and aqueous extracts were analyzed quantitatively for three important

biomarkers viz. quercetin, luteolin and apigenin by High Performance Liquid

Chromatography (HPLC). Their percent content in various extracts of all the plant parts

are summarized in Table 6.1.

The results revealed that these biologically active flavonoids are considerably present in

all the plant parts. The solvent medium played a significant role in extracting the

biomarkers reasonably. It was observed that quercetin and luteolin was extracted in

higher quantities in alcoholic extract whereas, apigenin was predominantly extracted in

aqueous medium and also constituted the major portion of the components. Apigenin was

found to be highest in aqueous extract of stem bark (0.0411%) which was followed by

187

insignificantly different aqueous extracts of branch (0.0372%) and twigs (0.0375%).

Leaves (0.0018%) contained least amount of this biomarker. Interestingly, the pattern

was reversed in the case of luteolin, which was dominant in alcoholic extract of leaves

followed by twigs, branches and stem bark. This may be due to the alcohol solubility of

luteolin which is naturally found more leaves. The content of the compound in alcoholic

extract of leaves was 0.0095% followed by twigs (0.0081%), branches (0.0052%) and

stem bark (0.0051%). In the case of quercetin, alcohol was found to be the suitable

medium of extraction for the flavonoidal glycoside which was again present

predominantly in woody parts rather than leaves. The highest content was observed in

alcoholic extract of stem bark (0.0059%). Whereas, alcoholic extract of branch and twig

contained approximately same amount of the flavonoid (0.0045% and 0.0042%)

respectively. Rutin was the compound which was negligent in comparison with other

biomarkers and was almost equally soluble in the entire three solvent medium. It was

predominantly present in leaves followed by twig, branch and stem. The total quantity of

biomarkers was found to be highest in aqueous extracts of stem bark and twigs followed

by same extract of branch. Altogether, solvent selection had much influence on extraction

of major compounds and there was a methodical fashion of dominance of flavonoid

biomarkers in various parts of the plant.

3.1.2 In-vivo anti-inflammatory activity

Footpad of rats became oedematous soon after carrageenan injection. Administration of

100 mg/kg of extract and 15 mg/kg of Indomethacin (reference drug) significantly

inhibited the development of swelling over time after carrageenan infection (Fig. 6.1).

Present investigation revealed that the aqueous extracts of plant parts effectively

repressed the progression of oedema and showed most potent anti-inflammatory effects

followed by hydro alcoholic and alcoholic extracts. The maximum inhibitory activity was

observed in aqueous extracts of stem bark (54.251%, p<0.001) and twigs (52.634%,

p<0.001). Aqueous extract of branch also exhibited significant potential against oedema

(41.7642%, p<0.01), but the same extract of leaves lacked the specific potential.

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In case of hydro alcoholic extract, twigs demonstrated the most significant effects

(40.542%, p<0.01) followed by stem bark (39.110%, p<0.01) and branch (35.585%,

p<0.05). Hydro alcoholic extract of leaves manifested negligible activity, while alcoholic

extract of same showed reasonable inhibition on carrageenan induced paw oedema. But,

overall potential of alcoholic extracts of plant parts were very low in comparison to that

of other two extracts.

Comprehensively, all the plant parts except leaves possess significant anti inflammatory

activity and potency of twig were very much equal to that of stem bark which is the

traditionally used plant part. It is also evident that water is least toxic medium for

extraction and in this case, aqueous extracts have shown higher potential than alcoholic

and hydro alcoholic extracts. Thus, the use of same could be much safer in terms of

administration of drug.

3.1.3 Cytotoxicity

The significant change in live cell population (%) was not observed (p<0.05) in cells

incubated with B.variegata extracts (100 µg/mL) in comparison with the vehicle control.

The viability of cells was not affected in the presence of the samples studied, thus,

showing that B.variegata extracts were not toxic to immune cells (Table 6.7).

3.2 Oroxylum indicum


The chemical composition of different parts of O. indicum and their various types of

extracts were analyzed quantitatively for four important biomarker compounds viz.

oroxylin A, chrysin, baicalein, and hispidulin by High Performance Liquid

Chromatography (HPLC). The percent content (dry weight basis) in various extracts viz.

alcoholic, hydro alcoholic and aqueous extracts of all the plant parts are summarized in

Table 6.2.

The results revealed that these biologically active major flavonoids are relatively present

in all the plant parts, thus making a comparable compound pattern in each matrix. The

medium of extraction played a significant role in extracting the biomarkers reasonably. It

189

was observed that the two major flavonoids, chrysin and baicalein, were extracted in

higher quantities in alcoholic medium. Antithetically, oroxylin A was pre-eminently

extracted in water while, hispidulin was found to be partially soluble in both aqueous and

alcoholic media. Chrysin constituted the highest percentage of all the other flavonoids

and the content was found to be highest in alcoholic extract of twig (0.3417 %).

Alcoholic extract of branch and root bark also contained generous content of this

bioactive marker which was 0.4813% and 0.3142 %, respectively. The other two

extracting media i.e. hydro-alcoholic and aqueous media were not so effective in

extracting the particular compound, regardless the plant parts. Aqueous extract of leaves

(0.0091%) contained the least amount of the biomarker, whereas, the compound was

present in moderate quantities in alcoholic extract of stem bark (0.2776%). The pattern of

extraction of baicalein was exactly similar to that of chrysin. This may be due to the

structural similarities and common moieties present in both the compounds. The highest

content of the compound was present in alcoholic extract of twig (0.2131%) followed by

same extract of branch (0.1254%), root bark (0.0996%) and stem bark (0.079%). Leaves

consisted negligible amount of the compound as compared to other plant parts.

Interestingly, the pattern was reversed in case of oroxylin A where aqueous extract was

found to be most potent to extract this flavonoid and it was predominantly present in root

and stem bark. The aqueous extract of these parts constituted 0.0861% and 0.0842 % of

the compound, correspondingly, contrary to that of branch, twig and leaves which were

found deficient of this flavonoid. Hispidulin was the only compound which was present

moderately in each type of extract due to its extensive solubility. Although, higher

content of the compound was observed in aqueous extract of root bark (0.1321%) and

stem bark (0.1408%) but, branch, twig and leaves also contained decent amount of this

compound. Conclusively, solvent selection had much influence on extraction of major

compounds and there was a methodical fashion of dominance of flavonoid biomarkers in

various parts of the plant.

190

3.2.2 In-vivo anti-inflammatory activity

Footpad of rats became oedematous soon after carrageenan injection. Administration of

100 mg/kg of extract and 15 mg/kg Indomethacin (reference drug) significantly inhibited

the development of swelling over time after carrageenan injection as shown in fig. 6.2.

Present investigation revealed that the alcoholic extract of plant parts effectively

repressed the progression of oedema and demonstrated most potent anti-inflammatory

effects followed by hydro-alcoholic and aqueous extracts. The maximum inhibitory

activity was observed in alcoholic extract of twigs (46.712%, p<0.001) and branches

(41.314 %, p<0.001). Root bark (26.884%, p<0.01) and stem bark (24.417%, p<0.01),

also exhibited significant potential against oedema but the same extract of leaves lacked

the specific activity. Among hydro-alcoholic extracts, twigs (38.615%, p<0.001)

demonstrated most significant effects followed by branch (34.094%, p<0.001). However,

their extent of activity was comparatively lower than that of alcoholic extracts of the two.

Root bark (31.421%, p<0.01) and stem bark (29.934%, p<0.01) established

insignificantly different effects in terms of suppression of oedema but the effects were

moderately higher than that of their alcoholic extracts.

Aqueous extracts of root and stem bark showed improved activity with inhibition of

37.712% (p<0.001) and 36.558% (p<0.001), respectively. However, branch and twigs

had continuous declining effects in their potential. Comprehensively, all the plant parts

except leaves i.e. root bark stem bark, branch and twig possess significant anti

inflammatory activity and potency of twig and branch were equal or higher to that of root

bark which is the traditionally used part of the plant.

3.2.3 Cytotoxicity

The significant change in live cell population (%) was not observed (p< 0.05) in cells

incubated with O. indicum extracts (100 µg/mL) in comparison with the vehicle control.


showing that O. indicum extracts were not toxic to immune cells (Table 6.8).

191

3.3 Holarrhena pubescens


The chemical composition of different plant parts of H. pubescens in three types of

extracts were analyzed quantitatively for the most active secondary metabolite of the

plant i.e. conessine by HPLC (Table 6.3). The traditionally used part of the plant is stem

bark but chemical investigation revealed that the biomarker was present more or less in

all the parts of plant viz. stem bark, branches, twigs and leaves, thus making an analogous

compound pattern in each matrix.

When compared on the basis of medium of extraction, it was found that the alcoholic

extract of plant parts contained higher percentage of conessine unlike aqueous and hydro-

alcoholic extracts. It was interesting to note that extracts of branch and twig also

possessed higher content of marker component compared to that of stem bark whereas,

leaves hardly contained the compound. Conessine content was found maximum in

alcoholic extract of stem (1.0644%) which was comparable to that of branch (1.0436%)

followed by twig (0.8245%). It was ineffectual to extract the alkaloid in other medium as

the highest content of the conessine from hydro alcoholic or aqueous extracts were limit

to 0.0389% and 0.004% respectively. Altogether, there was a methodical fashion of

dominance of marker compounds in various parts and solvent selection much influenced

the content of compound extracted.

3.3.2 Anti-bacterial activity

Significant anti-bacterial activity was found for extracts against a wide range of bacteria,

regardless of the plant parts tested (Table 6.5). Greater and remarkable activity was

observed by alcoholic extract than the corresponding hydro-alcoholic and aqueous

extracts. The extracts of bark and branches exhibited almost similar inhibition of bacterial

growth. The MIC for most of the strains like B. subtilis (125 μg/ml), P. aeruginosa (62.5

μg/ml), E. coli (31.25 μg/ml) and S. typhi (250 μg/ml) were equal in stem bark and

branch extracts. Moreover, in M. luteus the MIC exhibited by branch extract (15.62

μg/ml) was lower than that of bark extract (31.25 μg/ml). Alcoholic extract of twig also

possessed significant activity and was found to be more active than other parts for P.

192

aeruginosa with MIC 31.25 μg/ml. Leaf extracts, irrespective of the solvent used showed

insignificant activity against bacterial strains. Overall, all the parts of plant except leaves

provides significant anti bacterial activity.

3.3.3 Cytotoxicity


showing that H. pubescens extracts were not toxic to immune cells (Table 6.9).

3.4 Terminalia arjuna


The chemical composition of different plant parts of T.arjuna in hydro-alcoholic extract

was analyzed quantitatively for the most active secondary metabolite of the plant i.e.

arjunic acid by HPLC (Table 6.4). It was noted that the marker compound was present

luxuriously only in the traditionally used part of the plant i.e. stem bark and

comparatively lower in quantities in the other parts of plant viz. stem bark, branches,

twigs and leaves. Additionally, all the extracts consisted of almost equal quantity of the

biologically active constituent. Stem bark (0.5128%) consisted of highest amount of

arjunic acid followed by branch bark (0.0263%), twig bark (0.0018%). However, the

compound was absent in leaves.

3.4.2 In-vivo hypolipidemic activity

Hypolipidemic activity of different plant parts of T. arjuna was tested in vivo against

Triton treated hyperlipemic rats. The effect was observed in the percent decrease in the

total cholesterol, phospholipids and triglycerides of serum lipid as evident in Table 6.6.

The effects of these extracts were compared with the standard drug „Gemfibrozil‟. The

study showed that extracts of all plant parts of T. arjuna have some degree of total

cholesterol, phspho-lipid and triglycerides lowering activity but the best activity was

observed in the trunk bark followed by twig bark, branch bark and leaves at 100mg/ kg

dose. In total cholesterol lowering activity, after trunk bark, branch bark exhibited better

activity than the twig bark and leaves. However, in phospholipids and triglycerides

lowering activity, after trunk bark, twig bark exhibited better activity than the branch

193

bark. Although leaves exhibited phospholipids lowering activity lower than the twig

barks but its activity was comparable to branch bark. However, the activity of leaves in

lowering triglycerides was better than even branch bark and comparable to that of twig

bark.

3.4.3 Cytotoxicity

There was an insignificant change in live cell population in cells incubated with T. arjuna

extracts (100 µg/ml). The viability of cells was not affected in the presence of the

samples studied (Table 6.10).

4. Discussion

In India, stem bark of B. variegata, H. pubescens, T.arjuna and root bark of O. indicum

are legitimately considered to be the plant part used in medicinal preparations (Almeida

et al. 2006; Kirtikar and Basu, 1999; Rao et al., 2008; Yadava and Reddy, 2003; Doshi et

al., 2012; Maitreyi and Sunita, 2010; Laupattarakasem et al., 2003; Warrier et al., 1996),

thus resulting in overharvesting of the crucial part which is subsequently leading to the

population abatement of these valuable indigenous plant species. The purpose of this

study was to attain a solution to this predicament through bioequivalence by examining

the impact of plant part substitution in order to promote the sustainable management of

the botanicals.

The four biomarkers used for qualitative and quantitative analysis between plant parts of

B. variegata were rutin, quercetin, luteolin and apigenin. The foremost reason for

selection of these biomarkers was their direct relation with the anti-inflammatory

potential of the plant. All the three compounds are known to possess potential anti-

inflammatory activity (Ueda et al., 2002; Seelinger et al., 2008; Ziyan et al., 2007) and it

is well established that due to the presence of these bioactive compounds, the plant is

used for anti-inflammatory purposes. It was interesting to note that these active principles

were present in all plant parts, though there were some quantitative variances between

different plant parts. From the present outcome it is possible to infer that aqueous

medium significantly extracted the major flavonoid, apigenin and this may be attributed

to the hydrophilic nature of the compound. Contrarily, quercetin and luteolin being

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hydrophobic in nature (Fang et al., 2011) were found better extracted in alcoholic

medium. The HPLC analysis showed high degrees of similarities in chemical profile of

various parts. Interestingly, these bioactive compounds responsible for anti inflammatory

activity were found generously in non-traditionally used plant parts like twigs and

branches. It makes the result more critical in suggesting the practitioners to substitute the

vital parts of plant with other non destructive parts. Nevertheless, phytochemical

investigation cannot replace pharmacological investigation as latter determines the

medicinal value of the plant (Zschoke et al., 2000). Thus, the extracts were further

investigated for the presence of anti inflammatory activity to substantiate the same. In-

vivo anti inflammatory activity supported the chemical analysis and revealed that, the

aqueous extract of twig and branch exhibited pronounced inhibitory effects which were

comparable to that of stem bark. The pattern of bioactive flavonoids dominance could be

attributed as a reason behind it. In all inclusive manners, the chemical and

pharmacological investigations could further be interrelated as the extract which

constituted higher amount of apigenin and total flavonoids, possessed higher degree of

activity which may be due to their aggrandized potential for anti inflammatory action.

Although, all the biomarkers were present in leaves too, but insignificant anti

inflammatory activity was observed.

An analogous chemical profile of various plant parts of O. indicum strongly suggests that

crucial parts of the plant like root and stem bark could be substituted with other parts of

the same plant. Again, the reason for selection of the four biomarkers was related with

their effectiveness as anti-inflammatory agents. Chrysin, baicalein, oroxylin A and

hispidulin are known to possess potential anti-inflammatory activity (Gautam and Jachak,

2009; Hong et al., 2002; Kavimani et al., 2000; Kim et al., 2008; Lin and Shieh, 1996; Li

et al., 2012; Mueller et al., 2010; Song et al., 2012; Woo et al., 2005) and it is well

established that due to the presence of these bioactive compounds, the plant is used for

anti-inflammatory purposes. Present investigation revealed that the four active principles

were present in all plant parts but in different concentrations and solvent selection played

a vital role in extracting the biomarkers effectively. From the present outcome it is

possible to infer that alcoholic medium significantly extracted the two major flavonoids,

chrysin and baicalein and this may be attributed to the lipophilic nature of the compounds

195

due to which they are hardly soluble in aqueous medium (Ping et al., 2009; Kim et al.,

2008). Contrarily, oroxylin A, being hydrophilic in nature (Peña et al., 2013) was found

better extracted in aqueous medium. The result reinforces the theory of Cordell (2005)

that sustainability, with respect to use of solvent for extraction is important future

criterion for success of ethnopharmacology.

In-vivo anti inflammatory activity supported the chemical analysis and revealed that, the

aqueous extract of twig and branch exhibited higher inhibitory activity than root and stem

bark. The plausible reason behind the superior activity could be the presence of the two

major flavonoids (chrysin and baicalein) in higher quantities which are responsible for

the activity. Though, it was a clear observation that aqueous extract of root bark and stem

bark possessed improved activity in comparison to their alcoholic extract and aqueous

extracts of twig and branch. The pattern of bioactive flavonoid dominance could be

attributed as a reason behind the same. It was noticeable that aqueous extracts of root and

stem bark constituted, oroxylin A and hispidulin profusely, thus making their matrix

more robust. But in all inclusive manners, the chemical and pharmacological

investigations could further be interrelated as the extract which constituted higher amount

of chrysin and baicalein possessed higher degree of activity which may be due to their

aggrandized potential for anti inflammatory action. Although, all the biomarkers were

present in leaves too, but insignificant anti inflammatory activity was observed thus,

suggesting, that random selection of plant parts without any prior validation should be

discouraged in order to avoid resource waste. Furthermore, the results of toxicity analysis

revealed that all the plant parts are non toxic to immune cells and hence they are safe for

administration as drug.

According to the obtained results, it could be suggested that twig and branch could be

used in place of root bark and stem bark, leading to less detrimental effects on plant and

ultimately conserving this endangered plant species.

Comparison of extracts from different parts of H. pubescens for biomarker alkaloid

„conessine‟ revealed that the pharmacologically active compound was present in all the

parts of plant except leaves and alcohol was the best solvent to extract higher percentage

of the compound. Furthermore, there were high degrees of similarity between the content

196

of the compound in stem bark and branches followed by twigs. Thus, chemically,

branches and twigs can substitute stem bark. Anti-bacterial activity supported the

chemical analysis and revealed that, extracts of branch and twigs also possessed

equivalent degree of activity. It was interesting to note that the extracts containing higher

amount of marker alkaloid, exhibited potent antibacterial activity suggesting a causative

relationship between conessine and its antibacterial property. This may be due to the

formation of pores in the cell walls and the leakage of cytoplasmic constituents by this

active compound (Gnanamani et al., 2003). Although, the biomarker was present in

leaves too but insignificant activity was observed thus, suggesting, that random selection

of plant parts without any prior validation should be discouraged.

However, in T. arjuna, the traditionally used plant part i.e. stem bark was the only part

which possessed the highest content of the biologically active compound „arjunic acid‟.

In other parts, the content of the compound was found relatively low as compared to the

stem bark. The pharmacological activity possessed by alternative plant parts was too, non

comparable to the traditionally used part of the tree. Furthermore, the results of toxicity

analysis revealed that all the plant parts are non toxic to immune cells and hence they are

safe for administration as drug.

Our study concludes that, the use of vital part of plant like bark could be replaced with

plant parts which are less destructive to harvest, in the species where the extracts of both,

traditionally used part and substituted parts show equivalent pharmacological potency. It

implements the concept of bio- equivalency for conservation and in this way,

conservation and use of the species can be combined. These kinds of innovative

conservation strategies broaden the remit of ecology. In our outlook, complete

investigations like this may protect more tree species from extinction. However, policies

should be made for these promising methods for conservation and particularly enforced

for better regulation of the utilization of the botanical resources.

197

Table 6.1. Percent content of marker components in different plant parts and extracts of Bauhinia variegata

% content (w/w)#

Plant Parts Extracts Rutin Quercetin Luteolin Apigenin

Stem bark

AL 0.00513 ± 0.000053 0.00059 ± 0.000052 0.00513 ± 0.000053 0.00749 ± 0.000026

HA 0.00513 ± 0.000053 0.00028 ± 0.000029 0.00128 ± 0.000039 0.01628 ± 0.000044

AQ 0.00513 ± 0.000053 - 0.00043 ± 0.000051 0.04117 ± 0.000049

Branches

AL 0.00513 ± 0.000053 0.00045 ± 0.000048 0.00528 ± 0.000064 0.00421 ± 0.000052

HA 0.00513 ± 0.000053 0.00021 ± 0.000027 0.00242 ± 0.000048 0.01574 ± 0.000038

AQ 0.00513 ± 0.000053 - 0.00048 ± 0.000046 0.03725 ± 0.000056

Twigs

AL 0.00513 ± 0.000053 0.00042 ± 0.000014 0.00814 ± 0.000063 0.00417 ± 0.000063

HA 0.00513 ± 0.000053 0.00009 ± 0.000025 0.00297 ± 0.000059 0.01549 ± 0.000039

AQ 0.00513 ± 0.000053 - 0.00085 ± 0.000047 0.03757 ± 0.000063

Leaves

AL 0.00513 ± 0.000053 0.00017 ± 0.000016 0.00951 ± 0.000055 0.00022 ± 0.000021

HA 0.00513 ± 0.000053 - 0.00509 ± 0.000039 0.00074 ± 0.000034

AQ 0.00513 ± 0.000053 - 0.00093 ± 0.000057 0.00184 ± 0.000067

AL=Alcoholic extract, HA=Hydro alcoholic extract, AQ=Aqueous extract; #on plant dry weight basis

198

Table 6.2. Percent content of marker components in different plant parts and extracts of O. indicum

% content (w/w)#

Plant Parts Extracts Chrysin Baicalin Oroxylin A Hispidulin

Root bark

AL 0.3142 ± 0.00062 0.0996 ± 0.00053 0.0328 ± 0.00031 0.1126 ± 0.00055

HA 0.2418 ± 0.00068 0.0759 ± 0.00061 0.0571± 0.00035 0.1315 ± 0.00059

AQ 0.1086 ± 0.00058 0.0427 ± 0.00058 0.0861± 0.00029 0.1321 ± 0.00062

Stem bark

AL 0.2776 ± 0.00054 0.0791 ± 0.00041 0.0219 ± 0.00042 0.1241 ± 0.00047

HA 0.1008 ± 0.00059 0.0581 ± 0.00043 0.0673 ± 0.00053 0.1342 ± 0.00043

AQ 0.0891 ± 0.00061 0.0326 ± 0.00052 0.0842 ± 0.00045 0.1408 ± 0.00051

Branches

AL 0.4813 ± 0.00035 0.1254 ± 0.00068 0.0049 ± 0.00031 0.0842 ± 0.00034

HA 0.2861 ± 0.00039 0.0984 ± 0.00061 0.0104 ± 0.00032 0.0996 ± 0.00029

AQ 0.1142 ± 0.000.26 0.0421 ± 0.00057 0.0273 ± 0.00039 0.1146 ± 0.00031

Twigs

AL 0.5485 ± 0.00059 0.2131 ± 0.00059 0.0024 ± 0.00028 0.0609 ± 0.00048

HA 0.3417 ± 0.00048 0.1351 ± 0.00054 0.00850 ± 0.00021 0.0821 ± 0.00041

AQ 0.2076 ± 0.00051 0.0762 ± 0.00063 0.0108 ± 0.00026 0.0943 ± 0.00039

Leaves

AL 0.1152 ± .00026 0.0078 ± 0.00029 - 0.0032 ± 0.00020

HA 0.0746 ± 0.00021 0.0045 ± 0.00031 0.0009 ± 0.00013 0.0047 ± 0.00019

AQ 0.0091 ± 0.00017 0.0029 ± 0.00024 0.0046 ± 0.00016 0.0059 ± 0.00024

AL=Alcoholic extract, HA=Hydro alcoholic extract, AQ=Aqueous extract, #on plant dry weight basis, ±=standard deviation

199

Table 6.3. Percent content of conessine in different extracts and plant parts of H. pubescens

Plant parts % content (w/w)

a

Alcoholic

extract

Hydro-alcoholic

extract

Aqueous extract

Stem bark 1.0644 ± 0.0071 0.0389 ± 0.0057 0.0040 ± 0.0002

Branch 1.0436 ± 0.0075 0.0321 ± 0.0021 0.0034 ± 0.0003

Twig 0.8245 ± 0.0453 0.0292 ± 0.0006 0.0015 ± 0.0003

Leaves 0.1259 ± 0.0495 0.0051 ± 0.0012 0.0033 ± 0.0041 # on plant dry weight basis

Table 6.4. Percent content of arjunic acid in different extracts and plant parts of T. arjuna

Plant parts % content (w/w)

#

Alcoholic

extract

Hydro-alcoholic

extract

Aqueous

extract

Stem bark 0.5128 ± 0.0003 0.5095 ± 0.0004 0.4842 ± 0.0002

Branch 0.0256 ± 0.0006 0.0263 ± 0.0003 0.0217 ± 0.0005

Twig 0.0014 ± 0.0001 0.0018 ± 0.0005 0.0013 ± 0.0003

Leaves 0.0001 ± 0.0000 0.0002 ± 0.0001 0.0001 ± 0.0000 # on plant dry weight basis

200

Table 6.5. Growth inhibitory activity of various extracts and plant parts of H. pubescens against some bacterial strains

Extracts Plant parts SM 497 ML 2470 BS 121 KP 109 PA 741 SA 96 EC 723 SE 435 ST 733

MIC#(MBC)

Alcoholic

extract

Stem bark 250 (250) 31.2(62.5) 125 (125) 125

(500)

62.5 (125) 500

(>1000)

31.25 (62.5) 62.5 (125) 250 (500)

Branch 500(>1000) 15.62 (62.5) 125 (25) - 62.5 (125) - 31.25 (62.5) 125 (250) 250 (500)

Twig - 62.5(125) 62.5

(125)

- 31.25 (62.5) 500

(>1000)

62.5 (125) 125 (125) 250 (500)

Leaves - - - - 250 (500) - 250 (500) 500 (>1000) 500 (>1000)

Hydro-

alcoholic

extract

Stem bark 250 (500) 125 (125) 250 (500) 250

(500)

250 (500) - 125 (250) 125 (250) -

Branch 500(>1000) 62.5 (125) 250 (500) - 125 (125) - 125 (500) 500 (>1000) -

Twig - 250 (500) 125 (125) - 125 (250) - 500 (>1000) 250 (500) -

Leaves - - - - 500 (>1000) - - 500 (>1000) --

Aqueous

extract

Stem bark - 250 (500) 500

(>1000)

- - - 500 (>1000) 250 (>1000) -

Branch - 250 (500) 500

(>1000)

- - - 500 (>1000) 500 (>1000) -

Twig - - 250 (500) - 500 (>1000) - 500 (>1000) - -

Leaves - - - - 500 (>1000) - - - -

values in μg/ml, MIC: Minimum Inhibitory Concentration, MBC: Minimum bactericidal Concentration, SM 497: Streptococcus mutans , ML 2470: Micrococcus luteus, BS 121: Bacillus subtilis, KP

109: Klebsiella pneumoniae, PA 741: Pseudomonas aeruginosa, SA 96: Streptococcus aureus, EC 723: Escherichia coli, SE 435: Streptococcus epidermidis, ST 733: Salmonella typhi.

201

Table 6.6. Hypolipidemic activity of different plant parts of Terminalia arjuna.

Plant parts Dose (mg/kg) % Decrease of serum lipid

Total

Cholesterol

Phospho lipid Triglycerides

Leaf

50

100

9

16

13

17

11

21

Twig bark

50

100

9

17

10

19

17

21

Branch bark

50

100

11

20

8

17

7

18

Trunk bark

50

100

15

26

11

23

12

27

Gemfibrozil* 100 33 34 32

*Standard drug

Table 6.7. Effect of different plant parts and their corresponding extracts of Bauhinia variegata on

% Cell Viability using MTT assay in macrophage cells

Plant parts % Cell viability (mean ± SEM )

Alcoholic extract Hydro alcoholic extract Aqueous extract

Stem bark 99.29 ± 3.82 96.29 ± 3.88 95.36 ± 2.15

Branch 99.45 ± 5.85 97.12 ± 2.05 98.98 ± 3.67

Twig 99.23 ± 2.99 98.09 ± 4.65 95.44 ± 5.12

Leaves 93.71 ± 4.04 94.97 ± 2.67 98.44 ± 2.14

Table 6.8. Effect of different plant parts and their corresponding extracts of Oroxylum indicum on %

Cell Viability



Root bark 95.95 ± 2.99 97.69 ± 3.06 99.23 ± 2.99

Stem bark 102.29 ± 6.82 96.29 ± 3.88 103.71 ± 4.04

Branch 98.09 ± 4.65 95.12 ± 2.08 98.98 ± 3.67

Twig 97.86 ± 8.82 99.45 ± 5.85 100.44 ± 7.12

Leaves 95.36 ± 2.15 96.97 ± 2.67 98.44 ± 2.14

202

Table 6.9. Effect of different plant parts and their corresponding extracts of Holarrhena pubescens

on % Cell Viability



Stem bark 100.71± 5.82 94.49 ± 3.88 93.42 ± 6.04

Branch 97.65 ± 4.65 97.11 ± 2.08 97.98 ± 3.67

Twig 96.32 ± 8.82 97.54 ± 6.85 96.48 ± 3.46

Leaves 94.34 ± 2.15 93.87 ± 3.67 97.64 ± 2.29

Table 6.10. Effect of the extracts of different plant parts of Terminalia arjuna on % Cell Viability

using MTT assay in macrophage cells


T. arjuna extract (Hydro-alcoholic)

Stem bark 97.36 ± 3.14

Branch 95.81 ± 4.67

Twig 93.49 ± 6.38

aves 97.15 ± 2.67

203

(A): Aqueous extract, (B): Hydro alcoholic extract, (C): Alcoholic extract,*:

p<0.05 (Vehicle control vs. treated groups) **: p<0.01 (Vehicle control vs. treated

groups) ***: p<0.001 (Vehicle control vs. treated groups)

Fig. 6.1. Anti-inflammatory profile of various plant parts of B.

variegata on carrageenan induced paw oedema model in rats.

C

B

A

204

.

(A): Alcoholic extract, (B): Hydro alcoholic extract, (C): Aqueous extract,*: p<0.05

(Vehicle control vs. treated groups) **: p<0.01 (Vehicle control vs. treated groups) ***:

p<0.001 (Vehicle control vs. treated groups)

Fig. 6.2. Anti-inflammatory profile of various plant parts of O.

indicum on carrageenan induced paw oedema model in rats.

A

B

C

CHAPTER 7

Effect of Phenology and Temporal Variation on

Bioactive Secondary Metabolite Concentration within Tree

Species

205

EFFECT OF PHENOLOGY AND TEMPORAL VARIATION ON BIOACTIVE

SECONDARY METABOLITE CONCENTRATION WITHIN

TREE SPECIES

1. Introduction

Higher plants produce a vast number of secondary metabolites, in addition to primary

metabolites, via complex pathways, which are regulated in highly sophisticated

manners (Yazaki 2004). These secondary metabolites have diverse chemical

structures and high intra specific variation (Hartmann 1996). Bioactive secondary

metabolites have been utilized as natural medicines. In most cases these bioactive

natural compounds are found in particular organs, which are called „„medicinal part‟‟

in pharmacognosy, and their contents in such organs are often seasonally regulated

(Rocha et al. 2005). Some secondary metabolites are known to function as mediators

necessary for the interaction with other organisms, as being allelopathic substances or

insect attractants to facilitate pollination (Hoballah et al., 2005). To achieve those

functions, accumulation or secretion of those compounds has to be highly regulated,

for instance, flavonoids acting as UV protectant are specifically accumulated in

epidermal cells (Schmitz and Weissenbock, 2003), and insect attractants are emitted

from flower petals. Biosynthetic genes responsible for the formation of those

secondary metabolites may be highly expressed in such tissues where the metabolites

are mainly accumulated, while translocation of natural compounds among plant

organs often occurs as well, e.g., biosynthetic genes for nicotine, a pyrrolidine

alkaloid of Nicotiana species, are mostly expressed in root tissues (source organ)

whereas it is transported to the aerial part and accumulated in leaves (Shoji et al.

2000).

Despite the existence of genetic control, gene expression and genotypes, the total

content and relative proportions of secondary metabolites in plants may vary over

time and space, so that they occur at different levels (Wallaart et al. 2000, Grace et al.

1998, Lopes et al. 1997, Darrow et al 1997). The amount of metabolites present in a

given plant may be influenced by biological and environmental factors (Harborne

1993) as well as biochemical, physiological, ecological, and evolutionary processes

(Darrow et al. 1997, Lindroth and Palutee, 1987). Seasonality, circadian rhythm, plant

development, temperature, altitude, water availability, UV radiation, nutrients,

206

pollution, mechanical stimuli, and attacks by herbivores or pathogens are also

considered to be the factors that most affect the occurrence of plant metabolites

(Holopainen et al. 2010, Morales et al. 2010, Betz et al. 2009). Plant phenology,

studying the seasonal timing of plant life cycle events (phenophases), is also one of

the most important factors which influence the secondary metabolite accumulation

and fluctuation. However, Most of the studies about the factors influencing secondary

metabolite concentration are restricted to a few commercially important species

mostly herbs and shrubs or oil yielding botanicals and little is known about secondary

metabolite accumulation and variation in tree species. But, due to the large size per se

of the trees, they could be excellent models for the investigation of many specific

problems in variation and translocation of secondary metabolites.

Additionally, an increasingly important challenge for future research is assuring

sustainability of production systems and forested ecosystems in the face of increased

demands for natural resources and human disturbance of forests and meeting this

challenge requires significant shifts in research approach (Kaufmann and Linder,

1996). Keeping these facts in mind, here we determine how major secondary

metabolite concentrations vary with time, phenology and within the parts of four

medicinally important tree species viz. Bauhina variegata, Oroxylum indicum,

Holarrhena pubescens and Terminalia arjuna whose phonological attributes are

previously reported. A more detailed understanding of the variation in secondary

metabolites, will not only add to the understandings of physiology of trees but also

could provide a suitable harvest period which could further lead to judicious

management of the natural resources.


2.1. Plant material

Stem bark, branch bark, twig and leaves were collected on 15th of every month from

ten trees each of Bauhinia variegata, Oroxylum indicum, Holarrhena pubescens and

Terminalia arjuna between March 2009 to February 2012 and were pooled according

to the plant parts of each tree. As soon as possible, the plant materials were oven dried

at 40°C, for 48 h and stored in a dry place, away from light and insect attack.

207

2.2. Secondary metabolites

Variation in the content of apigenin and luteolin were analysed for B. variegata,

chrysin and baicalein for O. indicum, conessine in case of H. pubescens and arjunic

acid in T. arjuna.

2.3. Preparation of standard solution

Stock solutions of apigenin, luteolin, chrysin, baicalein, conessine and arjunic acid (1

mg/ml) was prepared in methanol as a standard reference.

2.4. Chromatographic analysis (HPLC)

High performance liquid chromatography (HPLC) was used to quantify the

biologically active compounds of respective tree species according to the method

described in chapter 3.

3. Statistical analysis

The data were summarised as Mean ± SD. Groups were compared repeated measures

two factor (groups and periods) analysis of variance (ANOVA) and the significance

of mean difference within and between the groups (plant parts) was done by

Bonferroni test for after adjusting for multiple contrasts (comparisons). A two-sided

(α=2) p value less than 0.05 (p<0.05) was considered statistically significant.

4. Results

The present study determines the concentrations of six metabolites (Apigenin,

Luteolin Chrysin, Baicalein, Conessine and Arjunic acid) in four different plant parts

(stem, branch, twig and leaves) for twelve months (March to Feb) over a period of

three years (2009 to 2011). For each plant parts and months, the concentrations of all

metabolites were first checked for variations between the years (Fig. 7.1-Fig. 7.6). For

each plant parts and months, as the concentrations of metabolites showed similar trend

over the years, we merged and averaged the data over the years for each plant parts

and months. Thus, after excluding the effect of year, the final data consists of two

factors i.e. plant parts (groups) and months (periods) with factor „periods‟ as a

repeated measure. For each plant species, the comparison of their metabolite

concentrations within and between the plants parts are summarised below.

208

Apigenin- Stem

2009 2010 2011

Mar April May June Jul Aug Sep Oct Nov Dec Jan Feb

Months

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Mean w

ith 9

5 %

CI

Apigenin- Branch

2009 2010 2011


Months

0.032

0.034

0.036

0.038

0.040

0.042

0.044

0.046

0.048

0.050

0.052

0.054

0.056

Mean w

ith 9

5 %

CI

Apigenin- Twig

2009 2010 2011


Months

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

Mean w

ith 9

5 %

CI

Apigenin- Leaf

20092010 2011


Months

-0.002

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

Mean w

ith 9

5 %

CI

Fig. 7.1. Concentration (%) of apigenin in various plant parts of B. variegata over the periods of 12 months for 3 years.

209

Luteolin- Stem

2009 2010 2011


Months

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

Me

an

with

95

% C

I

Luteolin- Branch

2009 2010 2011


Months

0.0015

0.0020

0.0025

0.0030

0.0035

0.0040

0.0045

0.0050

0.0055

0.0060

0.0065

Me

an

with

95 %

CI

Luteolin- Twig

2009 2010 2011


Months

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

Me

an

with

95%

CI

Luteolin- Leaf

2009 2010 2011


Months

-0.002

0.000

0.002

0.004

0.006

0.008

0.010

0.012

Me

an

with

95 %

CI

Fig. 7.2. Concentration (%) of luteolin in various plant parts of B. variegata over the periods of 12 months for 3 years.

210

Chrysin- Stem

Year 2009 Year 2010 Year 2011


Months

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Me

an

with

95

% C

I

Chrysin- Branch

2009 2010 2011


Months

0.20

0.22

0.24

0.26

0.28

0.30

0.32

0.34

0.36

0.38

0.40

0.42

0.44

Mean w

ith 9

5 %

CI

Chrysin- Twig

2009 2010 2011


Months

0.1

0.2

0.3

0.4

0.5

0.6

Me

an

with 9

5 %

CI

Chrysin- Leaf

2009 2010 2011


Months

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Mean w

ith 9

5 %

CI

Fig. 7.3. Concentration (%) of chrysin in various plant parts of O. indicum over the periods of 12 months for 3 years.

211

Baicalein- Stem

2009 2010 2011


Months

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

0.22

Mean w

ith 9

5 %

CI

Baicalein- Branch

2009 2010 2011


Months

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

0.13

0.14

Mean w

ith 9

5 %

CI

Baicalein- Twig

2009 2010 2011


Months

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

0.22

0.24

0.26

Mean w

ith 9

5 %

CI

Baicalein- Leaf

2009 2010 2011


Months

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

Mean w

ith 9

5 %

CI

Fig. 7.4. Concentration (%) of baicalein in various plant parts of O. indicum over the periods of 12 months for 3 years.

212

Conessine- Stem

2009 2010 2011


Months

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

Me

an

with

95 %

CI

Conessine- Branch

2009 2010 2011


Months

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Mean w

ith 9

5 %

CI

Conessine- Twig

2009 2010 2011


Months

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Me

an

with 9

5 %

CI

Conessine- Leaf

2009 2010 2011


Months

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Me

an

with

95

% C

I

Fig. 7.5. Concentration (%) of conessine in various plant parts of H. pubescens over the periods of 12 months for 3 years.

213

Arjunic acid- Stem

2009 2010 2011


Months

0.2

0.3

0.4

0.5

0.6

0.7

Mean w

ith 9

5 %

CI

Arjunic acid- Branch

2009 2010 2011


Months

-0.01

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Mean w

ith 9

5 %

CI

Arjunic acid- Twig

2009 2010 2011


Months

-0.005

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

Me

an

with

95

% C

I

Arjunic acid- Leaf

2009 2010 2011


Months

-0.0005

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

Mean w

ith 9

5 %

CI

Fig. 7.6. Concentration (%) of arjunic acid in various plant parts of Terminalia arjuna over the periods of 12 months for 3 years.

214


4.1.1. Apigenin

The concentration of Apigenin in four plant plants of B. variegata over the twelve months

of periods are summarised graphically in Fig. 7.7. Fig. 7.7 showed that the concentration

of apigenin was differentially expressed among plant parts over the periods. From March

to June, the mean concentration of apigenin was highest in twig while least in leaves; and

from July to Jan, it was highest in stem and least in leaves; and in Dec it was highest

again in twig and least in leaves. Further, the concentration of it in leaves did not varied

much i.e. remain almost similar over the periods. Comparing the effect of plant parts

(groups) and periods (months) together on concentrations, ANOVA revealed significant

effect of both groups (F=15376.76, p<0.001) and periods (F=108.48, p<0.001) on

concentrations. Further, the interaction (groups x periods) effect of both on concentrations

was also found significant (F=692.71, p<0.001).

For each plant part, comparing the mean concentration of apigenin within the groups (i.e.

between periods), Bonferroni test revealed significantly (p<0.001) different

concentrations in stem between the periods except March and April, May and Feb, July

and Jan, Aug and Dec, and Oct and Nov. Similarly, in branch, the mean concentration of

apigenin also fluctuated significantly (p<0.01 or p<0.001) between the periods except

March vs. July/Jan/Feb, April and June, July and Feb, Aug vs. Nov/Dec/Jan/Feb, Sept

and Oct, Oct and Nov, Nov vs. Dec/Jan, Dec vs. Jan/Feb, and Jan and Feb. Further, in

twig, the mean concentration of apigenin also differed notably (p<0.01 or p<0.001)

between the periods except March and June, Aug vs. Dec/Jan, Sept vs. Oct/Nov/Dec, Oct

and Nov and, Dec and Jan. Moreover, the mean concentration of apigenin in leaves also

diverged extensively (p<0.05 or p<0.01 or p<0.001) between most of the periods except

March vs. April/Sept to Feb, April vs. Aug to Nov/Feb, May vs. June to Aug, July and

Aug, Aug and Sept, Sept vs. Oct to Dec/Feb, Oct vs. Nov to Feb, Nov vs. Dec to Feb,

Dec vs. Jan and Feb, and Jan and Feb. Similarly, for each month, comparing the mean

concentration of apigenin between the groups (plant parts), Bonferroni test revealed

significantly (p<0.001) different concentrations among plant parts at all periods except

between branch and twig from July to Sept.

215

Apigenin

Stem Branch Twig Leaves


Months

-0.01

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Mean w

ith 9

5%

CI

Fig. 7.7. Concentration of apigenin in various plant parts of B. variegata over the period

of 12 months.

216

4.1.2. Luteolin

The concentration of luteolin in four plant parts of B. variegata over the periods are

summarised graphically in Fig. 7.8. Results revealed that the concentration of Luteolin

differentially expressed among plant parts over the periods. From March to May, the

mean concentration of luteolin was highest in stem while least in leaves; and from May to

Sept, it was highest in leaves and least in branch; and from Sept to Feb, it was highest in

stem and least in leaves. Further, the concentration of it in branch did not varied much i.e.

remain almost similar over the periods. Comparing the effect of plant parts (groups) and

periods (months) together on concentrations, ANOVA revealed significant effect of both

groups (F=162.54, p<0.001) and periods (F=718.04, p<0.001) on concentrations. Further,

the interaction (groups x periods) effect of both on concentrations was also found

significant (F=903.87, p<0.001).

For each plant part, comparing the mean concentration of luteolin within the groups (i.e.

between periods), Bonferroni test revealed significantly (p<0.01 or p<0.001) different

concentrations in stem between the periods except April and July/Aug/Sept, May and

June, July and Aug, Aug and Sept, and Dec and Feb. In contrast, the mean concentration

of luteolin in branch varied notably (p<0.01 or p<0.001) only between March vs.

May/June/Jan, May/June vs. July to Dec/Feb, Aug/Sept/Oct vs. Jan, and Jan vs. Feb.

Conversely, the mean concentration of luteolin in twig differed significantly (p<0.05 or

p<0.01 or p<0.001) between most of the periods except March and Oct, April and Sept,

Oct vs. Nov/Feb, Nov vs. Dec to Feb, Dec vs. Jan/Feb, and Jan vs. Feb. Likewise, the

mean concentration of luteolin in leaves also differed significantly (p<0.05 or p<0.01 or

p<0.001) in most of the periods except June and July, Nov and Dec/Feb, and Dec and

Feb. Similarly, for each month, comparing the mean concentration of luteolin between

the groups (plant parts), Bonferroni test revealed significantly (p<0.001) different

concentrations among plant parts at all periods except stem and branch from April to July,

stem and twig at Aug, stem and leaves at Aug, branch and twig at April/May/Aug/Sept,

branch and leaves at Sept, and twig and leaves from April to June/Aug to Oct.

217

Luteolin

Stem

Branch

Twig

LeavesMar April May June Jul Aug Sep Oct Nov Dec Jan Feb

Months

-0.002

0.000

0.002

0.004

0.006

0.008

0.010

0.012

Me

an

with

95

% C

I

Fig. 7.8. Concentration of luteolin in various plant parts of B. variegata over the period

of 12 months.

218


4.2.1. Chrysin

The concentration of Chrysin in four plant parts of O. indicum over the 12 months period

are summarised graphically in Fig. 7.9. Results showed that the mean concentration of

chrysin also expressed differently among plant parts over the periods. In March and April,

the mean concentration of chrysin was highest in stem while least in leaves; and from

May to Oct, the concentration of it was highest in twig and least in leaves; and from Nov

to Feb, the concentration of it was highest again in stem and least in leaves. Further, the

mean concentration of chrysin showed inverse trend between stem and twig. Moreover,

the mean concentrations of chrysin did not varied much within both branch and leaves i.e.

evident almost similar over the periods. Comparing the effect of plant parts (groups) and

periods (months) together on concentrations, ANOVA revealed significant effect of both

groups (F=6893233.93, p<0.001) and periods (F=12276.24, p<0.001) on concentrations.

Further, the interaction (groups x periods) effect of both on concentrations was also found

significant (F=479295.61, p<0.001).

For each plant part, comparing the mean concentration of chrysin within the groups (i.e.


concentrations in stem between the periods except June and Aug. Likewise, the mean

concentration of chrysin in branch also fluctuated significantly (p<0.001) between all the

periods except March and April. In contrast, the mean concentration of chrysin in twig

differed significantly (p<0.001) between all the periods. Conversely, the mean

concentration of chrysin in leaves also differed significantly (p<0.001) between all the

periods except June and Aug, and Dec and Jan. Similarly, for each month, comparing the

mean concentration of chrysin between the groups (plant parts), Bonferroni test revealed

significantly (p<0.001) different concentrations among plant parts at all periods.

219

Chrysin

Stem

Branch

Twig


R1

-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Me

an

with

95

% C

I

Fig. 7.9. Concentration of chrysin in various plant parts of O. indicum over the period of

12 months.

220

4.2.2. Baicalein

The concentration of baicalein in four plant parts of O. indicum over the periods are

summarised graphically in Fig. 7.10. The mean concentration of baicalein showed

similar trend as of chrysin. Like chrysin, the mean concentration of baicalein in March

and April was highest in Stem while least in leaves; and from May to Oct, the

concentration of it was highest in twig and least in leaves; and from Nov to Feb, the

concentration of it was highest again in stem and least in leaves. Further, like chrysin, the

mean concentrations of baicalein also showed inverse trend between stem and twig with

minimal variations especially within leaves over the periods. Comparing the effect of

plant parts (groups) and periods (months) together on concentrations, ANOVA revealed

significant effect of both groups (F=15824.94, p<0.001) and periods (F=120.68,

p<0.001) on concentrations. Further, the interaction (groups x periods) effect of both on

concentrations was also found significant (F=385.99, p<0.001).

For each plant part, comparing the mean concentration of baicalein within the groups (i.e.


concentrations in stem between the periods except March vs. Nov/Feb, April vs. Oct,

May vs. Sept, June vs. July to Sept, July vs. Aug/Sept, Aug vs. Sept, Nov vs. Feb, and

Dec vs. Jan. Similarly, the mean concentration of baicalein in branch also differed

significantly (p<0.05 or p<0.01 or p<0.001) between the periods except March vs.

April/May/Nov to Feb, April vs. May/Oct to Feb, May vs. June/Oct to Jan, June vs.

July/Sept to Nov, July vs. Aug to Sept, Sept vs. Oct, Oct vs. Nov/Dec, Nov vs. Dec/Jan,

Dec vs. Jan/Feb, and Jan vs. Feb. Further, the mean concentration of Baicalein in twig

also differed significantly (p<0.05 or p<0.01 or p<0.001) between most of the periods

except March and Feb, April and Dec, May and Nov, June and Sept, and Jan and Feb. In

contrast, the mean concentration of baicalein in leaves not differed significantly (p>0.05)

between all the periods i.e. found to be statistically the same. Similarly, for each month,

comparing the mean concentration of baicalein between the groups (plant parts),

Bonferroni test revealed significantly (p<0.001) different concentrations among plant

parts at all periods except between stem and branch and stem and twig at May, and

branch and twig at April/May/Dec .

221

Baicalein

Stem

Branch

Twig


Months

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

Mean w

ith 9

5%

CI

Fig. 7.10. Concentration of baicalein in various plant parts of O. indicum over the period

of 12 months.

222


4.3.1. Conessine

The concentration of conessine in four plant parts of H. pubescens over the periods are

summarised graphically in Fig. 7.11. Tthe mean concentration of conessine also

expressed variably among plant parts over the periods with highest being stem followed

by branch, twig and leaves, the least. Further, over the periods, the mean concentration of

conessine in stem showed inverse trend with branch, twig and leaves. Comparing the

effect of plant parts (groups) and periods (months) together on concentrations, ANOVA

revealed significant effect of both groups (F=4367721.49, p<0.001) and periods

(F=60996.07, p<0.001) on concentrations. Further, the interaction (groups x periods)

effect of both on concentrations was also found significant (F=62950.03, p<0.001).

For each plant part, comparing the mean concentration of conessine within the groups

(i.e. between periods), Bonferroni test revealed significantly (p<0.001) different

concentrations in stem between all the periods except Nov and Jan. Similarly, the mean

concentration of conessine in branch also differed significantly (p<0.001) between all the

periods except April and Aug. Further, the mean concentration of conessine in twig also

differed significantly (p<0.001) between most of the periods except April and July, May

and June, and Nov and Jan. Moreover, the mean concentration of conessine in leaves also

differed significantly (p<0.001) between all the periods except Dec vs. Jan/Feb, and Jan

vs. Feb. Similarly, for each month, comparing the mean concentration of conessine

between the groups (plant parts), Bonferroni test revealed significantly (p<0.001)

different concentrations among plant parts at all periods.

223

Conessine

Stem

Branch

Twig


Months

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Mean w

ith 9

5%

CI

Fig. 7.11. Concentration of conessine in various plant parts of H. pubescens over the

period of 12 months.

224


4.4.1. Arjunic Acid

The concentration of arjunic acid in four plant parts of T. arjuna over the periods are

summarised graphically in Fig. 7.12. Analysis illustrates that the mean concentration of

arjunic acid also expressed inconsistently among plant parts over the periods with highest

being stem followed by branch, twig and leaves. Further, over the periods, the mean

concentration of arjunic acid in stem showed inverse trend with branch, twig and leaves.

Comparing the effect of plant parts (groups) and periods (months) together on

concentrations, ANOVA revealed significant effect of both groups (F=3020949.39,

p<0.001) and periods (F=60681.70, p<0.001) on concentrations. Further, the interaction

(groups x periods) effect of both on concentrations was also found significant

(F=77554.20, p<0.001).

For each plant part, comparing the mean concentration of arjunic acid within the groups

(i.e. between periods), Bonferroni test revealed significantly (p<0.001) different

concentrations in stem between all the periods. Similarly, the mean concentration of

arjunic acid in branch also differed significantly (p<0.001) between all the periods except

July and Jan, and Aug and Dec. Further, the mean concentration of arjunic acid in twig

also diverged significantly (p<0.01 or p<0.001) between most of the periods except April

and Feb, July and Dec, and Aug to Oct. In contrast, the mean concentration of arjunic

acid in leaves only differed and lowered significantly (p<0.05 or p<0.01 or p<0.001)

from June to Jan as compared to May and rest of the periods it was found analogous i.e.

not differed statistically. Similarly, for each month, evaluation of the mean concentration

of arjunic acid between the groups (plant parts), Bonferroni test discovered significantly

(p<0.001) different concentrations among plant parts at all periods except twig and leaves

from Aug to Nov.

225

Arjunic acid

Stem

Branch

Twig


Months

-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Mean w

ith 9

5%

CI

Fig. 7.12. Concentrations (%) of arjunic acid in various plant parts of T. arjuna over the

period of 12 months.

226

5. Discussion

Changes in issues and advances in methodology have contributed to substantial progress

in tree physiology research during the last several decades. Research has shown that the

biosynthesis of secondary metabolites although controlled by genetic factors is affected

by environmental influences, developmental stages, functionally different plant parts. As

a result there are fluctuations in the concentration and quantities of secondary

metabolites. But, still now limited work has been done on tree species specifically. With

a view to improve the quality of plant based drugs, to ascertain the optimum

concentration of chemical constituents responsible for medicinal properties and to

provide scientific basis (time of collection/harvesting) for therapeutic purposes best time

of harvesting and to understand the physiology of tress better, the current work was

undertaken.

In present study, secondary metabolites of all the four studied species were found to vary

with respect to change of season and phenological attributes which supports the earlier

findings that the composition of phyto-constituents varies considerably throughout the

year (see Grace et al., 1988; Manika et al. 2013; Liu et al., 1998). From the results, it

could be inferred that secondary metabolites are translocated in different plant parts in

respective seasons. The content of apigenin and luteolin in B. variegata is found highest

in stem bark from July-Dec, it could be suggested that the harvesting of bark could be

done in the above mentioned months. Additionally, their content increases in twigs and

branches during Feb-July, making it clear that, these alternate parts could be harvested

for medicinal purposes during this period. The content of major phyto-constituents

increases in the leaves too, during May-Aug, so, leaves harvested in the above months

may show some pharmacological properties. However, as it could be noticed that the

content of the bioactive components remain lower in leaves than that of other parts, it is

possible that leaves do not show such high level of pharmacological potential, which

other parts could demonstrate.

In O. indicum, the major pharmacological activity is dependent on the two compounds

i.e. chrysin and baicalein which are found luxuriously in stem bark during Oct-Jan and

being translocated to twigs in the months of June-Sep. However, in this case content of

227

these compounds are found to be almost consistent throughout the year and further their

content rises in leaves during May-Oct. With these details, it could be suggested that

parts could be harvested in the particular season when the content gets higher in the

respective parts. Again, it is noticed that the content of these compounds are never

dominant in leaves of the species, be it in any season. Thus, harvesting leaves would not

favor the standards of medicinal component in any time of the year.

In case of H. pubescens, conessine is the pharmacologically active constituent of the

plant which is found maximum in stem bark during Sep-Feb and then shows its

dominancy towards the branch and twig during April-Aug. It was an interesting

observation in case of this species, that although the content of the bioactive alkaloid

increases in branch and twigs, but it still doesn‟t match the level of amount present in

stem bark. But even then, for sustainable harvesting measures it could be suggested to

harvest the other parts instead of stem bark for that period of time when the amount of

metabolite goes down in the bark. However, leaves do not contain the desired metabolite

in adequate amount throughout the year.

Conversely, the content of arjunic acid in T. arjuna, does not show drastic fluctuations

within plant parts and was found to be maximum in stem bark itself throughout the

seasons. Although, increase in its content was noted from May-Sep within stem bark but

the content of the phytoconstituent was not found to be relatively better in any other plant

part. Thus, in case of T. arjuna, use of only stem bark could be recommended.

Furthermore, a very interesting phenomenon was observed in terms of bioactive content

variation and phenology of all the studied tree species. It was observed that the content of

secondary metabolite increases towards upper half of the tree i.e. branches and twigs,

during their respective flowering and fruiting season.

In B. variegata, leaves flush during Feb-Aug and from the same time flowering starts

which remains for 2-3 months. The tree blossoms during the period of Feb-April. It was

noticed that the total content of secondary metabolites was predominantly higher during

this particular duration.

228

Similar phenomenon was noticed in case of O.indicum and H. pubescens too. O.indicum

and H. pubescens blossoms during the period of May-August and May- July,

respectively. And the increase in the metabolite content in other parts than bark was

observed in the same duration.

Nonetheless, there was no relevance of tree phenology with that to secondary metabolite

translocation in T.arjuna, where minimal fluctuation was noted within plant parts.

It may be due to the evergreen nature of this species, while the other three studied species

are deciduous in nature. Further studies on vast number of species are needed to confirm

this phenomenon.

Altogether, this study aimed not only at enhancing the knowledge in deciding the proper

harvest timings of a plant but also assessing within an eco physiological perspective, the

influence of environmental characteristics on the production of secondary metabolites.

Furthermore, it also adds inquisitiveness towards the physiological attributes of larger

plant species.

CHAPTER 8

General Conclusion and Summary

229

GENERAL CONCLUSION AND SUMMARY

Non timber forest products, especially medicinal plants are valuable natural resources

that are essential for human populace. Throughout the world, millions of people rely on

medicinal plants for their basic healthcare needs. Also, a vast number of tribal

communities throughout the world derive a major portion of their livelihood from these

gathered plant products and are economically dependent upon them. The annual market

for plant based drugs is increasing constantly and this increase is likely to rise in near

foreseeable future. When it comes to the increasing needs of human race, it becomes

mandatory to look at the other side of the coin, which is, in this case, base resource

availability. As we comprehend, most medicinal plants are harvested from the wild and

that to a large extent and this extent of their harvest has lead to species overexploitation

which ultimately leads to species extinction.

Thus the conservation of these species is imperative. Additionally, medicinal plant

conservation is an important aspect of biodiversity conservation and is a matter of urgent

priority throughout the world with a special reference to the developing nations of the

world. Conversationalists, policy makers and governments are constantly trying to handle

this challenge effectively. But utility systems to ensure the sustainability of plant

resources are still lacking, although, there are some strategies present to solve this

problem, for instance:

To establish conservation areas

Restrict/ ban the collection of medicinal plants from wild.

Cultivation of medicinal plants

Check on illegal trade

But again, these strategies could favor only a minor portion of the problem area for

example, large scale cultivation is feasible for herbaceous or shrubby species and not the

tree species. Furthermore, what alternative would be given to that segment of populace

whose livelihood is dependent upon the collection of NTFPs/ medicinal plants.

At this critical stage when the nations of the world are fighting to combat this issue of

overexploitation of natural resources, our study primarily aims and justifies conservation

230

research to benefit biological diversity by recognizing problems, identifying patterns,

quantifying changes and testing solutions.

Further, our research focuses on the effectiveness of the different methods for the

ecosystem services and the cost effectiveness of the management system. Also, it focuses

on the crucial point of practitioner‟s satisfaction which is directly related to the

implication of the method in regular practice.

Our study has focused mainly on tree species because:

More than 99% of the tree species are harvested from the wild.

Cultivation is not always an option for trees.

They have slow growth rate, so it take years to produce required secondary

metabolites.

They are principal biomass components of forest ecosystem

Used for more than one reason e.g. for timber wood, live stocks, fuel etc.

They support vast number of other life forms.

Additionally, our work provides a scientific conservation insight which fulfills the

precondition of sustainability yet meets the human need in parallel.

According to Ticktin (2004), to manage and conserve NTFP populations effectively, in

addition to socio-economic and political issues, some ecological questions must also be

addressed like the ecological impacts of harvest, how differently species respond to

different methods, what kinds of management practices may mitigate negative impacts

and/or promote positive impacts and what strategies could be used to minimize the

resource waste and so on.

The observation and the measurements of the various responses of the debarked tree in

reaction to the harvest techniques, in the natural surroundings is the first step of the

development of the decision model. The second step consists of determining the loss of

resources occurred between the period of postharvest and consumption. The third step is

that of finding an alternative, strategy which would satisfy the requirement of sustainable

harvesting, yet simultaneously provide the health care needs and the last is to ensure a

231

proper harvesting time so that resource waste could be avoided. The discussion in each

chapter indicates to what extent the specific study objective and research questions have

been met and answered. This information is briefly summarized as follows:

The fourth chapter enabled us to develop a first decision model, to identify the most

adequate debarking technique for each of the 4 species as a function of their responses

following bark removal: edge growth (regeneration developing from the edge of the

wound), sheet growth (regeneration developing from the surface area of the wound), and

agony shoots (vegetative shoots developing around a wound in response to wounding).

The results of this study showed that tree response to bark harvesting is species-specific

but, partial harvest with moisture treatment supported the regeneration rate maximum. It

was a clear observation that the harvesting technique based on total bark removal which

is also a general practice, did not promote bark regeneration by any means i.e. either edge

augmentation or sheet growth. While, the bark regeneration was found treatment as well

as size dependent but overall it was observed that this commercial harvest method of total

bark removal posed most detrimental effects on tree. Size of the tree also had a

significant influence on the bark recovery rate but this factor again, varies from species to

species. It was interesting to note that, in three out of four cases i.e. B. variegata, O.

indicum and H. pubescens, the trees with higher d.b.h. exhibited expeditious recovery in

terms of edge augmentation. However, size of the tree has least correlation with recovery

through sheet growth or edge augmentation because two species (B. variegata and O.

indicum) recovered the wound mostly by edge augmentation while on the other hand H.

pubescens recovered through sheet growth. The ability of a species to develop agony

shoots is particularly related with the capability of the species to produce copious shoots.

But the studied species were not found active in producing the same. Thus this technique

has insignificant relevance in context to the management of these particular trees. Overall

it could be inferred that the observations on different ecological responses of debarked

tree could assist in the development of a proper harvesting strategy in woodlands.

In the fifth chapter, we refined prescriptions related to the best and wise method of

storage of plant part to assist in the longer shelf life of the drug. In this way, the

experiment provided important information not only to traditional healers and potential

232

cultivators, but also exhibited conservational implications. The bioactive nature of many

secondary metabolites may arise from the presence of highly reactive functional groups.

Secondary metabolites may deteriorate because they react with and disrupt the functions

of physiologically important molecules such as enzymes or DNA. Because of this

reactivity, these compounds also may undergo reactions that lead to their deterioration or

conversion. Compound breakdown and conversion can be challenging since they mislead

quantitative data and could diminish the extent of metabolite activities in bioassays. If a

plant retains its activity for longer extent after harvesting, then this plant need not be

discarded and the fresh material need not to be harvested frequently which further

promotes the conservation of the remaining resources. Results prove that methods of

storing can significantly affect yields of biologically and ecologically important

compounds. The study concluded that the use of polypropylene (PP) material instead of

regularly used polystyrene (PS) containers could assist in minimizing the resource waste

due to bulk storage. Additionally, opting for low temperature conditions to store plant

materials could also support the cause. However, conclusions made from this

investigation cannot be attributed only to the medium of storage and temperature, as the

storage duration also affected the chemical composition of the material. The effect of

storage is also species-specific, because the chemical composition of each species differs.

Thus, no universal supposition can be made with respect to suggested shelf-lives of plant

material and each plant should be tested separately for the same. The implications of

these findings could affect the way traditional healers, medicinal plant consumers and

scientists working with medicinal plants treat their material.

The sixth chapter was associated with finding an innovative and reliable technique which

would fulfill the market demand for health care as well as satisfy the requirement of

sustainable harvesting. We proposed an interdisciplinary approach and an attempt had

been made to establish the necessary linkage between utilizing the valuable resource and

contributing equally to the conservation aspect. This was achieved by applying

biopharmaceutical equivalence approach. Alternative plant parts were tested for the

similar chemical profile and relevant pharmacological activity as compared to the vital

parts like roots and stem bark. Results demonstrate that in all the cases except T. arjuna,

different plant parts showed more or less similar chemical profile and relevant

233

pharmacological activities. However, leaves did not show any related activity

significantly. Our study concludes that, the use of vital part of plant like bark could be

replaced with plant parts which are less destructive to harvest, in the species where the

extracts of both, traditionally used part and substituted parts show equivalent

pharmacological potency. It implements the concept of bio-equivalency for conservation

and in this way, conservation and use of the species can be combined. As recommended

by Cunningham (1991), Delvaux et al. (2009) and Ticktin (2004), more strategies should

come up to promote sustainable use of medicinal plants and thus, plant part substitution

(PPS) could be a plausible solution in the direction. Moreover, it also covers the

integrated approach for management relevant understanding aimed at protecting

biodiversity as suggested by Likens and Lindenmayer (2012). We also suggest that

random selection of plant parts without any prior validation should be discouraged in

order to avoid resource waste.

The seventh chapter addresses a very crucial part of judicious resource management

which relates to the physiology of the tree species. As we comprehend that plants

produce a vast number of secondary metabolites, in addition to primary metabolites, via

complex pathways, which are regulated in highly sophisticated manners (Yazaki 2004)

and these secondary metabolites are the bioactive components due to which plants

possess pharmacological potential.

The amount of metabolites present in a given plant may be influenced by biological and

environmental as well as biochemical, physiological, ecological, and evolutionary

factors. As a result there are fluctuations in the concentration and quantities of secondary

metabolites. With a view to improve the quality of plant based drugs, to ascertain the

optimum concentration of chemical constituents responsible for medicinal properties and

to provide scientific basis (time of collection/harvesting) for therapeutic purposes best

time of harvesting and to understand the physiology of tress better, the current work was

undertaken. The study demonstrated that secondary metabolites of all the four studied

species varied with respect to change of season. As the observation on metabolite

fluctuation was taken in all the parts of the plant; it may be inferred that secondary

metabolites are translocated in different plant parts in respective seasons. The content of

234

apigenin and luteolin in B. variegata is found highest in stem bark from July-Dec and

increases in twigs and branches during Feb-July. In O. indicum, the major bioactive

compounds i.e. chrysin and baicalein were found luxuriously in stem bark during Oct-Jan

and being translocated to twigs in the months of June - Sep. In case of H. pubescens,

conessine was found maximum in stem bark during Sep-Feb and then shifts towards the

branch and twig during April-Aug. It could be inferred that the respective plant parts, in

which the content of secondary metabolites gets higher, could be used as source of drug

during the months

In contrary, no drastic fluctuations in the content of arjunic acid in T. arjuna was

observed within plant parts and it was found to be maximum in stem bark itself

throughout the seasons. Though, fluctuation in its content was noted within stem bark

itself. Thus, in case of T. arjuna, use of only stem bark could be recommended. It may

also be suggested to harvest stem bark during that season in which content of the

bioactive constituents remains highest.

This study aimed not only at enhancing the knowledge in deciding the proper harvest

timings of a plant but also assessing within an eco physiological perspective, the

influence of environmental characteristics on the production of secondary metabolites.

It implies the conservation through use system in factual sense and shifts the prevailing

approach of over protective disposition in forest management towards promising

sustainable system. The management implication of the study allows two types of

management relevant approach. Primarily, the tree could be sustainably harvested in its

existing habitat through partial harvesting followed by covering the wound and relatively

mature trees with larger d.b.h. should be harvested as their ability to close the wounds

was found to be much better than smaller trees. Additionally, monitoring of the harvests

by local practitioners could promote persistence. On the other hand, proper storage

method, substitution of plant parts and determination of appropriate harvest season could

also add value to the management practice. Managers, however, need to take an objective

decision on the most appropriate harvest options for a particular species to ensure that

bark harvesting is sustainable and viable in the long term and to optimize socio-economic

235

benefits from resources used. This conceptual framework for the development and choice

of a bark harvest system is provided in the study.

Furthermore, more interdisciplinary and applied perspective should be given to the work

in order to forge methods for flora protection. Additionally, new policies and acts should

be made and particularly enforced for better regulation of the utilization of natural

resources.

These kinds of innovative conservation strategies broaden the remit of ecology. Based on

our studies, it could be suggested that systematic pioneer endeavors like this may protect

more plant species from extinction, leading in the recovery of base resource for

pharmaceutical industries. However, policies should be made for these promising

methods for conservation and particularly enforced for better regulation of the utilization

of the botanical resources.

236

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SCIENTIFIC ACTIVITIES OF THE AUTHOR

PEER REVIEWED PAPERS

N. Manika, V.K. Gupta, R.K. Verma, M.P. Darokar, N. Pandey, G.D. Bagchi, 2013.

Extraction efficacy, antibacterial potential and validation of RP-HPLC coupled with

diode array detection in Holarrhena pubescens. International Journal of Pharmaceutical

Sciences and Research, 4(8), 3020-3027.

A.K. Yadav, N. Manika, G.D. Bagchi, M.M Gupta, 2013. Simultaneous determination of

flavonoids in Oroxylum indicum by RP-HPLC. Medicinal Chemistry Research, 22(5),

2222-2227.

N. Manika, C.S. Chanotiya, M.P.S. Negi, G.D. Bagchi, 2013. Copious shoots as a

potential source for the production of essential oil in Eucalyptus globulus. Industrial

Crops and Products, 46, 80–84.

N.Manika, S. Singh, R.K.Verma, G.D. Bagchi, 2013. Extraction efficacy, stability

assessment and seasonal variation of bioactive „gymnemagenin‟ in Gymnema sylvestre.

Industrial Crops and Products, 44, 572-576.

S. Singh, N. Manika, R.K. Verma, G.D. Bagchi, 2013. Effect of different storage

conditions on guggulsterone content in oleo-gum resin of Commiphora wightii.

International Journal of Phytomedicine. 5(1), 245-247.

A. Maurya, N. Manika, R. K. Verma, S.C. Singh, S.K. Srivastava, 2013. Simple and

Reliable Methods for the Determination of Three Steroidal Glycosides in the Eight

Species of Solanum by Reversed-phase HPLC Coupled with Diode Array Detection.

Phytochemical Analysis, 24(1), 87-92.

N. Manika, P. Mishra, N. Kumar, C.S. Chanotiya, G.D. Bagchi, 2012. Effect of season

on yield and composition of the essential oil of Eucalyptus citriodora Hook. leaf grown

in sub-tropical conditions of North India. Journal of medicinal plant research, 6, 2875-

2879.

N. Gupta, N. Manika, S. Singh, S.C. Singh, V.S. Pragadheesh, A. Yadav, C.S.

Chanotiya, 2011. Investigation on phenylpropanoids rich Melaleuca decora (Salisb.)

Britt. essential oil. Natural Product Research, 19, 1-3.

N. Kumar, N. Manika, R. Shukla, R.K. Verma, G.D. Bagchi, 2010. Concentration of

guggulsterons in oleo-gumresin of Commiphora wightii plants domesticated at the

subtropical conditions of North India, Indian Drugs, 47(6), 69-73.

RESEARCH PAPERS ACCEPTED

N. Manika, C.S. Chanotiya, M.P. Darokar, S.C. Singh, G.D. Bagchi, Compositional

characters and antimicrobial potential of Artemisia stricta f. stricta essential oil. Records

of Natural Products

PAPERS PRESENTED IN SYMPOSIUM/ CONFERENCES

N. Manika, A,K. Singh, H.P. Singh, R.K.Verma, B. Kumar, G.D. Bagchi, 2013. Effect

of calliterpenone on the enhancement of biomass and bio-active constituents in

Andrographis paniculata. National Conference on Microbes Promoting Crop Health,

Productivity and Sustainability, October 26-27, Lucknow, Uttar Pradesh.

N. Manika, 2013. Methods on reinforcement of resource use system for medicinal tree

species to ensure sustainability. XXXVI All India Botanical Conference, October 18-20,

Gorakhpur, Uttar Pradesh.

N. Manika, G.D. Bagchi, 2012. Evaluation of guggulsterone content in the oleo-gum

resin of Commiphora wightii (Guggul) on cultivation at Indo-Gangetic plains and at

different storage conditions. National Workshop of Sustainable Management of Natural

Gums and Resins, December 21-22, Jabalpur, Madhaya Pradesh.

N. Manika, 2012. Responses to bark stripping and alternative harvesting strategies in

Oroxylum indicum Vent., XXXV All India Botanical Conference, December 8-10,

Vadodara, Gujrat.

N. Manika, P. Mishra, R.K. Verma, G.D. Bagchi, 2011. Determination of methods of

sustainable harvesting for Terminalia arjuna. National Conference on Environment and

Biodiversity of India, December 30-31, New Delhi.

N. Manika, P. Mishra, A.K. Singh, B. Kumar, G.D. Bagchi, 2011. Effect of

„calliterpenone‟ a novel plant growth promoter on various attributes of sweet basil

(Ocimum basilicum l.) as compared to various growth regulators. XXXIV All India

Botanical Conference, October 10-12, Lucknow, Uttar Pradesh.

N. Manika, G.D. Bagchi, 2011. Ocimum: An overview of phylogeny, evolutionary

tendencies and systematic, Ocimum 2011: Ancient heritage to modern enigma, July 28-

29, Lucknow, Uttar Pradesh.

P. Mishra, N. Manika, F. Haider, G.D. Bagchi, 2011. Effect of domestication for the

conservation of Artemisia myriantha var pleiocephala, a rare temperate plant, at

subtropical conditions, National Conference on Environment and Biodiversity of India,

December 30-31, New Delhi.

N. Kumar, N. Manika, S. Banerjee, G.D. Bagchi, 2010. In vitro secondary metabolite

production in callus cultures of Lagerstroemia speciosa, The International Conference on

Current Status and Opportunities in aromatic and Medicinal Plants: AROMED, February

21-24, Lucknow, Uttar Pradesh.

R. Shukla, N. Manika, F. Haider, G.D. Bagchi, 2010. Effect of climatic condition on

essential oil composition of some rare Artemisia species, The International Conference on

Current Status and Opportunities in aromatic and Medicinal Plants: AROMED, February

21-24, Lucknow, Uttar Pradesh.

submitted to the university of lucknow for the...

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