Journal of Plant Development Sciences (An International Monthly Refereed Research Journal)

Volume 12 Number 5 May 2020

Contents

RESEARCH ARTICLES

Assessment of carbon stock and future potential of carbon sequestration of Soor Sarovar bird Sanctuary,

Keethm-UP

—Ashutosh Kumar Pathak, J.V. Sharma and Priyanka Tiwari--------------------------------------------- 261-268

Preclinical study of healing effect of methanolic extract of Coriandrum sativum in wounds of an animal model

of Diabetes

—Flor Rivera-Barbosa, Reyna Hernández-Ramos, Alejandro Hernández-Herrera, Irais Castillo-

Maldonado, Mario-Alberto Rivera-Guillén, Rubén García-Garza, Dealmy Delgadillo-Guzmán, Agustina

Ramírez-Moreno, María-Del-Carmen Vega-Menchaca, Sergio-Everardo Velázquez-Gauna, Luis-

Benjamín Serrano-Gallardo and David Pedroza-Escobar ---------------------------------------------------- 269-275

Seed germination behaviour of Cannabis sativa L. under different temperature regimes

—Birendra Kumar, S. Zaidi, Vagmi Singh, K.T. Venkatesh, Govind Ram, A.K. Gupta, Narendra Kumar

and A. Samad ---------------------------------------------------------------------------------------------------------- 277-281

Performance of intercrops in hybrid maize under North Central Plateau Zone of Odisha

—T.R. Mohanty, M. Ray, S.K. Sahoo, K.C. Sahoo, N. Mishra and H.K. Patro -------------------------- 283-287

Effect of integrated nutrient management on growth and development of mustard (Brassica juncea L.) in irrigated condition of upper Gangetic plains

—Sauhard Dubey, M.Z. Siddiqui, Saurabh Rana, Gaurav Shukla, Dharmendra Singh and Ashish Nath

Pandey ------------------------------------------------------------------------------------------------------------------- 289-295

Utilization potential of agricultural information sources

—K. Pradhan, Avishek Saha, Biman Maity and Keshav Ram ----------------------------------------------- 297-301

Plant growth promoting activities of indigenous strains of Trichoderma viride and Trichoderma harzianum

used as seed treatment in groundnut

—Shweta Mishra, Arwind Kurre and R.K.S. Tiwari ---------------------------------------------------------- 303-307

Evaluation of soybean cultivars for resistance to Alternaria leaf spot caused by Alternaria alternata

—Raj Kumar Fagodiya, Amit Trivedi, B.L. Fagodia and R.S. Ratnoo ------------------------------------ 309-312

Ethno medicinal knowledge of spices and their uses by tribal community of Rajasthan, India

—Deepa Indoria and S.R. Verma ---------------------------------------------------------------------------------- 313-316

Effect of soaking and placement of seed on germination and seedling emergence in Litchi

—Narayan Lal, E.S. Marboh, A.K. Gupta, Abhay Kumar and Vishal Nath ------------------------------ 317-320

Performance of parents and hybrids for yield and yield attributing traits in tomato (Solanum lycopersicum L.)

—Kiran Kumar, Dhananjay Sharma, Jitendra Singh and S.S. Paikra ------------------------------------ 321-326

*Corresponding Author

________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 261-268. 2020

ASSESSMENT OF CARBON STOCK AND FUTURE POTENTIAL OF CARBON

SEQUESTRATION OF SOOR SAROVAR BIRD SANCTUARY,KEETHM-UP

Ashutosh Kumar Pathak*, J.V.Sharmaa and Priyanka Tiwari

a

*Department of Natural Resources, TERI School of Advanced Studies, Vasant Kunj,

New Delhi, India aForestry & Biodiversity Division, The Energy and Resources Institute (TERI)Habitat Center, -New

Delhi, India

Email: ashutosh.pathak@terisas.ac.in

Received-04.05.2020, Revised-25.05.2020

Abstract:Soor Sarovar Bird Sanctuary is a small human-made forest with a lake on the outskirts of Agra, India. The study estimates terrestrial and aquatic carbon. The total carbon stocks estimated at 1.31 million tons bears a social cost of carbon value of `21 million. The aquatic carbon stock density was found to be significantly higher than the terrestrial stocks. The

study outcomes are usable for maximising ecosystem services in the broader context of sustainability. The research method estimating carbon stocks is relevant to national policies and applicable to similar forests. An optimistic scenario suggests that the sanctuary area by 2030 can sequester per unit area carbon which is 12times the target of achieving our ambitious target. An established theoretical and empirical correlation of increased carbon stocks with biodiversity and other ecosystem services are suggestive of such small urban peripheral sanctuaries playing a critical role in mitigating the climate change.

Keywords: Soor Sarovar Bird Sanctuary, Aquatic carbon, Terrestrial carbon, Carbon stocks,Anthropogenic

INTRODUCTION

orests are both source and sink of greenhouse

gases. The impact of Agriculture, Forestry and

Other Land Use (AFOLU) sector to anthropogenic

emission is just close to a quarter of the

anthropogenic total (Smith et al. 2014). Annual

greenhouse gas change from land use and land-use

change activities during the first decade of this

century accounted for approximately 4.3-5.5 GtCo2

eq/yr, amounting to 9-11 per cent of total

anthropocentric gas emissions globally (Smith et al. 2014).

Indian forests stock 7 Gigatons of carbon out of 650

Gigatons estimated globally(ISFR 2017). Contrary to

the declining global trend of forests(FAO 2018),

various Indian proactive conservation policies and

legislation seem to have stalled and reversed the

deforestation(MOEF&CC 2015). The claim,

however, has been contested based on the resolving

potential of remote sensing data(Puyravaud et al.

2010)(Davidar et al. 2010)(Ravindranath et al. 2014).

Loss of forests through diversion, encroachment, and

degradation was a specific problem highlighted in The Forest Commission Report (MOEF 2006). The

issue of forest degradation thus needs to be

addressed.

None the less, the National Forest Policy also

acknowledges and calls for special attention against

forest degradation. (MOEF & Forests 1998). Forest

Survey of India (FSI) since 2011 has published

reports on carbon stock as a separate chapter. The

India State of Forest Report (ISFR) now includes

state and district wise information on carbon stock

and change(ISFR 2017). Sustainability requires that these mesoscale efforts mainly through the satellite

imagery are supplemented and correlated with local site-specific microscale environmental parameters.

Such quantification becomes critical in the context of

our ambitious Nationally Determined Contribution

(NDC) goal of creating additional carbon sink of 2.5

to 3.0 billion tons of CO2 equivalent through

additional forest and tree cover by 2030 (MOEF&CC

2015).

Forest pathways contribute to ten of the seventeen

sustainable development goals (FAO 2018).

Country’s commitment to Sustainable Development

Goals (SDGs) focuses on enhancing the forest ecosystem services through new technological

advancements. It has been recognized that the

tangible benefits like firewood, timber, and non-

timber forest Products only form an abysmally low

proportion of all Ecosystem services(MOEF&CC

2018).

The present study at Soor Sarovar Bird Sanctuary is

set in the context of evaluating the total ecosystem

services for sustainable development.

Study Area

Soor Sarovar Bird Sanctuary (SSBS), Keetham, Agra

is an important protected area in the state of Uttar Pradesh. Unique for scenic beauty, religio-cultural

heritage and abundant fauna and flora, it has been

named after Soordas - the great blind poet of Hindi

literature, whose place of birth is said to be within

the boundary of this sanctuary. SSBS lies between

latitude N27º 14' 4″ and N27º 31' 51″ and longitude

E77º 49' 38″ and E77º 52' 40″. The total area of Soor

Sarovar bird sanctuary is 7.99 km2. It consists of a

core of 3.96 km2, 0.478km2 for tourism and a buffer

zone of 3.55 km2(Uttar Pradesh Forest Department

2010). Figure 1 shows the key plan of the study area.

F

RESEARCH ARTICLE

262 ASHUTOSH KUMAR PATHAK, J.V.SHARMA AND PRIYANKA TIWARI

Fig. 1: Key Pan of Soor Sarovar Bird Sanctuary

The Sanctuary meets the criteria laid out by the

International Bird Association (IBA). Ministry of

Environment, Forest and Climate Change,

Government of India has also identified Soor Sarovar

Bird Sanctuary’s Keetham lake as important Wetland visited by migratory birds (MOEF 2007). The

Sanctuary supports three vulnerable bird species,

namely, Sarus Crane (Antigone Antigone), Lesser

Adjutant (Leptoptilosjavanicus) and Greater Spotted

Eagle (Aquilaclanga) listed in the IUCN Red List

Category. The artificial lake with more than 90 %

reservoir storage capacity has been categorised as

near favourable specifically for the habitat of birds.

The Sanctuary has also been categorised as a high

threat area on account of Biological Resource use

and Residential and commercial development (IBA 2019).

Anthropogenic pressures:The study area is set in

Agra district for which Census 2011 records a human

density population at 1084 inhabitants per square

Km. This places Agra at rank 41st amongst 640

Indian districts(The Registrar General & Census

Commissioner 2011). High-density habitations

surround the Sanctuary except on the east side

through which the river Yamuna flows.

Being upstream of a significant population settlement

of Agra hydrologically and on the way to National

Capital Region, Delhi makes region around Soor Sarovar Bird Sanctuary area an ecological hot spot.

Rapid planned and unplanned development at the

regional level is causing unprecedented

anthropogenic pressures all around.

METHODOLOGY

The study area was acquainted by wandering around

using measuring tools including manual compass,

GPS, clinometer, a tape of various sizes, survey

Chain and flags. Google My Maps mobile application was used as the main tool of site

contextualization. Google Earth Pro application was

used to crosscheck and get details about the

location’s altitude and coordinates.

The methodology of measuring carbon and related

parameters were developed based on subject

knowledgebase for measuring carbon considering the

local condition. The level of precision required was

kept as provided for in the Forest Survey of India’s

publication The Manual of Instructions for Field

Inventory 2002 (FSI 2002) and ensured that the mean

value of carbon stock estimation falls within ± 10% of carbon stock at the 95% confidence interval.

The study area was delimited adopting the boundary

specified for SSB Sanctuary by the Forest

Department. A categorised study area cover map

based on canopy density and forest type was

prepared by integrating information available from

Google Mymaps, archival records, available forest

management plans and ground survey, taking 25 m x

25 m as a unit of observation. The data was plotted

using 3D Map tool of the MS Excel spreadsheet

application. Five terrestrial classes could be mapped: (i) very dense forest (in more protected central areas

near water body with broad leave plantation having

tree canopy density of > 70%) ii) moderately dense

(Other thorny forest areas, with tree canopy density

between 40%-70%) iii) open forest (Tree Canopy

density between 10%-40% iv) scrub and v) barren

(Areas with no or very little vegetation). Carbon

stock in a given stratum was computed from its

carbon density (t/ha) and area (ha). The aquatic areas

within have been classified by water depth as Deep

(>2.5m), mid-deep (1.5m-2.5m), Shallow (<1.5m)

and bank (the silty areas around the waters with seasonal grass or nascent vegetation).

Terrestrial Carbon:The Intergovernmental Panel on

Climate Change(IPCC 2003) specifies five carbon

pools viz., above ground biomass, below-ground

biomass, litter, woody debris and soil organic matter

except that aboveground woody debris component

was assumed to be insignificant because of regular

removals by the people around the study for

fuelwood.

Sampling design:Eighty-four samples distributed

across the study proportionate to the strata areas were selected, all trees with more than 10 mm diameter at

breast height and with a least 2 meters’ height were

marked. The sample geolocation, tree species and

their Diameter at Breast Height (DBH) and heights

were recorded as per the procedure of measuring

detailed in the Measuring Carbon Stock Manual of

the World Agroforestry Center (Hairiah et al. 2010).

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 263

The samples were rectangular /circles of a size of

approximately .01 ha area. Above ground tree

biomass was calculated using available volume

equations (Picard, Saint-André & Henry 2012)(FAO

2018), a biomass expansion factor of 3.4 as per the

Good Practice Guidance for Land Use, Land Use Change and Forestry (IPCC 2003) and wood density

databank of FAO’s (FAO 2018) was taken.

The below-ground biomass was calculated based on

the root: shoot factor (RSR) of 0.27 as per IPCC

Good Practice Guidelines (IPCC 2003).

Soil Organic Carbon: Forty-two monoliths (30 cm x

30 cm x 30 cm) representing all five strata were

excavated, soil from three depths (0-10, 10-20 and

20-30 cm) were stored separately. The samples were

mixed to form three composite samples for each

forest stratum which were analysed in the laboratory.

The soil was air-dried and passed through 250-micron sieve after removing gravels. Soil organic

carbon was estimated by Walkley-Black wet

digestion method (IS : 2720 (Part XXII) 1972-

(Reaffirmed 2010)). The soil bulk dry density was

estimated using excavation method which involved

digging out a small hole for taking out soil sample

and measuring the volume of the hole by pouring

water from a calibrated measurement jar into a

hermetically sealed and tested polythene bag filling

the hole. The soil taken out was oven dried (at

105°C) and weighed as per soil lab modules. (https://labmodules.soilweb.ca/soil-compaction-bulk-

density/). Carbon density was calculated using men

carbon percentage for each stratum and their bulk

values (Hairiah et al. 2010).

Aquatic carbon Estimation

Carbon Pools: Aquatic carbon was estimated by

totaling i) Alluvium carbon deposits ii) Lake waters

in the form for both dissolved and particulate carbon

and iii) Carbon contained in Fish and water birds.

Soil/ Alluvium carbon Estimation: Levels for all

segments of and around the lake were worked out

using google earth pro imagery. Data analysis of the segments depths was conducted and plotted on the

3D map to demarcate lake stratum. While sample on

the lake bank and shallow waters could be obtained

using a 4 meter PVC pipe which was vertically

driven and created a space for lowering and working

the SPT hammer for sample collections; two such

pipes were hermetically sealed to obtain samples

from deep and mid-deep water stratum.

For alluvium sampling in waters, the boat, with the

help of google my map mobile geolocation, was

taken to the sample coordinates and fixed to be lake bottom with the help of three ballies. The

hermetically sealed pipe was then used to create a

vertical working space for lowering and working of

the SPT hammer for obtaining the alluvium sample.

The rope for pounding the hammer for sample

collection was marked at 0.5 m, 1.0 m, 1.5 meter and

2.0 m using red cotton ribbons. Water from collected

alluvium from the hammer was drained and about

200 gm of alluvium was collected in the pre-marked

sample bags.

Alluvium soil samples from six locations in each of

the four aquatic strata were collected using a

Standard Penetration Test (SPT) hammer sampler (IS : 9640 1980). The loose alluvium consisting mostly

of silt and fine sand and did not allow undisturbed

sampling.

Three soil samples representing five alluvium depths

of each stratum were prepared. Sixty samples

representing the four strata at five depths were lab

tested. The carbon for the 2.5 m sediment column

was calculated by multiplying the mean carbon

proportion reported for each stratum for the

representative depth segment. Bulk dry density of

sample as calculated in the laboratory was used in

calculations. Carbon Estimation of lake waters: As per the USGS

publication Methods for Assessing Carbon Stocks,

Carbon Sequestration, and Greenhouse-Gas Fluxes

of Aquatic Ecosystems the lake water carbon is

contained as Dissolved Inorganic carbon(DIC),

Dissolved Organic carbon (DOC), and Particulate

Inorganic carbon (POC) (Zhu, et al. 2010).

The estimation for dissolved carbon Dioxide in the

lake was based on the Soor Sarovar’s mean water pH

and alkalinity values collected and analyzed between

September 2014 to July 2015 at The Academy of Environmental Biology, India. (Gopal, Verma &

Tripathi 2015).

Carbon dioxide values were calculated for the given

pH and Alkalinity following method elucidated in the

Southern Regional Aquaculture Center Publication

468 carbon Dioxide in Fish Ponds(John Hargreaves

and Martin Brunson 1996). Charts for various water

alkalinities showing the variation of free Carbon

Dioxide with pond water pH have been provided.

Step 1 involved drawing a straight line up for the

measured pH to the curved line representing the total

alkalinity value of the pond. Another straight line extended (Step 2) to the left-hand axis indicated the

free Carbon Dioxide.

Calculations for dissolved and particulate organic

matter in the lake water was determined based on the

reported values in similar physiochemical parameters

and climate of pond waters at Central Inland

Fisheries Research Institute, Karnal by (Singhal,

Swarn Deep & Davies 1986).

The fish and water birds are also an essential part of

the aquatic system and their biomass estimation has

been based on the archives data of the Uttar Pradesh Forest department and through local information

gathering. Water bird and fish biomass has been

converted to carbon by multiplying the carbon

fraction @ 18% as per the details noted from(Emsley

1988). Due weights for residence at SSBS has been

accounted for migratory birds.

264 ASHUTOSH KUMAR PATHAK, J.V.SHARMA AND PRIYANKA TIWARI

RESULTS AND DISCUSSION

Fig. 2:Visualises the study area coverage categories.

Figure-2: Study Area Land Cover

Strata Areas:Table 1 provides areas for each strata in ha.

Table 1. Stratificationareas at soorsarovar bird sanctuary

Soor Sarovar Bird Sanctuary Area 799 ha

Terrestrial 563 ha Aquatic 236 ha

Barren Scrub Open Mod

Dense

Very

Dense

Bank Shallow Modeep Deep

21 105 169 247 17 26 77 66 67

The figure 3 compares the estimated areas of land categories at Soor Sarovar Bird Sanctuary.

Legend:T1_BAR: Terrestrial Barren areas;T2_Scrub

areas;T3_OF: Terrestrial Open forest areas; T4_MD Terrestrial

moderately dense forest areas; T5_VD:Terrestrial Very Dense

forest areas

W1_Bank: Aquatic lake bank areas; W2_Shallow: Aquatic

shallow depth water areas; W3_MD: Aquatic lake mid-depth

water areas;W4_Deep: Aquatic lake deep depth water areas

Fig. 3:Soorsarovar bird sanctuary area pattern

While the Moderately Dense forest with an area of

247 ha was estimated to form the maximum of the

terrestrial forest, shallow waters (77 ha) were the

largest size of the aquatic areas. The Very Dense

forest (17 ha) and Bank (26 ha) areas respectively

formed the least of the terrestrial and aquatic areas.

Carbon Densities: The respective carbon densities

represented as t/ha were estimated as shown in the

figure 4.

71%29%

AREAS

Terrestrial

Aquatic

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 265

Fig. 4: Carbon stock densities in various terrestrial and aquatic categories

The MidDeep and Deep Aquatic strata with more

than 450 t/ha carbon stock were estimated way ahead

of the very dense terrestrial carbon density. The

highest carbon density in the terrestrial forest was

calculated as 110 t/ha. The areas categorised as Barren and Bank had the least density for terrestrial

and aquatic categories. It is worth noting that the

carbon density even in the least of an aquatic

category was 1.3x more than the maximum terrestrial

carbon density of the very dense forest.

The average aquatic carbon density was estimated

more than three times the average terrestrial density. Figure 5 shows the carbon stocks at SSBS.

Fig. 5:Charts showing carbon stocks at Soor Sarovar Bird Sanctuary

The carbon and their values were calculated as per

the social cost of carbon dioxide of $86 per tCo2 as

the social cost of carbon for India [27] in each of the

strata is depicted in the figure 6.

Fig. 6:Social cost of carbon of Soor Sarovar Bird Sanctuary

266 ASHUTOSH KUMAR PATHAK, J.V.SHARMA AND PRIYANKA TIWARI

Comparing results with other similar Forest type in

ISFR 2017: According to Champion and Seth

classification, the SSBS falls under Northern

Tropical Dry Deciduous Forests (subgroups 5 B:

5/E1 and 5/E2) and Northern Tropical Thorn Forest

(sub-group 6B) [28]. The figure 7 compares the

carbon densities at SSBS in comparison with the

carbon Density estimated in the ISFR Report 2017 in

comparative forest type.

Fig. 7:Carbon stock (tonnesC / hectare) as per ISFR 2017in the comparative forest types and as estimated for

SSBS

The average above ground biomass carbon densities

at Soor Sarovar Bird Sanctuary for the Very Dense

Forest were estimated markedly higher as compared

with national figures for Tropical Dry Deciduous

Forests. The statistics for Moderately Dense Forests

were slightly higher. Nevertheless, the above ground

carbon Statistics for this protected bird sanctuary are

much higher than the national average for Tropical

Thorn Forest. The statistics for Soil Organic carbon were estimated

to be lower than both the Tropical Dry deciduous and

Tropical Dry Evergreen Forests. It may be due to

Bird Sanctuary's recent origin and indicate a high

potential for carbon sequestration.

The Above Ground Biomass carbon density for

SSBS's Scrub forest category of 13.72 t/ha is

comparable to the national statistics of Tropical

Thorn Forests Very Dense Forest category which is

13.30 t/ha.

The national statistics for aquatic areas are not published in the ISFR. However, the reported

average carbon density of 110 g of carbon per kg of

soil for tropical aquatic sediments [29] is an order of

magnitude higher than the estimated carbon average

of 4.79 grams of carbon per kilogram of soil for

SSBS.

Limitations and opportunities: The size of grid

25mX25m limits the precision of the demarcation of

strata and study area boundary, but the deviations in

the measurements occur on the either (plus or minus)

side and are thus noncumulative. The innovative

deployment of the commonly used Excel spreadsheet

application, however, liberates the process from the

steep learning curve of deploying an expensive

professional GIS software. It also makes the study

process very transparent which is an essential

requirement of NDC implementation.

The study, synchronous with the national policies integrates new mobile geolocation and simple excel

map and visualisation techniques into a practical

microscale measurement solution. The methodology

evolved is simple enough to be clearly understood

and implemented by the field staff for its replication

in other areas. Geolocation with mobile and

visualisation through spreadsheet technologies are

expected to simplify the process further and

democratise the difficult research process to bring it

within reach of an ordinary forester.

Soil Degradation: Besides a rainfall range of 300 to 600 mm, the human actions and landforms are

considered as critical parameters of predictability of

land desertification [27]. The results showing a vast

range of carbon densities and their dramatic spatial

variation at Soor Sarovar Bird Sanctuary corroborate

this. The temporal process of a barren area creation

due to recent anthropogenic disturbance was also

established through historical imagery as shown in

the figure 8.

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 267

Fig. 8: Temporal process of barren area creation at Soor Sarovar Bird Sanctuary

Other important ecosystem services, conflict of

Interests and Synergy: Ecosystem Services are the

various benefits that human beings get from functioning ecosystems [28]. Other essential

ecosystem services (not measured) besides measured

carbon stock at SSBS are enumerated below.

1.Biodiversity (Bird Habitat)

2.Water Provision

3.Weather & Climate Change Mitigation

4.Ecotourism

5.Meaningful Employment

6.Cultural Heritage

7.Erosion and Sedimentation Control

There is strong theoretical and empirical evidence

that these ecosystem services support each other. Globally there is a generally positive relationship

between carbon stocks and biodiversity (Hicks et al.

2014).

Conclusion and further research needs: The

relationships amongst these services are complex.

However, as study visualisation and results at SSBS

indicate, lesser anthropogenic disturbance and better

forest management are likely to enhance all the

services. Forest Management Plan for SSBS,

however, points to a conflict in the provision of

water to Mathura Refinery which requires deeper water for enhancing the reservoir capacity and the

birdlife which thrives on shallower waters. Synergy

in the two can be thought by increasing the lake area

by extending it to the newly emerged barren areas

and appropriate peripheral plantations (which as

indicated by historical imagery is a product of

anthropogenic pressure of forest degradation and

topological disturbances of nearby constructions). It

is likely to enhance the biodiversity and carbon stock

as also all other ecosystem services. The

recommendation, however, would be to go for a test

case first as complex relationships in nature sometimes defy common sense (Lewis Michael,

2003).

A scenario assuming conversion of barren areas into

shallow waters and upgrading of 30% forest types to

the next level up along with an increase of 5% in

aquatic carbon densities up to 2030 would result in

adding up of 22,500 t (15%) of carbon within the

sanctuary area. This is about 12 times the national

average required for meeting a target of 3 billion tons

of additional carbon dioxide equivalent storage.

However, only 5000 t (4%) carbon would be added in a scenario involving the routine approach resulting

in the status quo of the barren areas and modest

growth of 10% upgradation in the forest stratum. A

situation where the random urban growth is not stopped, barren areas are likely to increase further, is

the worst possible scenario.

ACKNOWLEDGEMENT

The authors thank the Chief wildlife warden of U.P.

Forest for granting permission for research and all

Officers and staff of Forest Department at Soor

Sarovar Bird Sanctuary for sharing archival data,

useful suggestions and insights.

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*Corresponding Author

________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 269-275. 2020

PRECLINICAL STUDY OF HEALING EFFECT OF METHANOLIC EXTRACT OF

CORIANDRUM SATIVUM IN WOUNDS OF AN ANIMAL MODEL OF DIABETES

Flor Rivera-Barbosa1, Reyna Hernández-Ramos

1, Alejandro Hernández-Herrera

1, Irais

Castillo-Maldonado1, Mario-Alberto Rivera-Guillén

1, Rubén García-Garza

2, Dealmy

Delgadillo-Guzmán3, Agustina Ramírez-Moreno

4, María-del-Carmen Vega-Menchaca

5, Sergio-

Everardo Velázquez-Gauna6, Luis-Benjamín Serrano-Gallardo

1 and David Pedroza-Escobar

1*

1Department of Biochemistry, Biomedical Research Centre, Faculty of Medicine, Universidad

Autonoma de Coahuila Unidad Torreon, Torreon, Mexico 2Department of Histology, Faculty of Medicine, Universidad Autonoma de Coahuila Unidad Torreon,

Torreon, Mexico 3Department of Pharmacology, Faculty of Medicine, Universidad Autonoma de Coahuila Unidad

Torreon, Torreon, Mexico 4Faculty of Biological Sciences, Universidad Autonoma de Coahuila Unidad Torreon,

Torreon, Mexico 5Faculty of Chemical Sciences, Universidad Juarez del Estado de Durango, Gomez Palacio, Mexico

6Department of Embryology, Faculty of Medicine, Universidad Autonoma de Coahuila Unidad

Torreon, Torreon, Mexico

Email: dpedroza@uadec.edu.mx,lserranogallardo@uadec.edu.mx

Received-18.05.2020, Revised-31.05.2020

Abstract: People with Diabetes Mellitus often use medicinal plants to treat this metabolic disease that frequently reports complications, such as impaired wound healing. Coriandrum sativum has a wide range of healing properties: antibiotics, antifungals, hypoglycemics and antioxidants to name a few. However, no studies have been conducted on its potential as a wound healing agent. So, the objective of this work was to determine the wound healing effect of the methanolic extract of C. sativum seeds in reducing the closing time of surgical lesions in Long Evans black rats induced to a diabetes model with

alloxane. Material and methods: Toxicity tests were performed using the Artemia salina model and phytochemical test were conducted to determine the composition of the extract. The Diabetes model was induced with alloxane and wound was done with a biopsy punch. During the experiment, 6 groups of 5 rats each were included and the diameter of the wound was measured at days 0, 7, 14 and 21. At the end of the observation period, the animals were sacrificed and histological analysis of the wound skin was performed. Results: The alloxane treated group (diabetes model) had delayed wound healing. The group treated with the extract at a concentration of 2000 µg/mL presented wound closure on day 16 and histological characteristics similar to normal tissue of the control group. Conclusions: C. sativum methanolic extract accelerated wound healing, which was confirmed by histological analysis.

Keywords: Diabetes Mellitus, Coriandrum sativum, Scarring effect, Hyperglycemia, Healing effect, Wound healing

INTRODUCTION

he skin is the outer tissue covering and the largest organ of the body with important

protective and immunological functions (Abbas et

al., 2018). It acts as a protective barrier that isolates

the organism from the external environment,

protecting against pathogens and water loss, and

helping to keep its structures intact, it also works as a

communication system with the environment and is

one of the main sensory organs, it contains nerve

endings that act as touch, pressure, pain and

temperature receptors (Rojas-Espinosa, 2017). The

skin is made up of three layers: 1) epidermis, 2) dermis, and 3) hypodermis. The epidermis varies in

thickness according to its location from 30 μm in the

eyelids to 1.5mm in the palms of the hands with an

average of 0.4mm. The epidermis is divided into 5

strata: corneum, lucidum, granulosum, spinosum, and

basale (Gantwerker & Hom, 2011). The most

abundant cells in the epidermis are the keratinocytes

that reach a proportion of 95% located mainly in the

stratum basale (Regueiro-González et al., 2011). The dermis is the layer underlying the epidermis, it

comprised mainly lymphatic and blood vessels,

follicles, apocrine and eccrine glands. The deeper

layer, the hipodermis contains conjunctive tissue,

lymphatic and blood vessels, adipocytes, and

cutaneous nerves (Zomer & Trentin, 2017). Any

damage to the skin regardless of deepness requires

wound healing to repair the damage (Pazyar, et al.,

2014). Wound healing is a progressive dynamic

process that is divided into four overlapping but

distinct phases: 1) hemostasis, 2) inflammation, 3) proliferation, and 4) remodeling. This process

involves the participation of different molecules and

cells types (Nguyen & Soulika, 2019).

The hemostasis phase occurs in the first moments

after damage to the skin. During this phase clot

forms to prevent further blood loss through an active

T

RESEARCH ARTICLE

270 DAVID PEDROZA-ESCOBAR et al.

participation of platelets, vasoactive substances, and

an infiltration of leukocytes, red blood cells,

keratinocytes, fibroblasts, and plasma proteins

(Ridiandries et al., 2018). The inflammation phase

occurs in the first minutes and until the wound is

resolved. During this phase there is an infiltration of neutrophils, macrophages and lymphocytes to the site

of the damage and they are mainly responsible for

eliminating cellular debris and microorganisms that

may be present (Boniakowski et al., 2017).

The proliferation phase consists mainly of damage

repairing through reepithelization and extracellular

matrix production. Both stages are characterized by

the proliferation and infiltration of keratinocytes and

stem cells to repopulate the stratum basale (Eming et

al., 2014). Angiogenesis, the formation of new blood

vessels from pre-existing blood vessels, is important

during the phases of inflammation and proliferation (Okonkwo & DiPietro, 2017). Finally, the

remodeling phase is characterized by a

reorganization of the collagen matrix. The failure of

these phases promotes pathologic wound healing

such as the development of chronic non-healing

wounds. Multiple intrinsic and extrinsic factors affect

this process, especially those affecting the immune

system such as medication use or disease (Cohen et

al., 2016).

Poor wound healing is associated with the most

common metabolic disease: Diabetes mellitus (Schmidt, 2018). It is not clear to what extent

impaired healing is due to direct effects of

hyperglycemia, insulin deficiency, angiogenesis

alteration or an excess of inflammation (Guthrie,

2004). For instance, inflammation affects the wound

from progressing to the proliferation phase leading to

chronic non-healing wounds (Kautzky-Willer et al.,

2016). On the other hand, the most common clinical

indication of impaired wound healing associated with

diabetes is the diabetic skin ulcer where inadequate

local angiogenesis is considered a very likely

contributor (Eming et al., 2014). Diabetic skin ulcer are painful sores with disintegration of dermal tissue

mainly epidermis and dermis.

Wound closure is greatly delayed in diabetes and it is

associated to impaired angiogenesis and the chronic

presence of inflammation as previously stated. Due

to the fact that diabetes affects a high proportion of

the world population; besides the fact that, poor

wound healing is associated with diabetes; and

considering the fact that, coriander seeds are

attributed medicinal properties against diabetes and

wound healing (Laribi et al., 2015; Muniandy et al., 2019; Silva & Domingues, 2017; Wei et al., 2019).

The aim of this study was to evaluate the healing

effect of methanolic extract of Coriandrum sativum

seeds in wounds of an animal model of diabetes.

MATERIALS AND METHODS

Biological material

All protocols used in this study were approved by the

Bioethics committee of the Faculty of Medicine,

Universidad Autonoma de Coahuila Unidad Torreon

(reference number CB071017).

Thirty Long Evans black male rats with an age of 12

weeks old, weighing 200-250 grams were used. The animals were divided into six groups of five rats

each. The animals were housed in acrylic rat cages

using sawdust as bedding with stainless steel grill

covers. Water and food were offered ad libitum. The

environmental parameters were monitored by means

of a temperature and relative humidity meter. The

photoperiod was 12 hours of light and 12 hours of

dark.

The samples of Coriander (Coriandrum sativum L.)

seeds were obtained from a local market in the city

of Torreon, Mexico. An amount of 100 g was washed

with water and grindered in a manual mill. The extract was prepared with the macerated infusion of

methanol at room temperature (25+ 2 °C) in a 1:4

ratio for 24 h with constant stirring at a speed of 60

rpm. Subsequently the supernatant was filtered on

Whatman No. 40 filter paper and the solvent was

evaporated under reduced pressure on a rotary

evaporator (Buchi R-210) at a temperature below

60°C and the extract was subjected to complete

desiccation in a hot air oven at 40°C. Subsequently, it

was collected with a stainless-steel spatula and stored

in an amber glass bottle at -20 °C; and dilutions at 10, 100 and 1000 µg/mL were prepared.

Biotoxicity assay with the Artemia salina model

To evaluate the biotoxicity of the extract, the in vivo

biotoxicity assay with the Artemia salina model was

used. The Artemia salina was cultivated by placing

0.01 g of Artemia salina eggs in artificial seawater

(40 g of sea salt in one liter of distilled water) with

0.06 g of yeast extract. This mixture was placed in an

artemia chamber at a temperature of 28°C for 48

hours for the eggs to hatch. Once the eggs of Artemia

salina hatched, a standard curve of the extract to be

evaluated at a concentration of 0, 1, 10, 100, 250, 500, 1000, 5000 μg/mL was prepared in enough

seawater for 10 mL. A sample of Artemia salina

(N=10) was added in triplicate in test tubes for each

of the concentrations under study. Potassium

dichromate was used at 1000 μg/mL in seawater as a

positive control. During this assay, the samples were

incubated at 28°C for 24 hours; subsequently, live

and dead Artemia salina larvae were quantified, and

the lethal dose 50% (LD50) was estimated by Probit

regression.

Phytochemical tests These tests were qualitative to identify the main

chemical groups of organic compounds present in

plant extracts. The principle of these tests based on

chemical reactions between the functional chemical

groups of organic compounds present in plant

extracts and chemical reagents that led to the

formation of precipitates or colored substances. For

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 271

the following tests, a standard solution of 10 000

μg/mL concentration was used.

Alkaloids (Dragendorff and Mayer’ Reagents)

This test based on the presence of nitrogen in the

alkaloids which reacted with reagents containing

bismuth or mercury and formed insoluble iodides of color bright yellow. For this test, 1 mL of the

solution to be evaluated was placed in three test

tubes, 1 drop of concentrated hydrochloric acid was

added to each tube, the sample was then heated

gently and the test tubes were left to cool. Then one

drop of the Dragendorff reagent [Bi(NO3)3:5H2O 8%;

HNO3 20%; KI 1.6M], Wagner and Mayer [KI 5%;

HgCl 0.05M] was added. The development of a

bright yellow color indicated the presence of

alkaloids. An atropine solution was used as a positive

control (Sigma Aldrich St. Louis, MO) and distilled

water as a negative control.

Aldehydes (Tollens’ Reagent)

This test involved the oxidation of the aldehydes to

the corresponding carboxylic acid, using a 5%

ammoniacal silver nitrate solution. The positive test

consisted of the formation of a silver mirror or a

black silver precipitate. For this test, 5 drops of 5%

silver nitrate, 1 drop of 2N sodium hydroxide and 3

drops of 10% ammonium hydroxide were placed in a

test tube. Until this moment the solution was

transparent, then 1 mL of the standard solution to be

evaluated was added. A glucose solution was used as a positive control (Sigma Aldrich St. Louis, MO) and

distilled water as a negative control.

Carbohydrates (Brady’ Reagent)

This reaction based on Brady’s Reagent (with the

reactant 2,4-dinitrophenylhydrazine) that quickly

formed 2,4 dinitrophenylhydrazones with aldehydes

and ketones, yellow or red pigments. For this test 1

mL of the standard solution was placed in a test tube

and 8 drops of 2,4-dinitrophenylhydrazine 20% were

added in concentrated sulfuric acid, plus 3 drops of

70% ethanol. The formation of a red or yellow color

indicated the presence of aldehydes or ketones. Glucose and fructose solutions were used as positive

controls and distilled water as a negative control.

Flavonoids

This test based on the formation of pigments by the

reaction that occurred between the

gammabenzopirone ring with hydrochloric acid and

Magnesium. For this test, 1 mL of the standard

solution to be evaluated was placed in a test tube, a

piece of Magnesium metal (10 mg) and 2 drops of

concentrated hydrochloric acid were added. The

formation of a red or blue color indicated the presence of flavonoids. A catechin solution was used

as a positive control (Sigma Aldrich St. Louis, MO)

and distilled water as a negative control.

Sterols (Liebermann-Burchard’s Reagent)

This test based on the reaction that occurred between

the steroid rings with acetic anhydride with the

formation of green or blue pigments. For this test, 1

mL of the standard solution to be evaluated was

placed in a water bath of 50 °C until the solvent

evaporated completely, the sample was solubilized in

2 mL of acetic anhydride and cooled in ice, then 3

drops of concentrated sulfuric acid were added. The

formation of a green or blue color indicated the

presence of the steroid ring. Vitamin D was used as a positive control and distilled water as a negative

control.

Tannins

This test based on the tannins property to form

precipitates of urea-soluble proteins which form

pigments with ferric chloride. For this test, 1 mL of

the standard solution to be evaluated was placed in a

test tube, 1 mL of a solution of gelatin 1% in

physiological saline solution was added, and

afterwards the sample was centrifuged at 3500 rpm

for 5 minutes. The precipitate was resuspended in 1

mL of 10M urea, and then 3 drops of 5% ferric trichloride were added. The formation of a blue color

indicated the presence of tannins. A tannic acid

solution was used as a positive control (Sigma

Aldrich St. Louis, MO) and distilled water as a

negative control.

Terpenoids

For this test, 1 mL of the standard solution to be

evaluated was placed in a water bath at 50°C until

the solvent evaporated in its entirety, 1 mL of a

solution of glacial acetic acid and sulfuric acid [1:1]

was added, then 1 mL of chloroform was added. The formation of a red or blue color indicated the

presence of terpenoids. An ursolic acid solution in

DMSO was used as a positive control (Sigma

Aldrich St. Louis, MO) and distilled water as

negative control.

Quantification of total phenolic compounds (Folin

Ciocalteu method)

A sample of 150 μL of standard solution or sample

was mixed with 150 μL of Folin Ciocalteu 0.2 N

reagent (Sigma Aldrich St. Louis, MO). The mixture

incubated at room temperature and left in the dark for

5 minutes, and the reaction was stopped with 300 μL of 0.35 M sodium hydroxide solution. The

absorbance was measured on a UV

spectrophotometer (Spectronic 20 Genesys) at a

wavelength of 760 nm. This result was extrapolated

in a standard curve with concentrations of 0, 2, 4, 8,

10, 15, 20, 30 and 50 μg/mL of gallic acid (Sigma

Aldrich St. Louis, MO).

Experimental procedures

The animal model of diabetes was induced by means

of intraperitoneal administration of alloxane (3

doses) 125 mg per kg-weight until reaching a glucose concentration over 300 mg/dL; blood glucose was

measured, with an Accu-check glucometer, during

the induction period and one week after reaching the

300 mg/dL threshold. The experimental animals

underwent a circular wound on the back with a 1.5

cm2 biopsy punch 2 mm deep. The wound was

measured on days 0, 7, 14 and 21, in which glycemic

record was also kept. The Coriander treatment was

272 DAVID PEDROZA-ESCOBAR et al.

administrated via topical route on days 0, 7 and 14. It

consisted of 500 L of methanolic coriander seeds extract at concentrations of 1000, 2000 or 4000

g/mL prepared in a 1.6% carboxymethyl cellulose (CMC) solution with phosphate-buffered saline

(PBS) as diluent. The healing percentage was

determined using the following formula:

Healing percentage =

Wound areaDay 0 − Wound areaDay N (100)

Wound areaDay 0

The animal groups were as follows: 1) Control group

(without any treatment); 2) Alloxane treatment; 3)

Alloxane and CMC/PBS treatment; 4) Alloxane and

extract (1000 µg/mL) treatment; 5) Alloxane and

extract (2000 µg/mL) treatment; and 6) Alloxane and

extract (4000 µg/mL) treatment.

Histological analysis Animals were sacrificed by cervical dislocation;

subsequently, an elliptical incision was made which

covered the area of the healing process. The samples

were dehydrated and embedded in paraffin to make

microtome cuts 5 µm thick subjected to hematoxylin

and eosin (HE) and Masson's trichrome (MT) stains

for analysis.

Statistical analysis

The variables of the phytochemical tests were

nominal. The rest of the variables were continuous

and they were described with means and standard

deviation. ANOVA and posthoc Dunnet test were

used to evaluate the difference of means among study groups; linear regression and Probit regression

were calculated with IBM SPSS 21 and

GraphPadPrism 6 software.

RESULT AND DISCUSSION

Biotoxicity assay with the Artemia salina model

Based on the results of the biotoxicity assay with the

Artemia salina model, a LD50 of 5424.82 μg/mL

(95%CI 4365.73-6483.90) was calculated. Therefore,

we proceeded to evaluate the coriander seeds extract

at concentrations lower than the LD50 that were 1000, 2000 and 4000μg/mL.

Phytochemical tests

The phytochemical tests of the coriander seeds

extract showed the presence of flavonoids, tannins

and terpenoids as seen in Table 1.

Table 1. Phytochemical tests of the methanolic extract of Coriander seeds.

Phytochemical test Result

Alkaloids -

Aldehydes -

Carbohydrates -

Flavonoids +

Sterols -

Tannins +

Terpenoids +

+ Positive. – Negative.

Scarring analysis

After the establishment of the diabetes model

through the application of intraperitoneal alloxane,

the surgical wound was performed under general

anesthesia supervised by the veterinarian in charge of

the Faculty's bioterium. The wound healing progress

was measured on days 0, 7, 14 and 21 as shown in

Figure 1. Scarring analysis among animals showed complete wound closure by day 21 in all study

groups but group 2 with only alloxane treatment

which is the control group for the diabetes model.

Wound closure was carried out more quickly in the

groups with coriander treatment, especially quick in

group 5 at a 2000 µg/mL concentration. Statistically

significant differences (p<0.05) were found by

ANOVA test as shown in Table 2 among healing

percentages of study groups. Posthoc Dunnet test

showed statistically significant differences (p<0.01)

among all the measures on days 0, 7, 14 and 21 of

the coriander treatment at a 2000 µg/mL

concentration. Even though, the three groups

receiving any coriander treatment showed

statistically significant differences (p<0.01) on day

21, the mean of days for full epithelization was 17.4,

16.2 and 18.4; respectively, from lower to highest

coriander seed extract concentration. The results for both healing percentages and days for full

epithelization indicated the best concentration of

extract for treatment at 2000 µg/mL.

In contrast, on day 21 of observation the wound in

the group 2, with only alloxane treatment which is

the control group for the diabetes model, had not

completely healed. The group 3 treated with alloxane

and CMC/PBS showed statistically significant

differences (p<0.05) on days 7 and 14. However, full

epithelization was not reached by day 21.

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 273

Table 2. Healing percentage and mean of days for full epithelization among study groups.

Day 4 (%) Day 7 (%) Day 14 (%) Day 21

(%)

Full epithelization

(Days)

GROUP I 16.13 + 2.46 28.13 + 5.14 80.39 + 1.80 100 + 0 19 + 0.7

GROUP II 10.26 + 7.90 17.99 + 5.33 71.19 + 5.7 97.86 +

1.09

20.8 + 0.44

GROUP III 26.65 + 3.61* 33.99 + 4.34 77.06 + 5.7** 99.86 +

0.29

19.8 + 1.09

GROUP IV 26.65 + 3.87 42. 06 +

2.83**

79.71 + 6.98 100 + 0** 17.4 + 0.54

GROUP V 31.59 +

6.35**

43.06 +

5.13**

94.93 +

1.97**

100 + 0** 16.2 + 0.38

GROUPVI 14.06 +

2.85**

26.19 + 2.76* 79.19 +

5.62*

100 + 0** 18.4 + 1.23

Results are expressed as means and + standard deviation. p values <0.05 and <0.01 were considered

statistically significant. Dunnet Test *.

Histological analysis

At the end of the 21-day observation period, the

animals were sacrificed and samples were obtained

from the area of injury for analysis. Two different

stains were performed: Hematoxylin-Eosin and

Masson's Trichrome, which are presented in Figure

2. In general, all groups presented a keratinized

stratified flat epithelium (white arrow). In the case of

Group I (A), the characteristics of the epithelium

were normal, with abundant hair follicles in transverse and longitudinal sections in the dermis

(purple arrow), little inflammatory infiltrate, and

irregular dense connective tissue (yellow arrow and

lower box 40x). With Masson's Trichrome stain, the

irregularly arranged collagen fibers were shown in

blue. Group II (B) presented a thinned epithelium in

the peripheral area of the lesion with the absence of

keratin in the central area. Absence of hair follicles

was observed in the dermis of the injured area with

irregular dense connective tissue and a moderate

inflammatory infiltrate. Irregular dense connective tissue was observed using Masson's Trichrome stain.

Group III (C) showed an epithelium of normal

characteristics at the ends of the lesion area with

thinning in the center and absence of keratin and hair

follicles, as well as abundant vascular congestion

(red arrow) and irregular connective tissue with the

presence of an infiltrate (lower box 40x). Moderate

inflammatory infiltrate was observed. Masson's

Trichrome staining revealed irregular connective

tissue. Group IV (D) presented a decrease in the area

of scarring and moderate fibrosis compared to the

groups described above. Mild inflammatory infiltrate was observed. Using Masson's Trichrome stain, it

was possible to visualize moderate fibrosis. Group V

(E) presented an epithelium with characteristics

similar to non-injured tissue with areas of chronic

infiltrate and mild vascular congestion, along with

some hair follicles and irregular connective tissue.

Masson's Trichrome stain shows connective tissue of

irregular disposition which agrees with the normal

histological description of the dermis. Group VI (F)

shows an epithelium with some areas with no keratin

and few hair follicles, irregular connective tissue, and the inflammatory infiltrate is moderate. Masson's

Trichrome stain shows irregular connective tissue.

Day 0 Day 4 Day 7 Day 14 Day 21

Group

I

Group

II

Group

III

274 DAVID PEDROZA-ESCOBAR et al.

Group

IV

Group

V

Group

VI

Fig. 1. Photographs of macroscopic wound healing progress among study groups.

Figure 2. Skin photomicrographs of the study groups: Groups I-VI from A to F. Main figure stained with 10x HE, the upper and lower boxes were observed at 40x and were stained with HE and MT, respectively.

CONCLUSION

The methanolic extract from coriander seeds was

shown to be non-toxic based on the biotoxicity assay

with the Artemia salina model. Among the

experimental groups, those that were treated with the

extract presented faster and better healing based on

histological analysis. This could be largely due to the

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 275

phytochemical compounds in the extract, since their

properties would help decrease the duration of

inflammation, and stimulate the production and

viability of collagen fibers. The phytochemical

compounds flavonoids, tannins and terpenoids seems

to favor the elimination of free radicals and decrease oxidative stress damage leading to an improvement

in wound healing.

ACKNOWLEDGMENT

The authors thank to the Consejo Nacional de

Ciencia y Tecnología (CONACyT) for the

scholarship given to FRB in order to develop his

graduate studies. To the program “Fondo Destinado a

Promover el Desarrollo de la Ciencia y la Tecnologia

en el Estado de Coahuila (FONCYT)” and its

“Convocatoria COAH-2019-C13” for supporting the project COAH-2019-C13-C058 and for the

scholarship given to AHH. The authors thanks to the

veterinarian Alfonso Zambrano Martínez for the

support provided to the care of the animals.

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276 DAVID PEDROZA-ESCOBAR et al.

*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 277-281. 2020

SEED GERMINATION BEHAVIOUR OF CANNABIS SATIVA L. UNDER

DIFFERENT TEMPERATURE REGIMES

Birendra Kumar1*, S. Zaidi

1, Vagmi Singh

1, K.T. Venkatesh

2, Govind Ram

1, A.K. Gupta

3,

Narendra Kumar4 and A. Samad

5

1Seed Quality Lab on MAPs, GPB Division,

2CSIR-CIMAP Resource Centre, Pantnagar, US Nagar,

3GRM Department, GPB Division,

4Botany and Pharmacognosy Department,

5Plant Protection Division,

Council of Scientific and Industrial Research-Central Institute of Medicinal and Aromatic Plants

(CSIR-CIMAP), P.O. CIMAP, Lucknow-226015, India

Email: b.kumar@cimap.res.in; birendrak67@gmail.com

Received-01.05.2020, Revised-22.05.2020 Abstract: Cannabis sativa L. (Cannabaceae) is one of the earliest cultivated plant, containing many of the valuable natural components useful for health as well as livelihood. Cultivation of Cannabis is done by sowing its seeds in the field provided with favourable physical and chemical parameters for germination. In this study, optimum temperature and time required for germination of Cannabis seeds collected from Kausani, Uttarakhand have been studied at various temperatures under the controlled laboratory conditions. The percentage of germination, germination energy and seedling vigor index I and II was reported maximum at a constant temperature of ‘25˚C’ with having 3rd-4th and 6th day as its first and final count day, respectively. Therefore, it is suggested to the researchers/cultivators to raise the nursery of Cannabis sativa L. seed at ‘25˚C’

to achieve healthy and maximum seedlings of the crop.

Keywords: Hemp, THC, CBD, Germination potential, Seedling vigor

INTRODUCTION

annabis sativa L. (Fam. Cannabaceae), an

annual herb, native to eastern Asia is cultivated

worldwide having medicinal and recreational

properties due to the presence of more than 100

active chemical constituents viz. Cannabidiol (CBD), Tetrahydrocannabinol (THC), Cannabinol (CBN),

Tetrahydrocannabivarin (THCV), THCa, and

cannabidiol terpenes, etc. (Sera et al., 2018). Being a

good source of fibre, it can be used in paper, cotton,

biodegradable plastics, paints and bio-fuel industries

(Keller, 2013; Johnson, 2019; Fortenbery and Mick,

2015). Major cultivated areas for Cannabis

production in the world are Europe, Canada and

China (Huaran et al., 2018). One third to half of the

total Cannabis cultivated area of the world is

occupied by China (Yan, 2014; Salentijn et al.,

2015). Under section 10 of The NDPS Act, 1985 in India, under section 41 of UP Excise Act 1910 (UP

Excise Rule, 2018) and section of 14 of The NDPS

Act for hemp cultivation rule in Uttarakhand

(Uttarakhand Hemp Cultivation Rule, 2016-17) a

proper licence required from state excise department

for the cultivation of Cannabis for medicinal and

scientific purposes (The NDPS Act, 1985; Official

Gazette of UP, 2018). Government of India, UP state

excise department and Uttarakhand state excise

department permits the cultivation of only those

varieties/genotypes of Cannabis which have less than

0.3% THC and higher content of CBD (The NDPS

Act, 1985; Official Gazette of UP, 2018).

Dioecious Cannabis herb can be cultivated through

seeds in the field. Seed germination potential is a

very important aspect for the successful

establishment of seedling in the field and commercial

cultivation of Cannabis crop. Germination of Cannabis seed is tested under the controlled

condition of the laboratory by examining the

emergence and development of seedling where the

condition of its essential structures (root system,

shoot axis, cotyledons, terminal buds) determine its

ability to grow under the favourable condition in the

field (ISTA Rule, 2010). Temperature variation

along with a number of days to counting affected the

germination percentage of Ocimum basilicum

(Kumar et al., 2012), Tagetes minuta (Kumar et al.,

2008), Cymbopogon martinii (Kumar et al., 2010)

and Artimisia annua (Kumar et al., 2013). Change in the temperature and light had also affected the

germination of lettuce seeds (Erwin, 1991.However a

very few and erratic information is present depicting

the optimum temperature and photoperiod required

for the seed germination of Cannabis sativa L. Thus,

the main motive of this study was to determine the

optimal temperature regimes and time required for

maximum seed germination potential. The results of

maximum seed germination percentage obtained in

the seed germinator under controlled laboratory

condition are accepted worldwide by seed trades and

C

RESEARCH ARTICLE

278 BIRENDRA KUMAR, S. ZAIDI, VAGMI SINGH, K.T. VENKATESH, G. RAM, A.K. GUPTA, NARENDRA

KUMAR AND A. SAMAD

its customers as indicators of field germination

(Yaklich and Kulik, 1979).

MATERIALS AND METHODS

Seed collection

The Cannabis sativa L. seeds were collected during

October, 2019 from their naturally growing habitat of

Kausani and Bageshwar regions of Uttarakhand,

India. The seeds were stored in paper bag at

‘25oC±3oC’ until the germination experimentation

was initiated.

Germination potential and seedling vigor index

During December, 2019–January, 2020 experiment

were conducted at constant temperatures of ‘15C’,

‘20C’, ‘25C’, ‘30C’, ‘35C’ and ‘40C’ at 16 h light/8 h dark daily regimes and alternate

temperatures of ‘25oC/15oC’ at 3 photo-regimes viz.16h light/8hr dark, 8h light/16h dark and 12h

light/12h dark with 60-70% relative humidity. Seeds

were placed on top of filter paper (TP) soaked with

sterile distilled water in Petri dishes (15cm diameter

3 cm deep). The experiment was arranged in a complete randomized design with six replications of

50 seeds. Germination was checked daily and

numbers of normal (bearing both root and shoot) and

abnormal (lacking either root or shoot or having

stunted growth) seedlings recorded from the first day

of counting till the day of maximum seed

germination percentage (Kumar et al., 2011).

Numbers of healthy seedlings were used for data analysis. Observation on germination percentage,

germination energy percentage, seedling vigor index

I and seedling vigor index II were recorded and

calculated (Kumar et al., 2011) as follows:

Total number of seed =

Germination percentage

------------------------------------------- x 100

Total number of seeds in all replicates

Germination energy =

¼ of maximum number of seeds germinated in a day

-------------------------------------------------------- x 100

Total number of seeds in all replicates

Seedling vigor index I = Germination (%) x

Average seedling length (cm)

From each replication, ten normal seedlings were

selected randomly at the end of the germination test,

and seedling length (root + shoot length) was

measured. Average seedling length (cm) was

calculated.

Seedling vigor index II = Germination (%) x Average seedling dry weight (g)

The same ten seedlings were placed in a paper

envelope and dried under shade for 16 h. These dried

seedlings were placed in an oven at 75C±5C for 48

h after which they were weighed to determine

average seedling dry mass (g) in each replication.

Statistical analysis

At the end of the experiment, data were subjected to an analysis of variance (ANOVA) and mean

separation. The least significant difference (LSD) at

5% level was used to compare the means of different

test parameters under different temperature

conditions.

RESULTS AND DISCUSSION

ANOVA of table 1 revealed that temperature regimes

(T), number of days to counting (D) and their

interaction were highly significant for percentage of germination (G) and germination energy (GE) while

table 2 revealed that temperature regimes was highly

significant for percentage of germination (G),

seedling vigor index I (SV-I) and seedling vigor

index II (SV-II) of Cannabis seed. Percentage of

germination (G) along with germination energy (GE)

was analysed to be varying from day to day at

different temperature regimes. At various

temperature regimes, the emergence of the radicle

was recorded during the first two days of the

experiment except at ‘40oC’ where no seed

germination was observed though out the experiment. While at 35°C, radicle and plumule

emerged on 2nd and 3rd day respectively showing

stunted growth (devoid of cotyledon) that later died

on 4th day of experiment. The appearance of both

radicle as well as plumule was firstly observed on

day 3rd at all studied temperature regimes [15oC’,

‘20oC’, ‘25oC’ (16h/8h), ‘25/15oC’ (16h/8h),

‘25/15oC’ (8h/16h) and ‘25/15oC’ (12h/12h)].The

maximum seed germination was found on day 6th at

all studied temperature regimes.

The mean percentage of seed germination and germination energy over the temperature regimes for

number of days to counting varied from 37.83 and

9.46 (‘15oC’) to 62.38 and 15.84 (‘25oC’),

respectively (Table 3). Among the studied

temperature regimes, ‘25oC’ had the highest mean

percentage of germination and germination energy

(63.38 and 15.84) and significantly different from

other temperature regimes while among the number

of days to counting, day 6th has maximum mean

percentage of germination and germination energy

(70.36 and 17.59) and significantly different from rest days of counting. Considering these two factors

simultaneously i.e. a number of days to counting and

temperature regimes, ‘25oC’ was found the best with

the maximum mean percentage of germination and

germination energy (87.17 and 21.79) and was

followed by‘30oC’ (77.33 and 19.33), ‘25/15oC

(8h/16h)’ (76.67 and 19.17), ‘25/15oC (16h/8h)’

(71.00 and 17.75), ‘25/15oC (12h/12h)’ (70.83 and

17.71), ‘20oC’ (60.17 and 15.04), and ‘15oC’ (49.33

and 12.33) at day 6th of temperature regimes (Table

3). Mean of seed germination percentage (G) was

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 279

found maximum (87.17%) at constant temperature of

‘25°C’ among the studied temperature regimes over

the number of days to counting, seemed to be

optimum temperature (Table 3). Similar observations

have also been reported by various workers in the

case of Indian basil (Kumar, 2012), sweet basil (Ramin, 2006), Holy basil (Kumar et al., 2014),

Palmarosa (Verma et al., 2012) and Kalmegh (Kumar

et al., 2011). Analogously, for a number of days to

counting, day 6th had the highest values for the

percentage of germination and germination energy

(Table 3).Variation in seedling vigor index I (SV-I)

and seedling vigor index II (SV-II) was also recorded

with the change in temperature (Table 4). Seedling

vigor I was found maximum (758.98) at ‘25/15oC

(8h/16h)’ and significantly different from other

temperature regimes except at ‘25/15°C (16h/8h)’

while seedling vigor index II (12.32) at a constant temperature of ‘25oC’ was significantly different

from other temperature regimes (Table 4). The

finding of the present study regarding maximum

seedling vigor index I at ‘25/15°C (8h/16h)’ and

reduction in its value by altering the temperature or

photoperiod suggests that on changing the

temperature and relative humidity, viability and vigor

of seed got disturbed as reported in the case of the

Ocimum basilicum L. (Kumar, 2012). In case of

maximum value of seedling vigor II at ‘25°C’ is

defended by similar findings obtained for Lens culinaris (Khatun, 2009) and Indian basil (Kumar,

2012). Seedling vigor index I (451.72) and II (6.15)

were reported minimum at a temperature of ‘20°C’

and ‘15°C’, respectively (Table 4). The lowest

seedling vigor index II at ‘15°C’ could be due to

lesser dry mass of seedling and lower value of

germination percentage similar to the case reported

for Indian basil (Kumar, 2012). Another reason for

decreased viability and vigor of seeds was because of

earlier harvesting the seeds before the

accomplishment of their physical maturity which

increases the number of seeds with relatively low embryonic development and higher content of

moisture in them as suggested in case of Lens

culinaris (Khatun, 2009) and Pisum sativum

(Matthew, 1973).

Table 1. Analysis of variance for percentage of germination (G) and germination energy (GE) in Cannabis

sativa L. under different temperature regimes (T).

Sources df

Mean Squares

G GE

Replication 5 10.79761905 0.590029762

Temperature regimes (T) 6 823.297619** 51.14236111**

Error1 12 29.91220238 1.921843998

Number of days to counting (D) 3 6019.439484** 376.8027654**

T x D 18 109.228836** 6.769345238**

Error2 42 7.800595238 0.504402282

** Significant at probability level (p ≤ 0.001)

Table 2. Analysis of variance for percentage of germination (G), seedling vigor index I (SVI) and seedling vigor

index II (SVII) in Cannabis sativa L. under different temperature regimes (T).

Sources df Mean Squares

Germination % SV I SV II

Replication 5 1.715 2459.64 0.50

Temperature regimes 6 458.76** 39307.92** 10.52**

Error 12 14.01 1939.70 0.31

Total 20 103952.68 6828087.99 1939.03

** Significant at probability level (p ≤ 0.001)

Table 3. Percentage of mean germination (G) and germination energy (GE) of Cannabis sativa L. at number of

days to counting (D) under different temperature (T) regimes.

Temperature(T) regimes

Number of Days to counting (D)

Day 3 Day 4 Day 5 Day 6 Mean

G GE G GE G GE G GE G GE

15°C (16h/8h) 28.67 7.17 34.00 8.50 39.33 9.83 49.33 12.33 37.83 9.46

20°C (16h/8h) 37.00 9.25 47.33 11.83 57.00 14.25 60.17 15.04 50.38 12.59

25°C (16h/8h) 40.67 10.17 53.67 13.42 72.00 18.00 87.17 21.79 63.38 15.84

280 BIRENDRA KUMAR, S. ZAIDI, VAGMI SINGH, K.T. VENKATESH, G. RAM, A.K. GUPTA, NARENDRA

KUMAR AND A. SAMAD

30°C (16h/8h) 28.67 7.17 44.67 11.17 67.67 16.92 77.33 19.33 54.58 13.65

25/15°C (16h/8h) 22.33 5.58 34.00 8.50 46.00 11.67 71.00 17.75 43.33 10.88

25/15°C (8h/16h) 30.00 7.50 45.33 11.33 64.00 16.00 76.67 19.17 54.00 13.50

25/15°C (12h/12h) 31.33 7.83 50.33 12.58 59.67 14.92 70.83 17.71 53.04 13.26

Mean 31.24 7.81 44.19 11.05 57.95 14.51 70.36 17.59

CD 5% for T 4.87(G) 1.23(GE)

CD 5% for D 6.52(G) 1.62(GE)

CD 5% for T×D 4.61(G) 1.17(GE)

Table 4. Percentage of mean germination (G), seedling vigor index I (SVI) and seedling vigor index II (SVII) of

Cannabis sativa L. under different temperature (T) regimes.

Temperature (T) regimes Mean germination percentage (G) SV I SV II

15°C (16h/8h) 49.33 480.50 6.15

20°C (16h/8h) 60.17 451.72 9.67

25°C (16h/8h) 87.17 520.05 12.32

30°C (16h/8h) 77.33 507.78 9.74

25/15°C (16h/8h) 71.00 582.58 9.78

25/15°C (8h/16h) 76.67 758.98 10.69

25/15°C (12h/12h) 70.83 689.90 8.93

SEM 3.06 35.96 0.45

CD at 5% 6.37 74.98 0.95

CV 5.32 7.72 5.79

CONCLUSION

Percentage of germination (G) and germination energy (GE) along with seedling vigor index II for

Cannabis sativa of Kausani accession was found

maximum at a constant temperature of ‘25°C’ with

3rd - 4th day and 6th day as its first and final count day,

respectively. Thus, from the above findings it is

suggested that to grow the seeds of Cannabis at

‘25°C’ as its optimum temperature which will be

useful for researchers/cultivators in producing

seedlings for commercial cultivation.

ACKNOWLEDGEMENT

Authors are highly obliged to the Director, CSIR-

CIMAP, Lucknow for providing necessary

infrastructure and facility; also thankful to Dr Rakesh

Kumar for statistical analysis, Revenue Department,

Ministry of Finance, Government of India, UP State

Excise Department and Uttarakhand State Excise

Department for issuing a license to cultivate hemp

for R&D activity. This study was financially

supported by Asheesh Concentrates International

LLP , Mumbai, India.

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282 BIRENDRA KUMAR, S. ZAIDI, VAGMI SINGH, K.T. VENKATESH, G. RAM, A.K. GUPTA, NARENDRA

KUMAR AND A. SAMAD

*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 283-287. 2020

PERFORMANCE OF INTERCROPS IN HYBRID MAIZE UNDER NORTH

CENTRAL PLATEAU ZONE OF ODISHA

T.R. Mohanty1 , M. Ray

2*, S.K. Sahoo

3 , K.C. Sahoo

4, N. Mishra

5 and H.K. Patro

6

1,2,3,4,5Regional Research and Technology Transfer Station [RRTTS] (OUAT),

Keonjhar, Odisha - 758002 5DPME, Orissa University of Agriculture and Technology, Bhubaneswar-751003

Email: monikarayouat@gmail.com

Received-04.05.2020, Revised-26.05.2020 Abstract: An experiment was conducted at Field Experimental Block, Regional Research and Technology Transfer Station,

Keonjhar, during Kharif season for two consecutive years of 2017 and 2018 under RKVY project to study the performance of maize based intercropping system under North Central Plateau Zone of Odisha. . The experiment was laid out in RBD design. The experiment comprised of thirteen treatments viz. T1- Maize + Cowpea (1:1), T2-Maize + Cowpea (2:2), T3-Maize + Radish (1:1), T4-Maize + Radish (2:2), T5-Maize + Cluster bean (1:1), T6-Maize + Cluster bean (2:2), T7-Maize + Arhar (1:1), T8-Maize + Arhar (2:2),T9-Maize (sole), T10-Cowpea (sole) , T11-Radish (sole), T12- Cluster bean (sole), T13-Arhar (sole). The varieties taken were: Maize-Pioneer 3396(Hybrid), Cowpea-Kasi Kanchan, Cluster bean -Pusa Navbahar, Arhar- Corg 9701 and Radish- Pusa Chetki Long. Results revealed that Maize + cowpea (1:1) proved to be the most profitable system being at par with maize + cowpea (2:2) & maize + radish (1:1 & 2:2) systems in both the years. However,

maize + arhar (1:1) returned the highest amount per rupee invested (1.78) among all the systems when number of days occupied in the field is not taken into account. Therefore for North Central Plateau Zone of Odisha cowpea and radish are the most suitable intercrops with maize in Kharif season in the above row ratios.

Keywords: Kharif, Intercropping, Maize, Cowpea, Profitable

INTRODUCTION

he state of Odisha is located in the eastern part of

India. It has 2.62 Mha of maize with a production

of 6.08 million tonnes (Mt), resulting in an average

productivity of 2,321 kg/ha (Government of

Odisha,2012) annually. Nationally, maize is cultivated on 8.78 Mha, with a production of 21.76

Mt and an average annual yield of 2,478 kg/ha

(Directorate of Economics and Statistics, 2012). In

Odisha maize is cultivated primarily in interior

districts such as Keonjhar (27,580 ha). Maize is a

staple tribal food crop and amounts to 7.4% of the

state's total food consumption .These tribal

communities constitute 23% of the total state

population (Census-2011, www.censusindia.gov.in ).

The predominant upland crop in this region is maize,

grown during the kharif season. Growing of a heavy feeder maize crop year after year mines the soil and

results in decline of fertility of the soil. Farmers

mostly use local varieties of maize crops under low

management conditions which results in low

productivity. So, the production of food grain could

be increased by adopting intercropping system.

Intercropping increases total productivity through

efficient utilization of land, labour and growth

resources (Ahmed et al., 2006). Greater productivity

in intercropping system is commonly achieved by

minimizing inter specific competition and maximizing

complementary use of growth resources (Islam, 2002). Inter-specific competition may be minimized

through judicious choice of crops (Santalla et al.,

2001). Usually plants differing in growth duration,

height, rooting systems and nutrient requirements are

considered to grow together in intercropping systems

(Reddy and Willey, 1981).

Intercropping also increases land equivalent ratio

(LER) to varying degrees (Mehta and De, 1980;

Hashem et al., 1990). Islam et al. (2004) reported that

maize and bush been exhibited similar competitiveness in simultaneous sowing and resulted

in the highest intercrop productivity in maize-bush

bean intercropping system. They suggested that two

rows of bush bean in between maize rows can be

grown by experiment was conducted in different

locations during rabi season 2005-06. Findings from

different locations showed that the highest maize

equivalent yield was obtained from Maize + Bush

bean intercropping systems at Jamalpur, Maize +

Spinach at Jessore, Mymensigh, and Rangpur, Maize

+ coriander (as vegetable) at Pabna. Maize + Red amaranth at Kushtia and Manikganj (OFRD, 2006).

The association of bush bean with maize provides

some N economy (Singh et al., 2000). Generally

legumes in association with non-legumes not only

helps in utilization of the nitrogen being fixed in the

current growing season, but also helps in residual

nutrients build up of the soil (Sharma et al., 1991).

However, the benefit accrued from intercropping may

vary according to the nature and type of intercrops

and their population densities. Therefore, it is

necessary to identify maize-based productive systems

for higher monetary returns in North Central Plateau Zone of Odisha as here there is ample scope for

intercropping with short duration vegetables with

maize in the inter row space without hampering the

T

RESEARCH ARTICLE

284 T.R. MOHANTY , M. RAY, S.K. SAHOO , K.C. SAHOO, N. MISHRA AND H.K. PATRO

main yield of maize. In view of this a study was

conducted to evaluate the performance of maize under

intercropping with different crops viz. Cowpea,

Cluster bean, radish and Arhar for selection of

suitable inter crop with maize and to increase the

cropping intensity, as well as increase the farmers’ income.

MATERIALS AND METHODS

The experiment was conducted at Field Experimental

Block, Regional Research and Technology Transfer

Station, Keonjhar, during Kharif season of two

consecutive years of 2017 and 2018 under RKVY

project. The soil of the experimental field was loamy

sand having pH

8 and N (107 kg/ha) and K (78 kg/ ha)

status was low whereas P (21 kg/ha) status was

medium. The experiment was laid out in a Randomized Complete Block Design with thirteen

treatments combinations and three replications. The

thirteen treatment combinations studied were as

follows: T1- Maize + Cowpea (1:1), T2-Maize +

Cowpea (2:2), T3-Maize + Radish (1:1), T4-Maize +

Radish (2:2), T5-Maize + Cluster bean (1:1), T6-

Maize + Cluster bean (2:2), T7-Maize + Arhar (1:1),

T8-Maize + Arhar (2:2),T9-Maize (sole), T10-

Cowpea (sole) , T11-Radish (sole), T12- Cluster bean

(sole), T13-Arhar (sole). The varieties taken were:

Maize-Pioneer 3396, Cowpea-Kasi Kanchan, Cluster bean -Pusa Navbahar, Arhar- Corg 9701 and Radish-

Pusa Chetki Long. Sowing was done on 24 June and

27 June in 2017 and 2018 respectively. Maize and all

intercrop vegetable seeds were sown at the same time.

All intercrops were sown in lines in between the

maize rows maintaining the standard spacing of the

respective crops. Maize seeds were sown in a planting

configuration of 60 cm x 30 cm spacing in 1:1

planting pattern and vegetable seeds were sown in

between them. A spacing 30 cm x 30 cm was

maintained in 2:2 planting pattern of maize and

vegetable intercropping, The crop was fertilized at the rate of 120-60-60 kg ha-1 of NPK and FYM at the

rate of 5 t ha-1. Full amount of P and K and 1/3rd of N

along with full amount of cow dung were applied at

the time of final and preparation. The rest N was

applied into two equal splits at knee height stage and

at tasselling stage. Intercultural operation was done as

and when necessary. Data on plant height, cobs per

plant, grains/cob , 100 seeds weight and grain yield

per hectare were recorded for data analysis. Grain

yield of maize was determined at 14% moisture

content. Ten cobs were randomly harvested from each plot, which was later converted into ton per

hectare. Maize equivalent yield (MEY) and BCR

were calculated to ascertain the efficiency of

intercropping. Maize equivalent yield was calculated

by converting the yield of intercrops to the yield of

Maize on the basis of prevailing market prices of

individual crops. Economic analysis on the basis of

net monetary return was performed to evaluate the

intercropping system.

Maize Equivalent Yield was calculated after

Bandyopadhyay (1984):

Maize Equivalent Yield (MEY) =

Yield of Intercrop (Kg ha-1) x Price of Intercrop (Rs Kg-1)

----------------------------------------------------------

Price of Maize (Rs Kg-1)

RESULTS AND DISCUSSION

Yield and yield contributing characters of Maize

Plant characters and yield attributes of Pioneer 3396

Hybrid Maize in maize- vegetable intercropping

system are presented in Table 1. The highest plant

height (185.3cm) and Cobs/ plant (1.51), was

recorded from sole maize followed by Maize + cowpea (1:1) (185.3cm and 1.45 respectively). The

lowest plant height (176.4cm) and Cobs/ plant (1.09),

was recorded from Maize + Arhar (2:2) intercropping.

The highest grains/cob (455.0) and 100 grain weight

(33.9g) was achieved from sole maize and it was

almost similar to treatments T1 and T2 i.e. Maize +

cowpea in the ratio 1:1( 32.5g) and 2:2 (31.2g).

Treatments T7 and T8 i.e. Maize + Arhar in the ratio

1:1(420.6 ) and 2:2 (419.5 ) produced the lowest

grains/cob .

Yield of Maize The maximum grain yield (5.35 t ha-1) was recorded

from sole maize and it was statistically identical to all

other treatments (Fig. 1). OFRD (2006) and Bhuiyan

et al., 1999 also reported that sole maize gave the

highest yield among the treatments

Yield of Intercrops

The highest average yield of intercrops (3.59 t ha-1)

was found from the Maize + Radish(2:2)

intercropping system whereas the lowest average

yield (0.48 t ha-1) was found in Maize + Arhar (2:2)

intercropping system.

Maize Equivalent Yield (MEY) Maize equivalent yields in the intercrops were

significantly higher than the sole crops. The pooled

data showed that the highest average Maize

equivalent yield of 7.10 t ha-1 was obtained from

Maize + Arhar (1:1) intercropping systems followed

by maize + cowpea(1:1) and maize + radish(1:1) ,

which was 25.2% higher than the sole crop of

Maize(Fig. 1). The results indicated that cereal

(Maize) – vegetable intercropping could bring more

benefit to farmers over sole maize. The increment of

total production by intercropping than sole cropping was also reported by Rao and Willey (1980); Umrani

et al. (1984); Bandhyopadhyay (1984); Basak et al.

(2006) and Bhowal et al. (2014).

Cost and benefit analysis

Productivity, net return , profitability and BCR of

maize-vegetable intercropping systems were shown in

Table 2. The productivity was highest Maize +

cowpea (1:1) intercropping (68.75 Kg/ha/day)

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 285

followed by Maize+Radish(1: 1) intercropping

(67.55 Kg/ha/day). Though the intercropping system

Maize + Arhar (2:2) gave the highest MEY but the

productivity was the less (41.5 Kg/ha/day). The least

productivity was obtained from sole Cluster bean

crop(24.5 Kg/ha/day). Maize + Arhar (1:1) gave the highest net return( Rs

42,580ha-1) and BCR(1.73) among all the systems

when no. of days occupied in the field was not taken

into account which was statistically at par with h

Maize + Cowpea(1:1) intercropping (Rs40,100 ha-1)

and BCR(1.69). The lowest net return( Rs 4,290.5 ha-

1) and BCR(1.08) was obtained from sole radish crop.

(Razzaque et al., 2007; Alam et al., 2008; Bhuiyan et

al., 2013; and Farhad et al., 2014. Uddin et al. (2009)

also documented that all the Maize-vegetables intercropping system in the hilly areas of Bangladesh

showed higher BCR than sole maize, which also

strongly supports the above findings.

Table 1. Plant and yield contributing characters of Maize (Pioneer 3396) during the Kharif season of 2017 and

2018 (Pooled).

Treatment Plant height (cm) Cobs/ plant(no) Grains/cob(no) 100 grain weight(g)

T1 (M+C-1:1) 185.3 1.45 451.6 32.5

T2 (M+C-2:2) 181.4 1.16 436.7 31.2

T3 (M+R-1:1) 168.4 1.11 435.2 30.9

T4 (M+R-2:2) 169.7 1.05 426.9 30.6

T5 (M+CB-1:1) 173.5 1.01 427.4 31.2

T6 (M+CB-2:2) 180.0 1.03 423.1 30.8

T7 (M+A-1:1) 178.3 1.10 420.6 31.4

T8 (M+A-2:2) 176.4 1.09 419.5

30.8

T9 (Sole M) 186.4 1.51 455.0 33.9

T10 (Sole C) --- --- --- ---

T11 (Sole R) --- --- --- ---

T12 (Sole CB) --- --- --- ---

T13 (Sole A) --- --- --- ---

Mean 177.7

1.2

432.9

31.5

Table 2. Cost and Return analysis of maize based intercropping systems at North Central Plateau Zone of

Odisha.

Treatment

Productivity

(Kg/ha/day)

Net Return

(Rs./ha)

Profitability

(Rs./ha/day) B:C

2017 2018 2017 2018 2017 2018 2017 2018

T1 (M+C-1:1) 67.6 69.9 38469 41731 384.7 417.3 1.66 1.72

T2 (M+C-2:2) 64.4 67.6 33826 38445 338.3 384.5 1.58 1.66

T3 (M+R-1:1) 66.4 68.7 35001 38255 350.0 382.6 1.59 1.64

T4 (M+R-2:2) 62.6 66.6 29660 35366 296.6 353.7 1.50 1.59

T5 (M+CB-1:1) 60.3 63.8 28981 34052 289.8 340.5 1.51 1.60

T6 (M+CB-2:2) 56.0 57.4 22822 24814 228.2 248.1 1.40 1.44

T7 (M+A-1:1) 43.1 45.6 39719 45441 248.2 284.0 1.68 1.78

T8 (M+A-2:2) 39.3 43.5 30910 40624 193.2 253.9 1.53 1.69

286 T.R. MOHANTY , M. RAY, S.K. SAHOO , K.C. SAHOO, N. MISHRA AND H.K. PATRO

T9 (Sole M) 52.4 54.6 26867 30033 268.7 300.3 1.56 1.63

T10 (Sole C) 37.1 37.4 21185 21661 211.9 216.6 1.67 1.68

T11 (Sole R) 40.6 40.6 3402 5179 34.0 34.0 1.06 1.10

T12 (Sole CB) 26.3 22.7 13268 5189 132.7 81.9 1.55 1.34

T13 (Sole A) 25.8 24.3 23349 19889 145.9 124.3 1.66 1.56

Sem (±) 2 2.1 3560 3202 28.1 29.8 - -

CD (0.05) 5.8 6.1 10390 9343 82.1 87.1 - -

Fig. 1: Comparison of Maize and Intercrop (vegetables) Yield with Maize Equivalent Yield (MEY) in Maize

vegetable intercropping system.

CONCLUSION

Maize + cowpea (1:1) proved to be the most

profitable system being at par with maize + cowpea

(2:2) & maize + radish (1:1 & 2:2) systems in both

the years. However, maize + arhar (1:1) returned the

highest amount per rupee invested (1.78) among all

the systems when no. of days occupied in the field is

not taken into account. Therefore the farmers of North

Central Plateau Zone are advised to take cowpea and

radish as intercrops with maize in Kharif season in the

above row ratios.

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288 T.R. MOHANTY , M. RAY, S.K. SAHOO , K.C. SAHOO, N. MISHRA AND H.K. PATRO

*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 289-295. 2020

EFFECT OF INTEGRATED NUTRIENT MANAGEMENT ON GROWTH AND

DEVELOPMENT OF MUSTARD (BRASSICA JUNCEA L.) IN IRRIGATED

CONDITION OF UPPER GANGETIC PLAINS

Sauhard Dubey1*, M.Z. Siddiqui

1, Saurabh Rana

1, Gaurav Shukla

2, Dharmendra Singh

2 and

Ashish Nath Pandey2

1Department of Agronomy, CSAUA&T, Kanpur, Uttar Pradesh-208002, India

2Department of Agronomy, SVPUA&T, Meerut, Uttar Pradesh-250110, India

Email: Sauhardsd29@gmail.com

Received-09.05.2020, Revised-29.05.2020

Abstract: A field experiment was conducted to study the effect of integrated nutrient management on growth and development of mustard (Brassica Juncea L.) under timely sown irrigated conditions on sandy loam soil at Students’ Instructional Farm (SIF) of C.S. Azad University of Agriculture and Technology, Kanpur. The experiment was laid out in Randomized Block Design replicated thrice. The treatments comprises of either 100% RDF (N:P:K:S) @ 120:60:40:40 kg ha-1 or 75 % RDF @ 90:45:30:30 kg ha-1 or 50 % RDF @ 60:30:20:20 kg ha-1 along with combinations of vermicompost @ 1.25 t ha-1 or 0.62 t ha-1, FYM @ 5 t ha-1 or 2.5 t ha-1 with bio-fertilizers (azotobacter + PSB) @ 7.5 Kg ha-1 + ZnSO4 @ 10 Kg ha-1. The results of the present investigation revealed that the growth and yield traits viz., plant height at maturity

(201.41cm), number of branches at maturity (7.59 primary, 9.37 secondary and 3.97 tertiary branches), LAI at 90 DAS (4.46), dry matter accumulated at maturity (44.23 g/plant) and grains yield (23.25 q ha-1) were recorded significantly highest with application of 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @ 10 kg ha-1. Hence, it may be recommended for farmers for higher yield in the area of Upper Gangetic Plains.

Keywords: Development, Fertilizers, FYM, Growth, Mustard, Vermicompost

INTRODUCTION

ilseeds, the second largest agricultural

commodity after cereals in India, play a

significant role in India’s agrarian economy, sharing

14% of the gross cropped area and accounting for

nearly 1.5% of the gross national production and 8%

of the value of all agricultural products. The gap in

supply is being met through huge imports costing more than Rs. 26000 crores during 2009-10.

Rapeseed and mustard are the major Rabi oilseed

crops of India and stand next to groundnut in the

oilseed economy. It is an important oilseed crops of

the family cruciferae and occupy a prominent place

among the leading oilseed crops being next to

groundnut both in area and production, meeting the

fat requirement of about 50 per cent population in the

state of Uttar Pradesh, Punjab, Rajasthan and Assam.

India is second in rapeseed and mustard production

to China and first in area. A range of oilseed crops viz. groundnut, rapeseed and mustard, soybean,

sesame, sunflower, safflower and niger (edible) and

linseed and caster (non edible) are also cultivated in

the country. In India, the overall area under rape

mustard has increased to 6.64 million hectares in

2018-19, up from 6.39 million hectares a year ago

while the production is jumped 19 per cent from a

year earlier to a record 8.5 million tonnes.

Vermicompost is a good organic source of plant

nutrient supply. It is a rich source of nitrogen (3%),

phosphorus (1%), potassium (1.50%), calcium

(0.44%), magnesium (0.15%), sulphur (0.45%), zinc (24.43ppm), iron (175.2ppm), vitamins and growth

hormones which enhance plant height, dry matter per

plant and seed yield. Rajiv (2019) stated that the

organic amendments like FYM, vermicompost and

bio-fertilizers might play a major role in

supplementing the crop nutrients through their direct

addition, improvement in soil condition, nitrogen

fixation and solubilisation of fixed forms of

phosphorus in soil. Rajiv (2014) reported that the

application of vermicompost integration with inorganic fertilizers might have improved the

availability of nutrients for crop use thus yielded

higher to sole inorganic fertilizers. In contrary to

synthetic fertilizers, vermicomposting reduce soil

toxicity by buffering action, prevent soil degradation

and enhance soil fertility status. Nitrogen is an

important constituent of growth. Effect of N level on

Indian mustard shows that all the growth characters

except number of branches increases with the

increasing nitrogen levels. Rajiv (2014a) reported

good impact of dissemination and diffusion of conservation agronomical practices on area

expansion (389.6 ha) as well as volume (623.36 t)

and value of produce (199.47 lac) of mustard in

Hamirpur district of Uttar Pradesh. Rajiv (2014b)

also stated that the improved techniques increased in

yield of vegetables by the margins of 44.35 to

58.23% over conventional system.

Therefore, in view of above facts, the field

experiment was conducted to study the effect of

integrated nutrient management on growth and

development parameters (plant height, No. of

branches, LAI and dry matter accumulation) of

O

RESEARCH ARTICLE

290 SAUHARD DUBEY, M.Z. SIDDIQUI, SAURABH RANA, GAURAV SHUKLA, DHARMENDRA SINGH

AND ASHISH NATH PANDEY

mustard (Brassica Juncea L.) in irrigated condition

of Upper Gangetic Plains.

MATERIALS AND METHODS

The experiment was conducted at Students’

Instruction Farm (SIF) of Chandra Shekhar Azad

University of Agriculture & Technology, Kanpur

(U.P) during Rabi season 2017-18. The field was

well levelled and irrigated by tube well. Soil of the

experimental field was sandy loam in texture

with 7.9 pH and electrical conductivity was

0.33 dSm-1. Nine different treatments viz., 100%

RDF (N:P:K:S @ 120:60:40:40 kg ha-1), 100% RDF + bio-fertilizers (azotobacter + PSB) @ 7.5 kg ha-1,

75% RDF + FYM @ 2.5 t ha-1 + ZnSO4 @ 10 kg ha-

1, 75% RDF + vermicompost @ 0.62 t ha-1 + ZnSO4

@ 10 kg ha-1, 75% RDF + FYM @ 2.5 t ha-1 + bio-

fertilizers @ 7.5 kg ha-1, 75% RDF + vermicompost

@ 0.62 t ha-1 + bio-fertilizers @ 7.5 kg ha-1, 50%

RDF + vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10

kg ha-1, 50% RDF + FYM @ 5 t ha-1 + ZnSO4 @ 10

kg ha-1 and 50% RDF + FYM @ 2.5 t ha-1 +

vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 + ZnSO4 @ 10 kg ha-1 were tested against control in randomized block design (RBD). The

treatments were replicated thrice to avoid any effect

of heterogeneity as per standard procedure. Land

preparation was started after harvesting of kharif

crop, for proper germination of seeds. Seeds were

sown in rows at a distance of 45 cm by using seeds

rate of 5 kg ha-1. The recommended dose of

fertilizers were applied at the rate of 120 kg N, 60 kg

P2O5, 40 kg K2O and 40 kg S (elemental sulphur) per

hectare. Full amount of phosphorus, potash, sulphur

and 75% nitrogen was applied as basal dose while

the remaining amount of nitrogen was applied after first irrigation as top dressing. The crop was further

fertilized with FYM, vermicompost, bio-fertilizer,

sulphur and zinc according to treatments. Three

phases thinning was done during the crop period in

which first thinning was done at seedling stage

at 10 days after sowing to maintain optimum plant to

plant distance by 15 cm followed by 15-20 DAS and

40 DAS. Crop variety Pusa Mustard-30 was used under study, which is a low erucic acid variety of

Indian mustard [Brassica Juncea (L.) Czern & Coss]

developed by Division of Genetics, Indian

Agricultural Research Institute, New Delhi. The new

released variety along with integrated nutrient

management increased significantly number of

leaves per plant and dry matter accumulation and

number of branches per plant leading to better plant

floral growth thus leads to increase in yield. The crop

was harvested at physiological maturity on 18th

March, 2018. The data regarding growth characters and yield were analysed with statistical analysis and

significance of treatments were tested with the help

of ‘F’ test.

RESULT AND DISCUSSION

Growth parameters The data regarding growth characters viz., plant

height, number of branches, LAI (leaf area index)

and dry matter accumulation are depicted in Table 1,

Table 2, Table 3 and Table 4, respectively.

Plant height

The maximum plant height of 12.77, 121.13, 193.46

and 201.41 cm were obtained at 30 DAS, 60 DAS,

90 DAS and at maturity respectively, with the

application of 50% RDF + FYM @ 2.5 t ha-1 +

vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 + ZnSO4 @ 10 kg ha-1 (T10) followed by 75%

RDF + vermicompost @ 0.62 t ha-1 + bio-fertilizers

@ 7.5 kg ha-1 (T7) and 50% RDF + vermicompost @

1.25 t ha-1 + ZnSO4 @ 10 kg ha-1 (T8) (Table 1).

However, these three treatments were statistically at

par with each other. Treatment T10 (50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 +

bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @ 10 kg ha-1)

significantly superior over 100% RDF (N:P:K:S @

120:60:40:40 kg ha-1

) (T2) as well as control (T1).

Jaiswal et al. (2017) also reported similar results.

Table 1. Plant height of mustard as influenced by different treatments

Treatments

Plant height (cm)

30

DAS

60

DAS

90

DAS

At

maturity

T1 Control 11.28 78.93 125.83 128.65

T2 100% RDF (N:P:K:S @ 120:60:40:40 kg ha-1) 11.46 103.03 164.25 168.55

T3 100% RDF + bio-fertilizers (azotobacter + PSB) @ 7.5 kg

ha-1 11.49 106.03 169.10 176.18

T4 75% RDF + FYM @ 2.5 t ha-1 + ZnSO4 @ 10 kg ha-1 11.68 107.83 171.93 175.74

T5 75% RDF + vermicompost @ 0.62 t ha-1 + ZnSO4 @ 10 kg

ha-1 12.14 112.13 178.75 182.71

T6 75% RDF + FYM @ 2.5 t ha-1 + bio-fertilizers @ 7.5 kg

ha-1 12.55 115.83 184.72 189.15

T7 75% RDF + vermicompost @ 0.62 t ha-1 + bio-fertilizers

@ 7.5 kg ha-1 12.57 119.23 190.07 194.28

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 291

T8 50% RDF + vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10 kg

ha-1 12.45 118.23 188.56 192.74

T9 50% RDF + FYM @ 5 t ha-1 + ZnSO4 @ 10 kg ha-1 12.07 117.53 187.45 191.60

T10 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t

ha-1

+ bio-fertilizers @ 7.5 kg ha-1

+ ZnSO4 @ 10 kg ha-1

12.77 121.13 193.46 201.41

S.E. (d) ± 1.079 4.605 10.095 13.487

C.D. at 5% N. S 9.670 21.216 28.346

Number of branches/plant

In case of number of branches/plant, application of

50% RDF + FYM @ 2.5 t ha-1 + vermicompost @

0.62 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @

10 kg ha-1 (T10) recorded highest number of primary

branches of 6.64, 7.35 and 7.59 at 60 DAS, 90 DAS

and at maturity respectively (Table 2). It was

followed by 75% RDF + vermicompost @ 0.62 t ha-1

+ bio-fertilizers @ 7.5 kg ha-1 (T7) and 50% RDF +

vermicompost @ 1.25 t ha-1

+ ZnSO4 @ 10 kg ha-1

(T8). However, excluding the treatment of control

(T1) and 100% RDF (T2), all the treatments from T3

to T10 were statistically at par with each other in

terms of number of primary branches. The minimum

values of number of primary branches of 4.33, 4.79

and 4.95 at 60 DAS, 90 DAS and at maturity

respectively, were found in control.

Similar trend was also observed in case of number of

secondary branches/plant and application of 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t

ha-1 + bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @ 10 kg

ha-1 (T10) recorded highest number of secondary

branches of 9.17, 9.31 and 9.37 at 60 DAS, 90 DAS

and at maturity respectively, followed by 75% RDF

+ vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 (T7) and 50% RDF + vermicompost @ 1.25 t

ha-1 + ZnSO4 @ 10 kg ha-1 (T8) at maturity stage

whereas, at the stage of 60 DAS and 90 DAS, the

trend is different and treatment T7 was followed by

50% RDF + FYM @ 5 t ha-1 + ZnSO4 @ 10 kg ha-1

(T9) in terms of secondary branches.

Similarly to number of primary and secondary branches/plant, the significant role of different

sources of nutrient was observed and application of

50% RDF + FYM @ 2.5 t ha-1 + vermicompost @

0.62 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @

10 kg ha-1 (T10) recorded significantly highest

number of tertiary branches of 3.14, 3.73 and 3.97

followed by 75% RDF + vermicompost @ 0.62 t ha-1

+ bio-fertilizers @ 7.5 kg ha-1 (T7) and 50% RDF +

vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10 kg ha-1

(T8) which were significantly superior over other

treatments. This may be due to the better establishment of plants under these treatments

compared to other remaining treatments and it might

be also due to improvement in nutrient availability

for crop use. Mukherjee (2016) and Yadav et al.

(2018) also reported similar results.

Table 2. Effect of different treatments on number of branches of mustard crop

Treatments

Primary branches Secondary branches Tertiary branches

60

DAS

90

DAS

At

maturity

60

DAS

90

DAS

at

maturity

60

DAS

90

DAS

At

maturity

T1 Control 4.33 4.79 4.95 5.98 6.01 6.10 2.05 2.43 2.59

T2

100% RDF

(N:P:K:S @ 120:60:40:40 kg ha-

1)

5.65 6.25 6.46 7.81 7.91 7.97 2.68 3.17 3.38

T3

100% RDF + bio-

fertilizers

(azotobacter + PSB)

@ 7.5 kg ha-1

5.91 6.53 6.75 8.16 8.08 8.34 2.80 3.31 3.53

T4

75% RDF + FYM

@ 2.5 t ha-1 +

ZnSO4 @ 10 kg ha-1

5.92 6.55 6.77 8.18 8.22 8.35 2.81 3.32 3.54

T5

75% RDF +

vermicompost @

0.62 t ha-1 + ZnSO4

@ 10 kg ha-1

6.15 6.80 7.03 8.49 8.59 8.68 2.91 3.45 3.68

T6

75% RDF + FYM

@ 2.5 t ha-1 + bio-fertilizers @ 7.5 kg

ha-1

6.36 7.03 7.26 8.77 8.86 8.97 3.01 3.56 3.79

292 SAUHARD DUBEY, M.Z. SIDDIQUI, SAURABH RANA, GAURAV SHUKLA, DHARMENDRA SINGH

AND ASHISH NATH PANDEY

T7

75% RDF +

vermicompost @

0.62 t ha-1 + bio-

fertilizers @ 7.5 kg ha

-1

6.54 7.24 7.48 9.04 9.15 9.23 3.10 3.67 3.92

T8

50% RDF +

vermicompost @

1.25 t ha-1 + ZnSO4

@ 10 kg ha-1

6.49 7.18 7.41 8.76 8.89 9.15 3.07 3.64 3.87

T9

50% RDF + FYM

@ 5 t ha-1 + ZnSO4

@ 10 kg ha-1

6.45 7.14 7.38 8.91 8.98 9.10 3.05 3.62 3.86

T10

50% RDF + FYM

@ 2.5 t ha-1 +

vermicompost @

0.62 t ha-1 + bio-

fertilizers @ 7.5 kg

ha-1 + ZnSO4 @ 10 kg ha-1

6.64 7.35 7.59 9.17 9.31 9.37 3.14 3.73 3.97

S.E. (d) ± 0.464 0.417 0.478 0.818 0.477 0.505 0.286 0.322 0.326

C.D. at 5% 0.974 0.879 0.991 1.719 1.003 1.061 0.601 0.678 0.686

LAI (leaf area index)

At 30 DAS, there was no significant difference in LAI between different treatments. The values of LAI

reveals that the different or high doses of nutrient has

no significant effect till 30 DAS in mustard crop as

the plant in its initial vegetative stage does not show

any effect of nutrients. Whereas, the LAI of 2.66 and

4.46 were recorded highest at 60 and 90 DAS

respectively, with the application of 50% RDF +

FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 +

bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @ 10 kg ha-1 (T10) (Table 3). It was followed by 75% RDF +

vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 (T7) and 50% RDF + vermicompost @ 1.25 t

ha-1 + ZnSO4 @ 10 kg ha-1 (T8). The minimum values

of leaf area index were found in control. Bhati and

Sharma (2006) also reported similar results.

Table 3. Effect of different treatments on LAI of mustard crop

Treatments

LAI

30

DAS

60

DAS

90

DAS

T1 Control 0.34 1.97 3.29

T2 100% RDF (N:P:K:S @ 120:60:40:40 kg ha-1) 0.39 2.26 3.79

T3 100% RDF + bio-fertilizers (azotobacter + PSB) @ 7.5 kg ha-1 0.40 2.32 3.88

T4 75% RDF + FYM @ 2.5 t ha-1 + ZnSO4 @ 10 kg ha-1 0.41 2.37 3.97

T5 75% RDF + vermicompost @ 0.62 t ha-1 + ZnSO4 @ 10 kg ha-1 0.41 2.37 3.95

T6 75% RDF + FYM @ 2.5 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 0.41 2.37 3.95

T7 75% RDF + vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 0.43 2.49 4.16

T8 50% RDF + vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10 kg ha-1 0.42 2.43 4.07

T9 50% RDF + FYM @ 5 t ha-1 + ZnSO4 @ 10 kg ha-1 0.41 2.37 3.97

T10 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 + bio-

fertilizers @ 7.5 kg ha-1 + ZnSO4 @ 10 kg ha-1 0.46 2.66 4.46

S.E. (d) ± 0.026 0.148 0.25

C.D. at 5% N.S 0.312 0.43

Dry matter accumulation

The highest dry matter accumulation of 2.66, 18.37, 42.96 and 44.23 at 30 DAS, 60 DAS, 90 DAS and at

maturity were recorded in treatment of application of

50% RDF + FYM @ 2.5 t ha-1 + vermicompost @

0.62 t ha-1

+ bio-fertilizers @ 7.5 kg ha-1

+ ZnSO4 @

10 kg ha-1 (T10) followed by 75% RDF + vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 (T7) and 50% RDF + vermicompost @ 1.25 t

ha-1 + ZnSO4 @ 10 kg ha-1 (T8). The difference

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 293

between treatments was significant at the stages of

60 DAS, 90 DAS and at maturity but at 30 DAS,

there is no significant difference between treatments.

The reason behind more dry matter in integrated

nutrient supply may be the proper establishment of

crop plants, increased height and larger vegetative growth. These results are in close conformity of

Jakhar and Singh (2004), Mandal and Sinha (2004),

Singh et al. (2015) and Tomar et al. (2017). Rajiv et

al. (2012) also reported that the sulphur application

increased plant height, branches/plant and dry

matter/plant significantly over no sulphur application

in sesame and it might be because sulphur is

involved in photosynthetic process of plant, which has a direct bearing on development and plant

growth.

Table 4. Effect of different treatments on dry matter accumulation of mustard

Treatments

Dry matter accumulation

30

DAS

60

DAS

90

DAS

At

maturity

T1 Control 2.35 12.19 27.95 31.58

T2 100% RDF (N:P:K:S @ 120:60:40:40 kg ha-1) 2.39 15.91 36.47 37.01

T3 100% RDF + bio-fertilizers (azotobacter + PSB) @ 7.5 kg ha-1 2.39 16.38 37.55 37.95

T4 75% RDF + FYM @ 2.5 t ha-1 + ZnSO4 @ 10 kg ha-1 2.43 16.65 38.18 38.59

T5 75% RDF + vermicompost @ 0.62 t ha-1 + ZnSO4 @ 10 kg ha-1 2.53 17.31 39.69 40.12

T6 75% RDF + FYM @ 2.5 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 2.61 17.89 41.02 41.53

T7 75% RDF + vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 2.62 18.47 42.21 42.66

T8 50% RDF + vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10 kg ha-1 2.59 18.26 41.87 42.32

T9 50% RDF + FYM @ 5 t ha-1 + ZnSO4 @ 10 kg ha-1 2.51 18.16 41.62 42.07

T10 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 +

bio-fertilizers @ 7.5 kg ha-1 + ZnSO4 @ 10 kg ha-1 2.66 18.37 42.96 44.23

S.E. (d) ± 0.37 1.050 2.093 2.506

C.D. at 5% N.S 2.207 4.399 5.266

Grains yield

The grains yield of mustard influenced significantly

by different treatment (Table 5). The significantly

highest grains yield of 23.25 q ha1 was produced

with the application of 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 + ZnSO4 @ 10 kg ha-1 (T10). It was followed

by 75% RDF + vermicompost @ 0.62 t ha-1 + bio-

fertilizers @ 7.5 kg ha-1 (T7) and 50% RDF +

vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10 kg ha-1

(T8). The most probable reason for this phenomenon

may be taller plant and higher dry matter, more

vegetative growth under proper organic and

inorganic nutrient supply (INM). This might had

resulted to increase grains yield. These findings are

in accordance with the findings of Giri et al. (2005),

Tripathi et al. (2011), Baranwal et al. (2017), Singh

et al. (2018) and Yadav et al. (2018). Rajiv (2014) also reported that the application of vermicompost

integration with inorganic fertilizers might have

improved the availability of nutrients for crop use

thus yielded higher to NPK fertilizers treatment. A

poor grains yield was produced as a result of

reflection of poor fertility as reported by Tomar et al.

(2016) and Tomar et al. (2019) in different crops.

Table 5. Effect of treatments on grains yield of mustard

Treatments Grains yield

(q ha1)

T1 Control 14.75

T2 100% RDF (N:P:K:S @ 120:60:40:40 kg ha-1) 19.23

294 SAUHARD DUBEY, M.Z. SIDDIQUI, SAURABH RANA, GAURAV SHUKLA, DHARMENDRA SINGH

AND ASHISH NATH PANDEY

T3 100% RDF + bio-fertilizers (azotobacter + PSB) @ 7.5 kg ha-1 19.82

T4 75% RDF + FYM @ 2.5 t ha-1 + ZnSO4 @ 10 kg ha-1 20.15

T5 75% RDF + vermicompost @ 0.62 t ha-1 + ZnSO4 @ 10 kg ha-1 20.95

T6 75% RDF + FYM @ 2.5 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 21.65

T7 75% RDF + vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5 kg ha-1 22.90

T8 50% RDF + vermicompost @ 1.25 t ha-1 + ZnSO4 @ 10 kg ha-1 22.10

T9 50% RDF + FYM @ 5 t ha-1 + ZnSO4 @ 10 kg ha-1 21.97

T10 50% RDF + FYM @ 2.5 t ha-1 + vermicompost @ 0.62 t ha-1 + bio-fertilizers @

7.5 kg ha-1 + ZnSO4 @ 10 kg ha-1 23.25

S.E. (d) ± 1.400

C.D. at 5% 2.942

CONCLUSION

On the basis of above findings, it can be concluded

that the application of 50% RDF + FYM @ 2.5 t ha-1

+ vermicompost @ 0.62 t ha-1 + bio-fertilizers @ 7.5

kg ha-1 + ZnSO4 @ 10 kg ha-1 (T10) shows the

outstanding results in terms of significant growth and

development parameters (plant height, number of

branches, leaf area index and dry matter

accumulation) and grains yield. Therefore, it may be

recommended for cultivation of mustard under Upper Gangetic Plains.

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296 SAUHARD DUBEY, M.Z. SIDDIQUI, SAURABH RANA, GAURAV SHUKLA, DHARMENDRA SINGH

AND ASHISH NATH PANDEY

*Corresponding Author

________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 297-301. 2020

UTILIZATION POTENTIAL OF AGRICULTURAL INFORMATION SOURCES

K. Pradhan1, Avishek Saha

2, Biman Maity

2* and Keshav Ram

3

Department of Agricultural Extension, Uttar BangaKrishiViswavidyalaya, Pundibari, Coochbehar

Email: avishek.extesion.2014@gmail.com

Received-11.05.2020, Revised-30.05.2020

Abstract: We are now living in the age of information where accessing and utilizing appropriate information source play crucial role in determining the success of any human activity. Agriculture of today has also become very time-critical and information-intense. Hence, the utilization potential of any information source to cater to the information needs of the farmers in various aspects would determine its usefulness to the farming community. With this background, the present

research work has been conducted in order to assess the utilization potential of the existing information sources in the study area and thereby identify the factors influencing the utilization potential of the information sources. In the present study, utilization potential of the information sources has been conceptualized as the predicted variable and the nineteen other attributes associated with the farmers has been considered as the predictor variables. The study has been carried out in three villages of Coochbehar-I and two villages of Coochbehar-II block of Coochbehar district in West Bengal. Purposive as well as multistage sampling and random sampling procedures were followed in selecting hundred numbers of respondents. The data were collected with the help of structured questionnaire through personal interview method. The major statistical tools like correlation co-efficient and multiple regression analysis were used to analyse the data. The important findings of the study are that the timeliness of the information sources has positive association with the utilization potential whereas the

usefulness of the multiple sources of agricultural information ultimately reduces the utilization potential of individual information source. Farmers have also admitted that the agricultural information sources available in the study area have medium level of potential to cater to their information needs. Therefore, there is a scope to further improvement of those information sources for effective and efficient dissemination of appropriate information for sustainable agricultural development.

Keywords: Information source, Information-intense, Utilization potential, Sustainable agricultural development

INTRODUCTION

he successful use of information as a resource

for development of agriculture depends to a

large extent on timely availability of existing sources

of information, pattern of different sources and

channels of agriculture as well as the attitude of

farmers towards information and information

sources. Information is the driving force behind any

development strategy. In India SAU, colleges,

research institutes, NGO’s, KrishiVigyan Kendra,

private agencies have been playing an important role

to disseminate the agricultural information to the farmers. Mainly agricultural information is diffused

through training programme, demonstration,

campaigns and mass media etc.Rural farmers need

various type of information regarding agriculture

such as availability of agricultural support

services,Government regulations, crop production

and managements, disease outbreaks, adaptation of

technologies by other farmers, wage rates, and so

on.Farmers receive agricultural information from a

multitude of sources, such as extension

agencies,mass media, fellow farmers, input dealers etc. (P. Adhigurua et al., 2009). There are also

several portals and SMS system which give the

actual information like market value of the

commodity, weather report, online buyer or seller of

the commodity, pest and insect management

procedure, disease management procedure etc. An

effective and efficient information delivery system plays a critical role to provide reliable and useful

information to the farmers (Demiryureket al., 2008).

In India, Farmers are being provided with knowledge

based information through various toll free numbers,

internet sites, mobile apps, and other means. For

example, Farmers’ Portal (www.farmer.gov.in), m-

Kisan Portal (www.mkisan.gov.in) and Kisan Call

Centers (KCC) are some of the platforms which are

currently active in India (KitturNazhatet al.,

2016).But, sometimes, due to poor information

network connectivity, farmers can not harness the

benefits of the internet related facilities provided by the Government or any other organization. Here,

extension services can play a major role in changing

the scenario of the village through providing

appropriate information to the farmers which are

need-based and demand-driven.Consequently,

agricultural extension, in the current scenario of a

rapidly changing world, has been recognized as an

essential mechanism for delivering knowledge

(information) and advice as an input for modern

farming (Jones, 1997).

Now days, private extension services are also involved in proving information related to agriculture

and allied activities, sometimes through paid services

which is gaining its popularity among the farming

community day by day. In India, though it is

generally claimed that public extension system is the

predominant source of farm information

T

RESEARCH ARTICLE

298 K. PRADHAN, AVISHEK SAHA, BIMAN MAITY AND KESHAV RAM

dissemination (Nirmala et al., 1995), it was

disappointing to note that it was accessed only by a

small proportion of farm households. Therefore, both

public and private extension systems are innovating

approaches for the transfer of technology and

information to farmers so as to empower them to face the challenges of market liberalization and

globalization (P. Adhiguru et al., 2009).

But, before formulating any strategic intervention to

address the information needs of the farmers, it is

very much essential to explore the existing

information sources available to the farmers and their

usefulness in the context of the farmers’ real life

situation. The content of the information services

needs to reflect their diverse circumstances and

livelihoods. Understanding of the communication

network in a specific farming system may provide

the recognition of basic structures, components, weakness and gap of the system and the different

sources of information used by these different

components (Demiryurek, 2000).Therefore, selecting

an appropriate source of information at the right time

in agriculture is the basic requisite for sustainability.

Under this research niche, the present study has been

conceptualized and conceived to assess the

usefulness of the existing agricultural information

sources and thereby identify the attributes associated

with the farmers which significantly influence the

perceived utility of the information sources.

METHODOLOGY

The study is conducted in the villages of Charakpara, Katamari, Elajanerkuthi of Cooch Behar-I block and

Gopalpur, DhangDhingguri of Cooch Behar-II block

under Cooch Behar district in West Bengal.

Purposive as well as multistage and random sampling

procedures were followed for selection of the final

respondents. The district and block were selected

purposively. A total number of hundred (100)

respondents were selected from an exhaustive list of

farmers who have continuous contact with existing

information sources in the locality identified with the

help of the local people, local administrators etc. The

perception of the farmers regarding the utilization potential of the information source has been

conceptualized as the predicted variable and the

nineteen other attributes associated with the farmers

were delineated as the predictor variables in the

present research work. The data were collected with

the help of a structured interview schedule through

personal interview method. The statistical tools like

co-efficient of correlation and multiple regressions

were the key analysers for drawing a definite

conclusion from the collected data.

RESULTS AND DISCUSSION

Table 1. Distribution of respondents according to their utilization potential of information sources

Category Score Frequency Percentage Statistics

Low 18-21.3 11 11 Range=18-28

Mean=24.18

SD=2.00

CV=8.27%

Medium 21.4-24.6 45 45

High 25.7-28 44 44

Table-1 presents the distribution of the farmers

according to utilization potential of information

sources. The results show that majority of the

respondents have agreed upon medium level of

utilization potential of information sources with score 21.4-24.6 (45%) followed by high level with

score25.7-28 (44%) and low level of utilization

potential with score18-21.3(11%). The mean score of

total distribution is 24.18 and standard deviation is 2.

The coefficient of variation value within the

distribution is 8.27% which signifies very high level

of the distribution for the variable ‘utilization

potential of information sources’. The result implies

that most of the farmers in the study area have admitted that existing information sources have the

potential to satisfy their information needs related to

their farming activity.

Table 2. Correlation Coefficient of utilization potential of information source (Y2) with 19 independent

variables

Variables Coefficient of correlation (r)

Age(X1) -.162

Education (X2) .136

Family Education Status (X3) -.018

Major occupation(X4) .161

House Type (X5) -.115

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 299

Social Participation (X6) -.031

Material possession (X7) .050

Land Holding (X8) -.123

Farm power (X9) -.056

Livestock possession(X10) .094

Extension contact (X11) .151

Mass media exposure(X12) .131

Risk Preference (X13) .162

Economic Motivation (X14) .157

Decision making ability (X15) .056

Attitude towards use of information sources (X16) -.005

Utilization pattern of information sources (X17) .157

Usefulness of the information source (X18) .042

Timeliness of the information source (X19) .235*

** Significant at 1% level, *Significant at 5% level

Table-2 reflects the Pearson’s coefficient of

correlation among the dependent variable, utilization

potential of information sources with the nineteen

causal variables. The result shows that the variable,

timeliness of the information source (X19) is the only

variable which is positively and significantly

associated with the dependent variable, utilization

potential of information sources.

Timeliness of the information source and

utilization potential of information source

Timeliness always plays an important role in case of

determining effectiveness of an information source.

Timeliness refers to the ability of the information

source to provide required information to the

information users at the right time in right format

with adequate accuracy. Therefore, it is obvious that

timeliness of the information source in providing

appropriate information would certainly enhance the

credibility of the information sources to the end users

and in this way, utilization potential of the

information source would be increased. In the

present study, the farmers have also identified some

of the information sources with the ability to provide

timely information correctly and therefore, they

regularly access those information sources for solving many problems of their farm and home by

utilizing the information provided by them. Hence,

utilization potential of the information sources has

increased. That is why the variable timeliness of the

information source is significantly and positively

associated with the dependent variable, utilization

potential of the information source.

Table 3. Multiple regression analysis of utilization potential of information source (Y2) of respondents with 19

predictor variable

Variables Standardized

regression

coefficient (β)

Unstandardised

regression

coefficient (B)

S.E of ‘B’ t-value

Age(X1) -.158 -.029 -.158 -.949

Education (X2) .076 .146 .306 .477

Family Education Status (X3) -.007 -.017 .268 -.062

Major occupation(X4) .061 .193 .352 .547

House Type (X5) -.152 -.616 .458 -1.344

Social Participation (X6) -.148 -.750 .532 -1.408

Material possession (X7) .007 .002 .030 .063

Land Holding (X8) -.062 -.110 .203 -.539

300 K. PRADHAN, AVISHEK SAHA, BIMAN MAITY AND KESHAV RAM

Farm power (X9) -.039 -.054 .152 -.359

Livestock possession(X10) -.024 -.024 .116 -.206

Extension contact (X11) .095 .079 .098 .802

Mass media exposure(X12) .099 .145 .181 .803

Risk Preference (X13) .058 .046 .093 .501

Economic Motivation (X14) .082 .064 .090 .705

Decision making ability (X15) -.012 -.010 .103 -.100

Attitude towards use of information

sources (X16)

-.001 -.001 .104 -.012

Utilization pattern of information

sources (X17)

.079 .027 .042 .652

Usefulness of the information source

(X18)

-.301 -.077 .038 -2.000*

Timeliness of the information source

(X19)

.376 .107 .045 2.410**

** Significant 1% level, * Significant at 5% level R2= 0.213

Table-3 reflects the multiple regression analysis of

the utilization potential of information source with

the 19 predictor variables. From the table it is

observable that the variable usefulness of the

information source (X18) are significantly and negatively contributing towards characterizing the

dependent variable, utilization potential of

information source while another variable namely

timeliness of the information source (X19) is

significantly and positively contributing towards

characterizing the dependent variable, utilization

potential of information source.

Usefulness of the information source and

utilization potential of information source

The utilization potential of information source is

measured through accomplishment of several goals in agricultural sector like improvement of farming

practices by reducing drudgery, enhancement of

productivity, usefulness of information and easier

handling of technology. The enhanced usability of

information sources increases the potentiality of

getting more information on a particular issue. The

issues may be related to farming practices, climate

resilience etc. But, more information creates a

conflicting state of mind in case of an

individual/farmer who does not have the acumen to

analyse the information and comprehend the information to be utilized by himself for

accomplishing the improved production practices,

productivity and easier technological intervention.

That is why the variable usefulness of information

source is significantly and negatively contributing

towards characterizing the dependent variable,

utilization potential of information source. The

variable usefulness of information source is directly

contributing 37.60% in case of characterizing the

dependent variable, utilization potential of

information source. One unit change of the variable

usefulness of information source is delineating the

0.107 unit change in the predicted variable.

Timeliness of information source and utilization

potential of information source

Utilization potential of information source indicates

the extent to which the information provided by the

source is helpful for the users to enhance their

effectiveness and efficiency in doing their job.

Therefore, it is mention worthy that timeliness of the

information source in providing needed information

to the users would act as one of the determinants of

utilization potential of the information source. In

agriculture, farmers require to consult with various information sources for getting appropriate

information related to several aspects of farming

starting from production to marketing of their

produce. In this regard, timeliness is an important

factor which could improve the utilization potential

of existing information sources to which the farmers

access. It is discernible that more timely the

information is, more is its utilization potential in

catering the information needs of the farmers. In the

present study, it has been found that the farmers can

utilize those information more successfully towards improving their farming practices which have

timeliness than those which are untimely. That is

why the variable timeliness of information source is

significantly and positively contributing in case of

characterizing the dependent variable, utilization

potential of information source. The variable

timeliness of information source is directly

contributing 37.60% in case of characterizing the

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 301

dependent variable, utilization potential of

information source. One unit change of the variable

timeliness of information source is delineating the

0.107 unit change in the predicted variable.

The R2

value being 0.213, it is to infer that the

nineteen predictor variables put together have explained 21.30% variation embedded with the

predicted variable, utilization potential of

information source. Still 78.70% variable embedded

within predicted one remains unexplained. Thus it

would be suggested that inclusion of some more

contextual variables possessing direct bearing on

utilization potential of information source could have

increased the level of explicability.

CONCLUSION

In this present age of information, every human activity relies largely upon a host of information

sources and the quality of information they provide.

In this regard, the reliability and credibility of the

information also contribute a lot to the usefulness of

the information in the farming situation of the

farmers. The capacity of the information source to

satisfy the information needs of the rural folk in

different aspects of cultivation determines its

usefulness to the farming community. In this context,

utilization potential of the information source is a

very relevant concept through which one can measure the usefulness of information source.

Similarly, in the present study, farmers’ perception

about the utilization potential of the agricultural

information sources available in the study area has

been analysed and the important socio-economic,

socio-personal and socio-psychological attributes of

the farmers have been identified which have a

determining role in case of characterizing the

utilization potential of the information sources. What

have been found in the study area is that most of the

farmers consider the existing information sources as

moderately useful for their farming profession but at the same time, they also locate some areas where

there is ample scope of further improvement in case

of disseminating appropriate information at the right

time to the farmers. Another important finding of the

present study is that the timeliness of the information

source improves its utilization potential in case of

using the information for betterment of the farming

enterprise. On the other hand, presence of so many

useful information sources often put the farmers in a

confusing state of mind regarding selection of the appropriate information source which ultimately

affect the utilization potential of the information

sources. Hence, in totality, a holistic approach needs

to be adopted considering all the elements of the

agricultural information network existing in a local

rural setting to tap maximum utilization potential of

the information sources towards catering the

information needs of the farming community in a

sustainable way.

REFERENCES

Jones, G.E. (1997). ‘The history, development and

the future of agricultural extension’ in B.E. Swanson,

R.P. Bentz and A.J. Sofranko (1997). Improving

agricultural extension – a reference manual. Rome:

FAO.

Demiryurek, K. (2000). The analysis of information

systems for organic and conventional hazelnut

producers in three villages of the Black Sea Region,

Turkey, Doctoral dissertation (Unpublished), The

University of Reading, Reading, UK.

Demiryurek, K. (2008). The use of social network analysis (SNA) to identify opinion leaders: the case

of organic hazelnut producers in Turkey. J. of Ext.

Systems, 24. pp. 17–30.

Nazhat, Kittur, Jain, Rajendra and Kittur,

Parveen (2016). Potential of M-Commerce of

Agricultural Inputs in Kolar, Karnataka, India.

Research Journal of Recent Sciences, 5(7). pp. 1-10.

Nirmala, L., Ravichandran, V. and

Rathakrishnan, T. (1995). Information sources

utilization influencing knowledge and adoption of

biofertilizers, Journal of Extension Education, 6(1).

pp. 1071-1074.

Adhigurua, P., Birthal, P. S. and Ganesh Kumar,

B. (2009). Strengthening Pluralistic Agricultural

Information Delivery Systems in India. Agricultural

Economics Research Review, Vol. 22. pp. 71-79.

302 K. PRADHAN, AVISHEK SAHA, BIMAN MAITY AND KESHAV RAM

*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 303-307. 2020

PLANT GROWTH PROMOTING ACTIVITIES OF INDIGENOUS STRAINS OF

TRICHODERMA VIRIDE AND TRICHODERMA HARZIANUM USED AS SEED

TREATMENT IN GROUNDNUT

Shweta Mishra*1, Arwind Kurre

2 and R.K.S. Tiwari

3

1,2

Departmant of Plant Pathology, IGKV Raipur 3Dean BTC CARS, Bilaspur

Received-05.05.2020, Revised-26.05.2020 Abstract: Experiment was conducted in vivo to study the plant growth promoting activities of strains of Trichoderma harzianum and Trichoderma viride used as seed treatment@ 10 g /kg seed in groundnut. Various observations of growth

parameters and yield components i.e. plant height (cm), no. of branches, no. of pods / plant, unfilled pods/ plant, filled pods/plant and pod yield/ plant (g) were recorded maximum in Trichoderma strains T2 respectively, followed by T3, T4 and minimum unfilled pod was recorded in strain T4(18) superior over control.

Keywords: Groundnut, Trichoderma harzianum, Trichoderma viride growth parameters, Yield components, Seed

INTRODUCTION

roundnut (Arachis hypogaea L.) is a major

legume and an important oil seed crop in India,

covering nearly half of the area under oilseeds.

It is grown in over 100 countries with a total

estimated area of 21.8 million ha and with production

of 28.5 million tons. In India, it is grown over an area

of 4 lakh ha, with an annual production of 5.5 million

tons and productivity of 1007 kg ha in the year 2009-

10 (Economic Survey, 2010-11). Several factors are

responsible for low productivity among which

diseases like leaf spot, collar rot, stem rot, bud

necrosis, etc., are very important. Stem rot, collar rot

and afla root are the major soil borne diseases of

groundnut causing extensive damage to the crop. S.

rolfsii attacks the crop at all the stages causing seed

rot, seedling blight, stem rot and pod rot, the most

common being stem rot (Deepthi and Eswara reddy,

2013). On the contrary, both A. niger and A. flavus

primarily attack the seedling stage causing collar rot

and aflaroot. Out of the only economical

management measure recommended for these

diseases is to treat seed with fungicides, but it can not

protect the crop for longer period (T.benitez ,2004).

The chemical method developed control too has its

own limitations such as high capital investment, non

remunerative, poor availability, selectivity,

temporary effect, efficacy affected by physio

chemicals and biological factors, development of

pest resistance, pollution of food and feeds, health

hazards, environmental pollution, etc. Considering

these limitations, biological control is an important

approach in this direction. (N.B. bagwan, 2011).

Reduction of amount of inoculum or disease

producing activity of a pathogen accomplished by

through one or more organisms other than man"

(Cook and Baker, 1983).

MATERIALS AND METHODS

Experiment was conducted under direct sown

conditions taking groundnut cultivar J-11 in upland

field having clay loam soil. The land was well

prepared by ploughing two three times. Isolaton of

Biological control agents from soil by serial dilution method: Different strains of Trichoderma were

isolated from rhizosphere soil of healthy groundnut

plants by serial dilution technique on Trichoderma

specific medium (Elad, 1980).. Talc powder based

formulations of different strains of Trichoderma spp.

were developed and used as seed treatment. Seeds of

chickpea were treated with Different strains of

Trichoderma spp. @ 10 g /kg seed. Hexaconazole

+Zineb was used @ 3 g kg/seed. Untreated control

was kept for making comparison. Seeds @ 120 kg/ha

were sown in each plot under randomized block

design with three replications. Fertilizers i.e. NPK @ 20:60:0 / ha were applied as basal dose. Plant growth

parameters i.e. plant height cm, number of branches

/plant and yield parameters i.e. No. of pods / plant

and pod yield / plant were recorded from each

treatment.

Whenever required, the glasswares of Borosil make,

plastic plates of Tarson make, blotter paper of

standard grade and chemicals of standard grade

(Merck, Qualigens, S.D. fine etc.) were used during

the course of investigation. All the glasswares,

polythene bags, ethyl alcohol, formalin, chemicals and other materials were procured from the Thakur

Chhedilal Barrister College of Agriculture and

Research Station, Bilaspur (C.G.).

The following equipments or materials used in

present investigation were-

1. Autoclave for media sterilization

2. BOD incubator for incubation

3. Binocular research microscope

4. Compound microscope

5. Hot air oven for glassware sterilization

G

RESEARCH ARTICLE

304 SHWETA MISHRA, ARWIND KURRE AND R.K.S. TIWARI

6. Forceps, needles, blades, inoculation needle, cork

borer, petri dishes

7. Growth chamber

8. Laminar air flow for isolation and purification

Efficacy of talc based formulations of

Trichoderma strains as seed treatment for plant

growth promoting activities in groundnut

Treatment details

Seed treatment with Trichoderma strains @ 10 g /kg

seed

Seed treatment with Hexaconazole + Zineb @ 3 g

/kg seed.

Total number of treatments: 12

Replications: 03

Design: RBD

Plot size: 2 mts x 0.60 mt Fertilizer: N 20 P60 K

0/ha

Dates of sowing – 9/12/2016 Observations to be recorded

Growth parameters: Plant height cm

Number of branches

Yield parameters: No. of pods / plant

Pod yield / plant

Treatment details

S.No. Treatments

1 Trichoderma harzianum (T 1)

2 Trichoderma harzianum (T 2)

3 Trichoderma harzianum (T 3)

4 Trichoderma harzianum (T 4)

5 Trichoderma harzianum (T 5)

6 Trichoderma harzianum (T 6)

7 Trichoderma harzianum (T 7)

8 Trichoderma harzianum (T 8)

9 Trichoderma viride (T 18)

10 Trichoderma harzianum (T 28)

11 Hexaconazole + Zineb (Fungicide)

12 Control

RESULTS AND DISCUSSION

Experiment was conducted in vivo to study the plant

growth promoting activities of strains of

Trichoderma harzianum and Trichoderma viride

used as seed treatment@ 10 g /kg seed in groundnut.

Various observations of growth parameters and yield

components were recorded Data from Table indicate that Trichoderma strain number T2 (34cm), T4 (32.8

cm) and T3 (32 cm) were significantly at par among

themselves and more effective in increasing plant

height over Trichoderma harzianum strain number

T1 (31.2 cm), T5 (31 cm), Trichoderma viride strain

number T18 (30.6 cm) and Trichoderma harzianum

strain number T8 (30.4 cm) which are statistically at

par among themselves .Whereas, Trichoderma

harzianum strain number T 3 (5.6cm), T5 (5.6cm),

T8 (5.6cm), T1 and T2 were significantly more

effective in increasing number of branches/ plant over other strains and control. Numbers of pods /

plant were significantly higher in treated plots over

control (8.4) with maximum number of pods from

T18 (10.8), T2 (9.6), T1 (9.6) and T3 (9.0). However,

numbers of pods / plant recorded from T4 (6.4) were

significantly less over other strains and at par with

control (8.4). Similarly, unfilled pods/plant were also

less in T4 (1.4) and at par with T5 (3.0),T6 (3.2) and

T7 (2.1). Whereas significantly higher number of

unfilled pods were recorded from control (5.8). All

strains were found significantly effective in

increasing filled pods/ plant over control (2.6).

However, significantly higher number of filled pods were recorded from Trichoderma viride T18 (6.6),

T7 (6.4) and T2 (6.2) over other strains. Pod yield

(g) / plant recorded from plots treated with different

isolates shows significantly higher pod yield (g) from

Trichoderma harzianum strain number T2 (12.6 g),

T1 (12.4 g), T3 (12 g), Trichoderma viride T18 (11.8

g), T6 (10.8 gm), T4 (10.8 gm) and T28 (10.6 gm)

over control (6.6gm). Similarly, in pot culture assay

soil treatment with T.harzianum, T. viride was found

to enhance the root/shoot length. Increased growth

by Trichoderma sp. was also induced by a diffusible growth-regulating factor (Windham et al.,

1986).Similar findings reported by Saralamma and

Reddy (2003) confirms above findings regarding

plant growth promoting activities of different

Trichoderma strains isolated from different locations.

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 305

Table 1. Plant growth promoting activity of indigenous strains of Trichoderma harzianum / Trichoderma

viride as seed treatment in groundnut.

Fig. 1: Plant growth promoting activity of indigenous strains of Trichoderma harzianum / Trichoderma viride

as seed treatment in groundnut.

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11

Pod yield/ plant ( g)

Filled pods/ Plant

Unfilled pods/ plant

No. of pods / plant

No. of branches

Plant height ( cm)

Strains Designation Plant

height

( cm)

No. of

branches

No. of

pods /

plant

Unfilled

pods/

plant

Filled

pods/

Plant

Pod

yield/

plant

( g)

Trichoderma harzianum T 1 31.2 4.8 9.6 4.6 5.0 12.4

Trichoderma harzianum T 2 34.0 4.8 9.6 3.4 6.2 12.6

Trichoderma harzianum T 3 32.0 5.6 9.0 3.4 5.6 12.0

Trichoderma harzianum T 4 32.8 4.6 6.4 1.8 5.2 10.8

Trichoderma harzianum T 5 31.0 5.6 8.6 3.0 5.6 9.4

Trichoderma harzianum T 6 29.0 3.8 9.0 3.2 5.8 10.8

Trichoderma harzianum T 7 27.4 4.0 8.6 2.1 6.4 12.4

Trichoderma harzianum T 8 30.4 5.6 8.8 4.8 4.0 10.4

Trichoderma viride T 18 30.6 5.4 10.8 4.2 6.6 11.8

Trichoderma harzianum T 28 28.4 4.2 10.0 4.2 5.8 10.6

Control 24.6 3.8 8.4 5.8 2.6 6.6

S E m (±) 0.70 0.28 0.95 0.48 0.25 0.65

CD 5% 2.08 0.83 2.79 1.42 0.74 1.91

306 SHWETA MISHRA, ARWIND KURRE AND R.K.S. TIWARI

Plate 1. Plant growth promoting activity of indigenous strains of Trichoderma harzianum / Trichoderma viride as

seed treatment in groundnut.

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 307

REFERENCES

Benitez, T. (2004). Biocontrol mechanisms of

Trichoderma strains. International microbiology. 7:

249-260.

Bagwan, N.B. (April, 2011). Evaluation of

biocontrol potential of Trichoderma species against

Sclerotium rolfsii, Aspergillus niger and Aspergillus

flavus, International Journal of Plant Protection, Vol.

4 No. 1 :pp 107-111

Cook, R.T. and Baker, K.F. (1983). The nature and

practices of biological control of plant pathogens. In: APS Books, St. Paul. Minn.539 pp

Deepthi, K.C. and Reddy Eswara, N.P. (2013).

Stem rot of groundnut(ARACHIS HYPOGAEA L.)

induced by Sclerotium Rolfsii and its management,

International Journal of Life Science Biotechnology

and Pharma Research ,Vol.2,No.3.

Elad, Y. Chet, I. and Katan, Y. (1980).

Trichoderma harzianum a biocontrol agent effective

against Sclerotium rolfsii and Rhizoctonia solani.

Phyto path.70: 119-121.

Saralamrna, S. and Vithal Reddy, T. (2003).

“Integrated Management of Sclerotial Root Rot in

Groundnut”, National Seminar on Stress

Management in Oilseeds For Attaining Self Reliance

in Vegetable Oil Indian Society of Oilseeds

Research, Directorate of Oilseeds Research, Hyderabad January 28 - 30, pp. 20 - 21. 71.

Windham, M. T., Elad, Y. and Baker, R. (1986). A

mechanism for increased plant growth induced by

Trichoderma spp. Phytopathology 26: 518-521.

308 SHWETA MISHRA, ARWIND KURRE AND R.K.S. TIWARI

*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 309-312. 2020

EVALUATION OF SOYBEAN CULTIVARS FOR RESISTANCE TO ALTERNARIA

LEAF SPOT CAUSED BY ALTERNARIA ALTERNATA

Raj Kumar Fagodiya*, Amit Trivedi, B.L. Fagodia and R.S. Ratnoo

Department of Plant Pathology, Rajasthan College of Agriculture (MPUAT) Udaipur

(Rajasthan) 313 001

Email: fagodiyarajkumar@gmail.com

Received-02.05.2020, Revised-24.05.2020

Abstract: The present study was undertaken to study Biology and Management of Alternaria leaf spot of soybean caused by Alternaria alternata, as the disease is quite destructive in all the soybean growing areas. The field experiment was conducted two consecutive years Kharif season 2018 and 2019 at Department of Plant Pathology, Rajasthan College of Agriculture, Udaipur. Ten cultivars of soybean were screened for these diseases under artificial inoculated field conditions and results revealed that 3 cultivars namely (JS-9305, JS-9752 and RVS 2002-04) exhibited moderately resistant (MR) reaction, while 5 cultivars viz. JS-2029, RKS-18, RKS-113, JS-9560 and RKS-45 exhibited moderately susceptible (MR) reaction. Rest of cultivars viz. RKS-24 and JS-335 showed susceptible (S) reaction.

Keywords: Alternaria leaf spot, Cultivars, Resistance, Soybean

INTRODUCTION

oybean (Glycine max L.) is a member to family

Leguminosae and sub-family Papilionaceae. It is

an important oil seed crop grown in several

developed countries like USA, China, Brazil,

Mexico, Russian federation and India. Soybean has

originated from China during 2800 BC, containing

about 43.2 per cent protein, 20.9 per cent oil, 19.5

per cent fat, 3.7 per cent fibre and small amount of

vitamin B complex and vitamin E (Singh, 2010). In

India, it ranks third after groundnut and rapeseed-mustard in vegetable oil economy and is cultivated

on 10.47 million hectares with total production of

1.07 million tonnes and average yield 1207 kg/hac.

In Rajasthan it is mainly grown in Jhalawar,

Chittorgarh, Kota, Bundi, Baran, Banswara,

Pratapgarh, Udaipur and Bhilwara districts, covering

an area of 0.89 million hectares with production of

1.07 million tonnes and average yield 1049 kg/hac.

(Anonymous, 2017-18).

The area under soybean is consistently increasing

every year in Rajasthan. However due to continuous

monocropping, same variety use, seed material exchanges becoming routine and found contributing

for increasing severity of foliar diseases of soybean

and yield losses year after year. Among the foliar

diseases of soybean, Alternaria leaf spot is

distributed throughout the soybean growing areas of

India but it is of special significance in Madhya

Pradesh, Maharashtra, Rajasthan and Delhi (Gupta

and Chauhan, 2005). Members of genus Alternaria

are cosmopolitan in nature and important fungal

pathogen which mostly cause diseases on aerial parts

of many plants worldwide. The members of this genus like A. alternata, A. solani, A. porri, A.

helianthi, A. duaci, A. carthami, A. tenuissima and A.

macrospora causes different diseases in their

respective hosts (Rostem, 1994). All the aerial parts

of the soybean plant are susceptible to Alternaria spp. which reduces the quality and quantity of seed

yield. In present situation cultivated soybean

varieties by the farmers are susceptible to the

diseases. The diseases can be managed successfully

by using chemical sprays but to avoid ecological

pollution and to reduce the input cost use of resistant

varieties against these diseases is of prime

importance to overcome these losses. Use of resistant

cultivar of crop plays an important role in combating

the losses caused by diseases as it is eco-friendly,

easy and cost-effective disease management strategy. A genotype with disease resistance and high yield

potential offered scope in breeding programme to

evolve multiple tolerance genotypes combined with

good yield. Keeping in view the importance of crop,

disease and considering scope of resistant varieties in

IDM technology, the present study was conducted to

screen the soybean advance lines against Alternaria

leaf spot diseases with high yield superiority for the

identification of resistant sources in available

cultivars.

MATERIALS AND METHODS

Soybean cultivar seed- The ten cultivars/varieties of

soybean received from All India Coordinated

Research Project on Soybean, Agriculture Research

Station, Kota (Agriculture University, Kota) were

screened against the most virulent isolate A.

alternata (1 x 103 conidia ml-1.) found in pathogenic

potential studies were used.

Screening of cultivars/varieties- Under artificial

inoculated field conditions, 10 cultivars/varieties

were evaluated at the field of Department of Plant Pathology, Rajasthan College of Agriculture,

Udaipur. Seeds were sown in rows each of 3 m

length and maintaining row to row and plant to plant

distance as 30 x 5 cm, with three replications in

S

RESEARCH ARTICLE

310 RAJ KUMAR FAGODIYA, AMIT TRIVEDI, B.L. FAGODIA AND R.S. RATNOO

Randomized Block Design (RBD). Observations on

disease rating were recorded two times first at pre-

flowering stage and second at maturity stage, when

the crop was 45 days old and the expression of

disease was clear, using a standard (0-5 disease

rating scale). Observations for percent disease index

were recorded by visual scoring as per the standard

disease rating 0-5 scale (Sangeetha and

Siddaramaiah, 2007).

Standard disease rating scale

Scale Description of the symptom

1.

2.

3.

4.

5.

Small irregular spots covering <5% leaf area.

Small irregular brown spots with concentric rings covering 5.1-10% leaf area.

Lesions enlarge, irregular brown with concentric rings covering 10.1-25% leaf area.

Lesions coalease to form irregular and appears as a typical leaf spotting symptoms covering

25.1-50% leaf area.

Lesions coalease to form irregular and appears as a typical leaf spotting symptoms covering

>50% leaf area.

The above rating scales or grades are utilized for the

calculation of PDI using the following formula - The

average intensity of each plot was worked out by

using formula

Per cent disease index (PDI) =

Sum of all individual disease rating

------------------------------------------------- x 100

Total no. of plants ass. x maximum rating

The disease reaction was qualitatively expressed as

resistant (score 1), moderately resistant (score 2), moderately susceptible (score 3), susceptible (score

4) and highly susceptible (score 5).

RESULTS AND DISCUSSION

Host plant Resistance is one of the best effective

tools to get rid of the diseases. Utilization and proper

screening of resistant sources is most important. To

find out the stable sources of resistance against

Alternaria leaf spot in soybean ten released varieties

(RKS-113, RKS-18, JS-9752, JS-9560, JS-9305, RKS-24, JS-2029, JS-335, RVS-2002-04 and RKS-

45) were screened under artificial epiphytotic

conditions during both the years i.e. Kharif 2018 and

2019. The experiments were conducted in single row

plot 3 m row length with plant to plant distance 5 cm,

three replications using RBD (Table-1).

Data shows that, including 10 varieties of soybean,

JS-9305 exhibited lowest disease in both the

observation i.e. at pre flowering and maturity stage

with PDI 14.2 and 16.7%, respectively. This was

followed by JS-9752, which showed PDI 15.6 and 18.4% respectively at both the stages. RVS 2002-04

and JS-2029 showed PDI 16.8 and 30.0%,

respectively at pre flowering and 17.9 & 32.2 per

cent disease index at maturity stage. Rest of the

entries viz. RKS-18, RKS-113, JS-9560, RKS-45, JS-

335 and RKS-24 showed the disease intensity in the

range of PDI 33.1 to 61.6, at pre flowering and in the

range of 35.2 to 63.4 per cent disease index, at

maturity stage in the year 2018 (Table 1 and Fig 1).

The similar results were also reported by Mahesha et

al. (2009) evaluated 204 genotypes under natural and

laboratory conditions against major disease and

reported several genotypes having multiple resistance

sources.

In the year 2019, Data shows that JS-9305 exhibited

lowest disease in both the observation i.e. at pre flowering and maturity stage with PDI 16.3 and

19.6%, respectively. This was followed by JS-9752,

which showed PDI 18.2 and 21.7% respectively at

both the stage. RVS 2002-04 and JS-2029 showed

PDI 18.7 and 32.6%, respectively at pre flowering

and 20.8 & 34.8 per cent disease index at maturity

stage. Rest of the entries viz. RKS-18, RKS-113, JS-

9560, RKS-45, JS-335 and RKS-24 showed the

disease intensity in the range of PDI 35.5 to 63.3, at

pre flowering and in the range of 38.5 to 65.8 per

cent disease index, at maturity stage (Table 1 and Fig 1). The similar results were also reported by

Dhurwey (2015) screened 30 soybean varieties

against Alternaria leaf spot and reported that the

incidence of Alternaria leaf spot ranged from 3.0 to

18.0 per cent in cultivar Bragg and Shivalik, higher

incidence of Alternaria leaf spot was recorded in

cultivars NRC 12, NRC 37, MAUS 61, MAUS 71,

VLS 47 from 13.0 to 17.0%.

None of the tested varieties showed immune

reaction, however three varieties namely (JS-9305,

JS-9752 and RVS 2002-04) exhibited moderately resistant (MR) while five varieties (JS-2029, RKS-

18, RKS-113, JS-9560 and RKS-45) showed

moderately susceptible. Rest others were categorized

as susceptible to highly susceptible.

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 311

S. No. Category based on PDI variety

1. Absolutely Resistant NIL

2. Resistant NIL

3. Moderately resistant JS-9305, JS-9752 and RVS 2002-04

4. Moderately susceptible JS-2029, RKS-18, RKS-113, JS-9560 and RKS-45

5. Susceptible RKS-24 and JS-335

6. Highly susceptible NIL

Table 1. Screening of soybean cultivars against Alternaria leaf spot under inoculation of A. alternata Kharif 2018 and 2019

S.

No.

Germplasm/Variety

Pre- flowering stage Per cent

Disease Index (PDI)

Maturity stage Percent

Disease Index (PDI)

Disease

Reaction 2018 2019 Pooled 2018 2019 Pooled

1. RKS-113 34.2

(35.7)

37.4

(37.6)

35.8

(36.7)

37.5

(37.7)

40.2

(39.3)

38.8

(38.5)

MS

2. RKS-18

33.1

(35.1)

35.5

(36.5)

34.3

(35.8)

35.2

(36.3)

38.5

(38.3)

36.8

(37.3)

MS

3. JS-9752 15.6

(23.2)

18.2

(25.2)

16.9

(24.2)

18.4

(25.4)

21.7

(27.7)

20.0

(26.5)

MR

4. JS-9560 40.8

(39.7)

42.4

(40.6)

41.6

(40.1)

41.3

(39.9)

43.9

(41.5)

42.6

(40.7)

MS

5. JS-9305 14.2

(22.1)

16.3

(23.8)

15.2

(22.9)

16.7

(24.1)

19.6

(26.2)

18.1

(25.2)

MR

6. RKS-24 61.6

(51.7)

63.3

(52.7)

62.4

(52.2)

63.4

(52.7)

65.8

(54.2)

64.6

(53.5)

S

7. JS-2029 30.0

(33.2)

32.6

(34.8)

31.3

(34.0)

32.2

(34.5)

34.8

(36.1)

33.5

(35.3)

MS

8. JS-335 58.4

(49.8)

59.6

(50.8)

59.0

(50.1)

60.7

(51.8)

62.5

(52.2)

61.6

(51.7)

S

9. RVS 2002-04

16.8

(24.2)

18.7

(25.6)

17.7

(24.9)

17.9

(25.0)

20.8

(27.1)

19.3

(26.08)

MR

10. RKS-45 44.2

(41.6)

46.3

(42.8)

45.2

(42.2)

47.2

(43.3)

50.0

(45.0)

48.6

(44.2)

MS

SEm±

CD at 5%

CV%

1.42

4.22

7.06

1.49

4.43

6.98

0.89

2.55

7.02

1.77

5.27

8.30

1.62

4.97

7.29

1.05

3.03

7.78

Category based on PDI:- 0 = Free from disease (I= Immune), 1 = 1 to 10 PDI (R= Resistant), 2 = 10.1 to 25

PDI (MR=Moderately resistant),

3 = 25.1 to 50 PDI (MS= moderately susceptible), 4 = 50.1 to 75 PDI (S = Susceptible), 5 = >75 PDI (HS=

Highly susceptible)

312 RAJ KUMAR FAGODIYA, AMIT TRIVEDI, B.L. FAGODIA AND R.S. RATNOO

Fig. 1. Screening of soybean cultivars against Alternaria leaf spot under inoculation of A. alternata during

Kharif 2018 and 2019 (Pooled)

The work on identification of multiple disease

resistance sources in cultivable and wild soybean has

been undertaken many workers like Anonymous

(2016), Ingle et al. (2016). In current investigation,

entries showed varied reaction ranging from HR to S.

This might be due to the availability of inoculums or

differential interactions of host genotypes with

different varieties. Zade et al. (2018) evaluated 33

advance lines under natural field conditions against

Alternaria leaf spot and reported 12 genotype

exhibited Highly Resistant (HR) reaction, While 14 genotype shown Moderately Resistant (MR) reaction

and 4 genotype exhibited Moderately Susceptible

(MS) reaction. Rest of genotype showed Susceptible

(S) reaction.

In the present study, varieties viz., JS-9305, JS-9752

and RVS 2002-04 which have shown maximum

resistance against the Alternaria leaf spot. Thus,

these resistant sources of soybean varieties may have

scope in future for breeding in development of

varieties or in integrated disease management

programme.

ACKNOWLEDGEMENT

Authors are thankful to Department of Plant

Pathology, Rajasthan College of Agriculture

(MPUAT), Udaipur, Rajasthan for providing

opportunity and assistance during research work.

REFERENCES

Annonymus (2016). Annual Report of Indian

institute of Soybean Research. Indore (MP)

Anonymous (2017-18). Directorate of Economics &

Statistics. Department of Agriculture Cooperation &

Farmers Welfare. Government of India.

Dhurwey, D.S. (2015). Studies on diseases of

soybean with reference to Colletotrichum dematium

causing seed rot and pod blight and its management.

Ph.D. (Ag.) Thesis, Jawaharlal Nehru Krishi Vishwa

Vidyalaya, Jabalpur pp- 47.

Gupta, G.K. and Chauhan, G.S. (2005).

Symptoms, Identification and Management of

Soybean Diseases. Technical Bulletin no. 10. Pub. IISR, Indore.

Ingle, Y.V., Chandankar, G.D., Patil, P.V. and

Patil, C.U. (2016). Evalution of advance lines of

soybean for resistance to major diseases under

natural field condition. Indian Journal of Agricultural

Research 50(1): 84-87.

Mahesha, B, Patil, P.V. and Nandini, P. (2009).

Identification of multiple disease resistance sources

in soybean. Crop Research 37: 213-216.

Rotem, J. (1994). The Genus Alternaria, Biology,

Epidemiology and Pathogenicity. The American

Phytopathological society. USA. 325 pp. Sangeetha, C.G. and Siddaramaiah A. L. (2007).

Epidemiological studies of white rust, downy mildew

and Alternaria blight of Indian mustard (Brassica

juncea (Linn.) Czern. And Coss.). African Journal

of Agricultural Research 2:305-308.

Singh, S.S. (2010). Crop management under

irrigated and rainfed conditions. Kalyani publishers

New Delhi pp-574.

Zade, S.B., Ingle, Y.V., Ghuge, A. S. and Wasule,

D. L. (2018). Screening of soybean genotypes for

resistance against Alternaria leaf spot disease. Journal in Science, Agriculture & Engineering

8(27):198-199.

*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 313-316. 2020

ETHNO MEDICINAL KNOWLEDGE OF SPICES AND THEIR USES BY TRIBAL

COMMUNITY OF RAJASTHAN, INDIA

Deepa Indoria*1 and S.R. Verma

2

1Krishi Vigyan Kendra, Chittorgarh, MPUAT, Udaipur Rajasthan

2Institute of Extention Education, CCSAU, Hisar, Hariyana

Email: deepa.indoria123@gmail.com

Received-03.05.2020, Revised-27.05.2020 Abstract: A spice is a dried seed, fruit, root, bark or vegetative material used in nutritionally insignificant amount as a food supplement for the reason of flavouring and imparting taste. Spices are defined as "a strongly flavoured or aromatic substance of vegetable origin, obtained from tropical plants, commonly used as a condiment". In ancient times, spices were as valuable as metal gold; and as noteworthy as medicines and perfumes. No country in the world cultivates as a lot of kinds of spices as India with quality spices come from Kerala, an Indian state. Because of the varying climates in India-from tropical to sub-tropical, temperate-almost all spices are grown in this country. In almost all of the 28 states and seven union territories of India, at least one spice is grown in profusion. Spices used by tribe as herbal ethno medicine to treat several common diseases such as fever, indigestion, diarrhoea, dysentery, vomiting, asthma, heart diseases, headache,

boils, leucoderma, bold disorders, piles and insect bites etc. were documented. High level of commercial use as ethno medicinal practices adversely affect the physical, social and economic welfare of the tribal community of Chittorgarh ,Rajasthan . A survey (December 2012 to December 2013) reported data on four-teen spices belonging to twelve families identified from this region. Brief information about the scientific names with family, common names (English), plant part used, way of application of plant parts and their uses against diseases have been presented. Present study reveals that some species are important in primary healthcare sys-tem of tribal communities. This paper deals with the biodiversity of spices and their ethno medicinal uses by the tribal communality for conservation and utilisation in Chittorgarh ,Rajasthan.

Keywords: Spices, Ethno medicinal uses, TSP (Tribal specific place) Antimicrobial activity

INTRODUCTION

hittorgarh is located at 24.88°N 74.63°E. It has

an average elevation of 394 metres

(1292 ft).Chittorgarh is located in the southern part

of the state of Rajasthan, in the north western part of

India.It is located beside a high hill near the

Gambheri River.Chittorgarh is located between 23°

32' and 25° 13' north latitudes and between 74° 12'

and 75° 49' east longitudes in the south eastern part

of Rajasthan state.The three panchayat samitee

encompasses 10,856 square km (3.17 per cent of the

Rajasthan State) area of land. In chittorgarh contained various tribes like bheel

,Rawat meena ,Gameti . In four P.S.of Chittorgarh,

the tribal population was highest in south side three

panchayat samitee. Thus, the tribal community was

typically concentrated in the rural areas. The tribe

live mostly on hill- tops and on slopes forming small

and isolated villages. Most of these villages were

located at remote and far away from the towns

and therefore, the people mostly depend on the

natural resources from the nearby forests for their

livelihood including medicinal herbs for

treatments of different diseases and ailments. Generally, the traditional knowledge of medicinal

herb was confined to local medicine men. How-

ever, some secret of medicinal virtues could be

obtained from them through close contact. The medicine men have practiced and developed this

knowledge of the use of medicinal herbs through

their age long trial and error methods and

passed on orally from generation by generation.

It is important to save this traditional knowledge of

biological heritage and explore new resources.

Traditional and ethnic knowledge has played a

significant role in the discovery of novel ideas

about conservation of natural resources. Spices

have good anti-oxidant and preservative proper-ties

as well as anti-microbial and antibiotic properties, and therefore, are also used for medicinal purposes.

Some of the spices are rich in iron, vitamins, trace

metals and potassium. About 60 varieties of

spices are grown in India (Babu et al. 2013)

which is a well known land of spices from the

ancient period onwards (Mathew 2013). Luxuriant

forest, abound in all parts of state and variety of

medicinal plants, herbs, shrubs, bamboo and trees

growing in the state are rich. There are number of

plants whose medicinal values have been

recognized but very little effort has been made to

develop the ethno medicinal plants in the past. It is essential for the tribal communities to understand

the need for sustainable utilization of these plants.

C

RESEARCH ARTICLE

314 DEEPA INDORIA AND S.R. VERMA

Plate 1. With Farmer: Ginger and Turmeric field

MATERIALS AND METHODS

Study was conducted in Three panchayat

samitee(Bari sadri ,Bhadesar ,Dungla ) of three

panchayat samitee chittorgarh Rajasthan during

December 2018-19 to December 2019-20 The survey

was done in spring and monsoon seasons when

plants bloom and show extensive growth with the

view of study their natural habitat and distribution.

The tribal community and the area were selected

purposely due to maximum biodiversity of ethno

medicinal plants in the area. The information and

data was collected from three panchayat samitees

of Chittorgarh. Five tribal places were selected from each three panchayat samitee and ten tribal

from each three panchayat samitee were selected.

group between 25 to 75 years. They were local

herbalists, healers, farmers, village headman,

elders and students of both the sexes. Standard

ethno medicinal investigations procedures were

followed (Jain 1995, Martin 1995). The data

collected during the fieldwork have been entered

and analyzed in a database generated with Mi

tract wise . A three panchayat samitee wise list of

tribal people was prepared and fifty tribal of each

three panchayat samitee were selected randomly.

Fig. 1: Map showing the study area of Rajasthan

Thus, the total sampling consisted of 200 tribal

peoples spread over three Panchayat samitee . People

to people contract in the form of personal interview

were conducted. Thus the primary data were

collected with the help of interview schedule

through a questionnaire. Secondary data were

obtained from published journals. Our respondents

were in a range of age corset Excel 2007 software.

Data collected about spices biodiversity, their

ethno medicinal uses and related information

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 315

about tribal com-munity of Chittorgarh were

documented.

RESULTS AND DISCUSSION

The present study revealed 12 spices be-longing to 12 families namely Zingiberaceae, Solanaceae,

Apiaceae, Piperaceae, Brassicaceae, , Leguminosae,

Liliaceae, Punicaceae, , Rutaceae and Lmiaceae

were docu-mented for their ethnomedicinal uses

against different diseases (Table 1). Plant parts

used for treatment were leaves (05 nos.), bark

(01 no.), bulb (01 no.), rhizome (02 nos.), fruits

(03 nos.) and seeds (03 nos.) Three different mode

of application of plants parts based on use for

treatment of aliments are internal (08 nos.),

external (02 nos.) And internal/external (04 nos.)

The spices studied were enumerated with their

Scientific names, family names, common names

(English) plant parts used, way of application and uses in Table 1. The tribal com-munity was

unique not only in practice of rituals and customs

but also in practice of indigenous medicinal

system compared to other tribes of Chittorgarh

and rest part of India. Each ethnic group has

some unique knowledge of ethnomedicinal plants

and the tribal community were not an exception

(Bennet 1983, Rai et al. 1998).

Table 1. Ethno medicinal uses of Spices by tribal community of Chittorgarh

Scientific name

with family

Common

name

Plant part

use

Uses (ailments treated

Allium sativum L

Liliaceae

Garlic Bulb Bulb is used against skin diseases and bulb paste

used against bone fracture.

.Amomum

subulatum (Roxb.)

Zingiberaceae

cardamom

Large

Seed Seed is useful in indigestion, vomiting, disease of

rectum, mouth and head.

Brassica juncea L.

Czern Brassicaceae

Mustard Seed The paste of seeds is externally used on boils and

skin allergy.

Capsicum annuum L. Solanaceae

Chilli Fruit Fruit used in headache, rheumatism, gastritis and digestive diseases

Coriandrum sativum

L. Apiaceae

Coriander Fruit and

Leaf

Fruit used in diuretic, antipyretic, stomachic,

stimulant, laxative, and anthelmintics. Leaf paste is

ap-plied on allergic affected area for a week.

Curcuma longa L.

Zingiberaceae

Turmeric Rhizome Rhizome juice mixed with honey is used against

anaemia. Paste of fresh turmeric with leaves of

neem (Azadirachta indica) and paste of turmeric

and bermuda grass (Cynodon dactylon) helps in the

healing of itches, boil, rheu-matism, urticaria, and

ringworm

Mentha piperita L.

Lamiaceae l

Mint Leaf Five to six leaves mixed with 50 ml of water used

against indigestion.

Murraya koenigii L.

Sprengal Rutaceae

Curry leaf Leaf and

Root

extract useful in leucoderma, bold disorders, piles

and stop vomiting. Leaves paste used against bruises and eruption

Piper nigrum L.

Piperaceae

Pepper Seed Seed used in gastrointestinal and improve

digestion.

. Punica granatum L.

Punicaceae l

Pomegranate Fruit and

Bark

Fruit juice is used as tonic for the heart, stopping

nose bleeds and toning skin. Fruit and bark used

against diarrhea and dysentery.

Tamarindus indica

Leguminosae

Tamarind Bark A decoction of bark is given in cases of paralysis,

ulcers & in-flammations.

Zingiber officinale

Rose. Zingiberaceae

Ginger Rhizome laxative, aphrodisiac, carmina-tive useful in heart

diseases, throat and asthma. treatment of aliments

are internal

Plant species used by tribe as herbal ethno

medicine to treat several diseases like fever,

indigestion, diarrhea, dysentery, vomiting, asthma,

heart diseases, headache, boils, leucoderma, bold

disorders, piles and insect bites are the common

ailments among different age groups of people

(Table 1). Photographs of some spices used by

tribal community are presented in Plate 1.

Documentation of these spices would not only

open opportunity to provide new medicines but

will also help in their conservation (Rai et al. 1998).

In hilly areas, traditional cropping is not productive

and therefore, in situ conservation and planting high

value spices may be a better alternative.

316 DEEPA INDORIA AND S.R. VERMA

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*Corresponding Author

________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 317-320. 2020

EFFECT OF SOAKING AND PLACEMENT OF SEED ON GERMINATION AND

SEEDLING EMERGENCE IN LITCHI

Narayan Lal1, E.S. Marboh

2*, A.K. Gupta

2, Abhay Kumar

2 and Vishal Nath

2

1ICAR-Indian Institute of Soil Science, Bhopal, MP

2ICAR-National Research Centre on Litchi, Muzaffarpur, Bihar

Email: esmarboh@gmail.com Received-06.05.2020, Revised-25.05.2020

Abstract:An experiment was conducted at ICAR-NRC on Litchi, Muzaffarpur during 2018 to assess the effect of soaking of seed, orientation and depth of seed sowing on germination and seedling emergence in litchi. Result indicated that soaking of seed in water before sowing had improved seed germination in litchi. The maximum germination was found in GandakiLalima with 92.58% as compared to without soaking (62.75%).There was a significant reduction in seedling emergence with an increase in burial depth. Seeds sown at 1 cm depth showed the highest seedling emergence with an average percentage of 79.81.The highest seed germination was found in lay flat orientation when seeds were sown at the

depth of 1 cm.Litchi seedlingemergence was greatest and most rapid when seeds were sown 1 cm deep and positioned flat, on their sides. Keywords: Effect, Germination, Litchi, Seed

INTRODUCTION

itchi (Litchi chinensisSonn.) is an evergreen

subtropical fruit tree and important member of

family Sapindaceae, which has strong mycorrhizal

association (Lal and Nath, 2020). The litchi is one of the most environmentally sensitive (Lal et al., 2017a)

fruit tree restricted to few a countries in the world

and in few states in India. Recently, it has been

reported that litchi is performing well in Southern

parts of India where difference of temperature was

less than 4 °C and humidity difference of about 6.5%

during June-August (Nath et al., 2015) but major

litchi producing states in India are Bihar,

Uttarakhand, West Bengal, Punjab, Uttar Pradesh,

Jharkhand and Tripura. Litchi commenced flowering

during February-March in Bihar condition and intensity of flowering depends on previous years

fruiting, temperature during floral bud

differentiation, phenol content (Lal et al., 2019a) and

age of plants (Lal and Nath, 2020). A single panicle

produced hundreds to thousands of flowers (M1

flowers, Female flowers and M2 flowers) and

success of fruit set depend on the pollen grain

received from male parents (Lal et al., 2019 c and

d).Heavy fruit drop has been reported in litchi (Lal et

al., 2017b) and heavy fruit load affect fruit weight

and quality in litchi (Nagraj et al., 2019).

Litchi is commercially propagated through marcottage but multiplication by seed is very

important to create variability due to highly cross

pollinated nature (Lal et al., 2019b). Seedling

population gives enormous opportunity to select

improved and desired traits specific new genetic

stock or cultivars (Lal et al., 2019b). These all efforts

depend on seed germinability. The germination

performance of seeds and the seed placement in

sowing are important to achieve seedlings (Aou-ouad

et al., 2014; de Andrade et al., 2004). Litchi seeds are

‘‘recalcitrant’’ due to their high sensitivity to

desiccation. They quickly lose their viability after

extraction from the fruits. Litchi seeds completely

lost viability when they were kept outdoors for 2 d or

indoors for 6 d (Ray and Sharma, 1987). Xia et al.

(1990) found that litchi seeds germinated fully when harvested at 10 d before fruit maturity or at fruit

ripening time, but entirely lost seed viability after 6 d

of natural drying. Ray and Sharma (1987) pointed

out that seed germinability was positively correlated

with seed moisture content above the critical limit of

20% moisture content. Therefore, the seed moisture

content must be retained to ensure high seed

germination rates.Seed imbibition is an important

treatment for successful germination in any crops

because sufficient water is necessary for loosening

seed coat, rehydrating enzymes and their substrates, and provides energy to boost radicle. Especially, the

first phase of imbibition characterized by the rapid

water uptake plays a crucial role in seed germination

success (Harb, 2013). Slow imbibe water from soil or

unable to uptake sufficient water results early death

of seed. Soaking before sowing enables a more rapid

imbibition than is usually the case in a nursery bed,

resulting in more rapid seed germination (Schmidt,

2000).

Seed orientation and sowing depth both play

important roles in seed germination and seedling

emergence (Aou-ouad et al., 2014; Huang et al., 2007). Recalcitrant seeds of coconut sown in

horizontal orientation exhibited much quicker

germination and better growth of seedlings (Thomas,

1978). Planting seeds of Balanitesaegyptiaca

horizontally or vertically with stalk end down-ward

showed better germination (Elfeel, 2012). The

seedling emergence was slower when seeds were

sown at deeper depth in Rhamnusalaternus and R.

ludovici-salvatoris (Aou-ouad et al., 2014). Since

2013, we have started crossing technique in litchi and

L

RESEARCH ARTICLE

318 NARAYAN LAL, E.S. MARBOH, A.K. GUPTA, ABHAY KUMAR AND VISHAL NATH

developed hundreds of hybrid seeds each year but

could not get sufficient seed germination. We have

observed good germination percentage near shade of

nursery bed, good germination in some pockets of

bed and wide variation due to bedding materials. We

realized the importance of sowing of litchi seed. Therefore, studies are needed to get good seed

germination in litchi. Therefore, an experiment was

formulated with pre sowing soaking of seed,

orientation and depth of seed sowing. The objectives

of this experiment wereto find the best ways to

improve seed germination and seedling emergence,

which are important for raising sufficient variability.

MATERIALS AND METHODS

Fruit of different cultivars were collected from

National Active Germplasm Site (NAGS), ICAR-National Research Centre on Litchi, Muzaffarpur,

Bihar, at fully ripe stage and seed were extracted

from fruits. Two hundred seeds of each cultivar were

soaked in water and same quantities were sown

immediately after extraction from fruits in prepared

nursery bed. Seeds were soaked for 48 h in a plastic

drum filled with water. Seeds were sown in three

orientations (seed laid flat, seed laid vertically with

the radicle upward, and seed laid vertically with the

radicle downward). Seeds sown in each of the three

orientations were placed in soil at five different depths of 1, 2, 3, 4 & 5 cm. Three replicates were

used for each treatment and 20 seeds were sown in

each replicate. A randomized block design was used

in the experiment. Some seedlings began to emerge

at the surface of soil on day 7, and the final percent-

age of seedling emergence was determined two

weeks after sowing.The data of seed germination and

seedling emergence were statistically analyzedusing SPSS version 16.0 Statistical Software. Pearson

correlation tests were used to determine the

correlations of soaking time with germination.

ANOVA was used to test the differences in seedling

emergence.

RESULTS AND DISCUSSION

Seed germination varied from 24.56 to 62.75 % with

maximum in GandakiLalima and lowest in Bedana

without soaking in water but varied from 43.56 to

92.58 % with maximum in GandakiLalima and lowest in Bedana when seed soaked in water (Fig 1).

Soaking of seed in water before sowing had great

impact on germination. Water soaking improved

germination in litchi.Soaking of seeds in water

helped to reduce the time required for germination

and improved germination percentage. Zhang et al.,

(2015) reported that seeds of ‘Yeshengli’ litchi

soaked in water showed a slightly higher germination

percentage than seeds without the soaking treatment.

The imbibition process occurred when seeds were

submersed in water and soaking enabled a quicker imbibition and might be of benefit for rapid seed

germination (Schmidt, 2000).

Fig. 1: Germination of seed (mean ± SD) in different cultivars of litchi.

The orientation and burial depth both significantly

influenced germination and seedling growth in litchi.

There was a significant reduction in seedling

emergence with an increase in burial depth (Fig

2).Seeds sown at 1 cm depth showed the highest

seedling emergence with an average percentage of 79.81. The highest seed germination was found in lay

flat orientation when seeds were sown at the depth of

1 cm. The seedling emergence was lower and slower

when seeds were sown radicle upward at the sowing

depth of 1 cm (Fig. 2).The burial depth of seeds

significantly influenced the seedling recruitment in

litchi. There was a significant reduction in seedling

emergence of litchi with depths below 2 cm. Planting seeds at deeper depths probably resulted in more

consumption of the carbohydrate reserves during the

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 319

process of germination and seedling emergence

(Huang et al., 2007).The seedling emergence was

higher and quicker when seeds were placed flat, on

their sides and radicle downward than those planted

radicle upward at the burial depth of 1 cm. Therefore,

growers should ensure seed placement avoids a

vertical seed orientation with the radicle upward.In

the present study, soaking increased seed

germination percentage.Placing seeds flat and on

their sides, orienting the radicle downward, and

covering with 1 cm of medium exhibited the best

seedling emergence.

Fig. 2.Percentage of seedlings emergence (mean ± SD) at different seed orientations and burial depths in litchi.

CONCLUSION

It can be concluded that GandakiLalimahad good

ability for germination with 92.58%. The seedling

emergence reduced with an increase in burial depth.

Seeds sown at 1 cm depth showed the highest

seedling emergence with an average percentage of 79.81 in lay flat orientation.

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*Corresponding Author

________________________________________________ Journal of Plant Development Sciences Vol. 12(5): 321-326. 2020

PERFORMANCE OF PARENTS AND HYBRIDS FOR YIELD AND YIELD

ATTRIBUTING TRAITS IN TOMATO (SOLANUM LYCOPERSICUM L.)

Kiran Kumar1*, Dhananjay Sharma

2, Jitendra Singh

3 and S.S. Paikra

4

1Department of Vegetable Science, College of Agriculture Raipur

2Department of Vegetable Science, College of Agriculture Raipur

3Floriculture and Landscape Architecture, College of Agriculture, IGKV, Raipur

4College of Agriculture and Research Station, Janjgir-Champa IGKV, Raipur (C.G.) India

Email: kiran.nagraj90@gmail.com

Received-04.05.2020, Revised-28.05.2020

Abstract: A field experiment was conducted during rabi season 2017-18 in Randomized Block Design with three replications at Horticultural Research cum Instructional Farm, Department of Vegetable Science, IGKV, Raipur (C.G.). Six diverse and horticulturally superior lines of tomato were crossed with four testers in line x tester mating design. The resultant 24 hybrids (F1'S) along with their parents (six lines and four testers) were evaluated for eighteen yield and yield attributing traits in tomato. The experiment results revealed that parents 2014/TOLCVRES-3 performed best for characters viz., number

of flowers per cluster (6.38), number of fruits per cluster (4.84), pericarp thickness (mm) 6.18 mm and total soluble solid (°Brix) 4.49 °Brix. Fruit diameter (cm), average fruit wt. (g) and fruit length (cm) were observed in parents 2015/TOLCVRES-2 and 2015/TOLCVRES-4.Whereas fruit yield per plant (3.78 kg), days to first fruit harvest (70.99) and dry matter % of fruit (6.21%) recorded in parent H-86. Among all parents, H-86 and 2014/TOLCVRES-3 with the yield of 659.72 q/ha and 611.04 q/ha respectively were found to be better yielders. Among all hybrids PR X 14/TLCV-3, PC X 15/TLCV-2, KA X 15/TLCV-2, KA X 14/TLCV-3 and AV X 14/TLCV-1 were best performing in maximum number of quality and yield attributing traits like days to 50% flowering (27.00), maximum number of fruit cluster per plant (12.42), ascorbic acid (25.01 mg/100g), number of flowers per cluster (7.12), fruit diameter 7.00 cm, average fruit wt. (144.50 g),

fruit yield per plant (3.52kg), total soluble solid (5.71 ºBrix), and number of locules per fruit (5.24). Fruit yield per hectare was observed in the cross H–86 X 14/TLCV-3 (727.58 q), followed by KA X 14/TLCV-3 (724.13 q) and H–86 X 15/TLCV-4 (705.76 q). Therefore, recommended for generation advancement and selection of desirable progeny lines useful for Chhattisgarh plains.

Keywords: Tomato, Fruit yield, Genotypes, Parents, Hybrids

INTRODUCTION

omato (Solannum lycopersicum L.) is one of the

most important and popular vegetable crops in

the world. Tomato is popular due to its nutritive and

medicinal values. Nuez et al. 2004 identified it as the

horticultural crop with the highest commercial value.

In India; tomato is grown across all agro-ecological zones and occupies an area of about 801 thousand

hectares with an annual production of 22.33 million

tonnes, respectively (Anon., 2017). Tomato is

universally treated as ‘Protective Food’ since it is

very rich in minerals, vitamins, antioxidants,

essential amino acids, sugars and dietary fibers

which are important ingredients for culinary and

table purpose, chutney, pickles, ketchup, soup, juice,

puree etc. (Sekhar et al., 2010). Fresh fruit of tomato

are in great demand round the year throughout the

country. Generally, both determinate and indeterminate

varieties are considered suitable for growing and for

commercial production; high yielding superior F1

hybrids are preferred. Hence, there is continuous

need to strengthen the crop improvement

programmes in tomato and ultimately developing

new varieties/hybrids satisfying to the present day

needs of farmers and consumers as well.

The information about mean performance of

genotypes is of basic importance for crop

improvement. The range of mean values could

present a rough estimate about the variation in

magnitude of variability present among the

genotypes. The characters showing wide range of

variation have more scope for improvement.

Evaluation of hybrids and its parents helps to identify best combination of parents which are resulting in

best hybrid with desirable yield attributing traits.

And it also helps us to understand the combining

ability of parents.

MATERIALS AND METHODS

The experiment was conducted at AICRP on

Vegetable Crops, Department of Vegetable Science,

Horticultural Research and Instructional Farm,

IGKV, Raipur (C.G.) during rabi season 2017-18. The experimental material (Table 1) consists of six

lines (viz., Pusa Ruby, Punjab Chhuhara, Arka Vikas,

Kashi Anupam, H–86 and H–24) and four testers

namely 2015/TOLCVRES-4, 2015/TOLCVRES-2,

2014/TOLCVRES-3, 2014/TOLCVRES-1) using

Line x Tester mating design was followed in this

study. Thus a total of 24 hybrids were synthesized by

making crosses between lines and the testers during

March – April 2017 in crossing block. The twenty

T

RESEARCH ARTICLE

322 KIRAN KUMAR, DHANANJAY SHARMA, JITENDRA SINGH AND S.S. PAIKRA

four crosses (F1’s along with their parents (six lines

and four testers) were grown in Randomized Block

Design with three replications during rabi 2017-18.

The recommended package of practices was

followed to raise a successful crop and necessary

prophylactic plant protection measures were carried

out to safeguard the crop from pests and diseases.The

observations for eighteen characters were recorded

on five plant basis in each replication. These

observations were subjected to statistical analysis.

Table 1. Details of the parents (lines and testers), F1 hybrids developed through L x T mating design used in the

study S. No. Parents Code No. Source

Lines

1 Pusa Ruby PR IARI, New Delhi

2 Punjab Chhuhara PC PAU, Ludhiana

3 Arka Vikas AV IIHR, Bengaluru

4 Kashi Anupam KA IIVR, Varanasi

5 H–86 H-86 IIVR, Varanasi

6 H–24 H-24 HAU, Hisar

Testers

1 2015/TOLCVRES-4 15/TLCV-4 AICRP on Vegetable Crops, Raipur

2 2015/TOLCVRES-2 15/TLCV-2 AICRP on Vegetable Crops, Raipur

3 2014/TOLCVRES-3 14/TLCV-1 AICRP on Vegetable Crops, Raipur

4 2014/TOLCVRES-1 14/TLCV-3 AICRP on Vegetable Crops, Raipur

List of F1 hybrids developed through Line x Tester mating design

S. No. Crosses (F1s ) Code No. S.

No.

Crosses (F1s ) Code No.

1 Pusa Ruby X 2015/TOLCVRES-4 PR X 15/TLCV-4 13 Kashi Anupam X 2015/TOLCVRES-4 KA X 15/TLCV-4

2 Pusa Ruby X 2015/TOLCVRES-2 PR X 15/TLCV-2

14 Kashi Anupam X 2015/TOLCVRES-

2

KA X 15/TLCV-2

3 Pusa Ruby X 2014/TOLCVRES-3 PR X 14/TLCV-3 15 Kashi Anupam X 2014/TOLCVRES-3 KA X 14/TLCV-3

4 Pusa Ruby X 2014/TOLCVRES-1 PR X 14/TLCV-1 16 Kashi Anupam X 2014/TOLCVRES-1 KA X 14/TLCV-1

5 Punjab Chhuhara X 2015/TOLCVRES-4 PC X 15/TLCV-

4 17

H–86 X 2015/TOLCVRES-4 H–86 X 15/TLCV-4

6 Punjab Chhuhara X 2015/TOLCVRES-2 PC X 15/TLCV-2 18 H–86 X 2015/TOLCVRES-2 H–86 X 15/TLCV-2

7 Punjab Chhuhara X 2014/TOLCVRES-3 PC X 14/TLCV-3 19 H–86 X 2014/TOLCVRES-3 H–86 X 14/TLCV-3

8 Punjab Chhuhara X 2014/TOLCVRES-1 PC X 14/TLCV-1 20 H–86 X 2014/TOLCVRES-1 H–86 X 14/TLCV-1

9 Arka Vikas X 2015/TOLCVRES-4 AV X 15/TLCV-4 21 H–24 X 2015/TOLCVRES-4 H–24 X 15/TLCV-4

10 Arka Vikas X 2015/TOLCVRES-2 AV X 15/TLCV-2 22 H–24 X 2015/TOLCVRES-2 H–24 X 15/TLCV-2

11 Arka Vikas X 2014/TOLCVRES-3 AV X 14/TLCV-3 23 H–24 X 2014/TOLCVRES-3 H–24 X 14/TLCV-3

12 Arka Vikas X 2014/TOLCVRES-1 AV X 14/TLCV-1 24 H–24 X 2014/TOLCVRES-1 H–24 X 14/TLCV-1

Table 2. Mean performance of parents (Lines and Testers) in tomato during rabi, 2017-18 Parents Characters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Lines

Pusa Ruby 26.67 11.65 78.13 10.07 5.38 4.44 27.46 71.10 1.58 3.51 4.52 77.23 4.81 4.92 4.44 19.87 3.69 295.98

Punjab Chhuhara 28.67 11.19 61.09 8.39 5.04 4.24 26.16 73.92 1.11 4.46 4.04 40.73 2.47 5.58 4.47 22.15 3.63 313.53

Arka Vikash 27.67 10.85 85.70 10.99 4.51 3.91 31.06 71.99 1.45 3.92 3.84 60.86 4.12 4.78 3.60 21.56 4.23 454.26

Kashi Anupam 27.67 10.23 56.63 8.65 5.04 4.18 19.97 70.99 1.68 5.58 6.05 81.46 5.11 4.94 3.79 21.25 5.03 406.46

H-86 29.00 8.66 48.65 10.01 5.11 3.98 29.99 70.99 3.78 6.14 5.98 107.06 3.27 5.38 3.78 20.76 6.21 659.72

H-24 29.33 9.69 56.27 9.38 5.71 4.38 28.58 73.05 1.57 3.97 5.66 69.39 3.84 4.26 3.01 19.96 5.00 381.41

Mean of lines 28.17 10.38 64.41 9.58 5.13 4.19 27.20 72.01 1.86 4.60 5.01 72.79 3.94 4.98 3.85 20.92 4.63 418.56

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 323

Testers

2015/TOLCVRES-4 30.67 8.57 39.14 8.63 5.31 4.64 26.11 72.66 2.68 6.17 6.12 97.79 3.81 5.31 3.97 22.64 3.65 524.07

2015/TOLCVRES-2 28.67 10.95 56.22 11.32 5.11 4.58 25.16 71.69 2.67 4.72 6.44 107.06 5.88 5.12 3.83 18.98 3.48 567.40

2014/TOLCVRES-3 28.33 10.16 66.60 9.43 6.38 4.84 26.86 71.75 2.64 5.87 6.26 96.78 4.02 6.18 4.49 24.31 4.28 611.04

2014/TOLCVRES-1 31.33 11.75 57.58 11.43 5.64 4.78 29.11 72.11 1.82 4.93 5.37 66.23 4.95 4.10 3.89 23.64 4.33 440.40

Mean of testers 29.75 10.36 54.88 10.20 5.61 4.71 26.81 72.05 2.45 5.42 6.05 91.97 4.67 5.18 4.05 22.39 3.93 535.73

Mean of parents 28.80 10.37 60.60 9.83 5.32 4.40 27.04 72.02 2.10 4.93 5.43 80.46 4.23 5.06 3.93 21.51 4.35 465.43

CD at 5% 1.40 1.28 6.10 0.95 0.51 0.42 2.54 - 0.19 0.48 0.54 8.17 0.44 0.49 0.38 2.07 0.41 45.88

C.V. 2.81 7.14 5.82 5.62 5.60 5.60 5.43 1.93 5.40 5.72 5.78 5.87 6.10 5.66 5.67 5.59 5.55 5.70

1. Days to 50% flowering 2. No. of branches per plant 3. Plant height (cm)

4. Number of fruit cluster per plant 5. Number of flowers per cluster 6. Number of fruits per cluster

7. Number of fruits per plant 8. Days to first fruit harvest 9. Fruit yield per plant (kg)

10. Fruit length (cm) 11. Fruit diameter (cm) 12. Average fruit weight (g)

13. Number of locules per fruit 14. Pericarp thickness (mm) 15. Total soluble solids (ºBrix)

16. Ascorbic acid content (mg/100g) 17. Dry matter % of fruit 18. Fruit yield per hectare (q)

Table 3. Mean performance of F1 hybrids of tomato during rabi, 2017-18

Hybrids Characters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

PR X 15/TLCV-4 27.33 11.28 53.73 11.47 6.52 4.92 27.84 70.76 2.36 4.84 5.57 83.31 2.69 6.45 4.333 24.34 5.28 486.30

PR X 15/TLCV-2 29.68 8.32 49.40 7.64 5.72 4.32 33.15 73.26 1.72 4.25 4.85 68.33 3.56 4.92 5.64 20.30 4.33 331.15

PR X 14/TLCV-3 27.00 12.62 54.07 12.42 6.92 5.32 32.40 69.35 3.12 4.89 5.96 101.03 4.02 6.49 4.74 25.01 4.48 671.35

PR X 14/TLCV-1 31.00 11.62 54.43 9.80 6.12 5.32 25.15 72.60 2.21 4.27 5.47 75.52 4.69 6.18 4.34 19.32 4.83 449.94

PC X 15/TLCV-4 30.33 8.95 49.40 9.13 6.92 5.52 27.97 71.0 1.99 4.77 5.39 84.29 3.35 6.31 3.72 20.10 5.08 398.22

PC X 15/TLCV-2 29.33 10.38 52.40 10.13 7.12 6.32 28.87 71.39 2.54 4.58 5.85 96.53 3.68 4.63 4.49 17.47 4.91 531.55

PC X 14/TLCV-3 27.33 9.27 61.47 8.80 5.72 5.12 33.01 71.93 1.67 3.98 4.37 59.11 4.07 4.57 3.79 21.34 5.01 319.03

PC X 14/TLCV-1 29.00 9.95 51.40 9.13 5.92 4.52 28.82 73.51 2.48 4.86 5.39 98.33 4.69 5.81 3.22 19.47 4.93 516.20

AV X 15/TLCV-4 29.33 9.62 55.40 9.80 5.72 5.32 30.48 74.55 2.55 4.98 5.62 92.06 4.23 6.66 4.34 21.34 4.36 533.17

AV X 15/TLCV-2 27.33 10.62 56.33 9.64 6.12 5.12 27.21 71.77 2.22 4.61 5.84 93.74 3.34 5.59 4.87 21.46 4.83 453.98

AV X 14/TLCV-3 30.67 10.62 58.73 9.52 6.52 6.12 27.35 70.45 2.59 5.12 5.94 101.47 3.32 6.62 4.20 19.63 3.74 542.87

AV X 14/TLCV-1 31.00 10.28 57.40 10.14 5.92 4.72 34.74 72.54 1.55 6.38 5.15 69.96 4.34 5.63 4.06 19.88 4.28 289.94

KA X 15/TLCV-4 30.00 11.36 50.73 11.80 6.12 5.52 27.82 73.81 2.38 5.06 5.92 103.93 5.24 5.49 4.15 20.95 5.08 492.77

KA X 15/TLCV-2 29.67 10.95 62.40 9.80 5.92 5.32 24.83 71.45 3.43 5.41 7.00 144.50 5.02 6.81 4.78 23.46 3.68 702.31

KA X 14/TLCV-3 27.67 11.92 53.69 11.44 5.72 4.92 28.82 70.48 3.52 5.72 6.62 132.83 5.21 6.33 5.71 22.59 5.05 724.13

KA X 14/TLCV-1 31.00 7.27 63.10 7.68 4.32 3.72 33.92 75.22 1.31 4.23 4.70 56.57 3.34 4.27 3.26 19.45 3.51 291.76

H–86 X 15/TLCV-4 27.67 9.95 54.07 8.74 6.72 5.12 27.26 72.30 3.37 5.94 6.08 131.37 4.32 4.45 4.42 23.32 4.05 705.76

H–86 X 15/TLCV-2 30.67 12.62 58.40 11.37 6.72 5.92 20.39 73.66 2.62 5.41 6.74 139.52 4.27 6.87 4.02 21.35 4.53 522.33

H–86 X 14/TLCV-3 27.33 13.95 57.72 12.32 6.32 5.72 33.62 71.84 3.46 6.24 6.04 117.94 3.42 6.68 3.99 21.47 5.00 727.58

H–86 X 14/TLCV-1 30.67 7.48 47.40 7.64 5.32 4.72 31.60 73.48 2.71 5.87 5.12 93.21 3.62 6.23 3.77 19.64 4.54 544.96

H–24 X 15/TLCV-4 29.33 10.95 58.07 10.13 6.32 5.72 25.58 72.87 1.65 5.32 5.83 91.69 3.20 6.34 4.17 19.88 4.24 374.93

H–24 X 15/TLCV-2 30.33 12.31 59.38 11.14 6.72 6.32 26.27 73.97 1.94 4.74 5.57 92.37 3.66 5.34 4.14 20.95 4.86 445.24

H–24 X 14/TLCV-3 27.67 10.28 50.73 9.47 6.32 5.32 25.36 73.22 1.49 5.34 5.46 94.50 3.34 5.41 4.20 23.46 5.11 336.96

H–24 X 14/TLCV-1 30.00 11.33 61.64 11.49 5.52 4.92 26.46 71.38 2.74 5.58 6.30 113.01 4.33 7.24 4.51 22.59 4.94 639.98

Mean of hybrids 29.22 10.62 55.36 10.03 6.14 5.25 28.70 72.37 2.40 5.10 5.70 97.30 3.96 5.89 4.29 21.16 4.61 501.35

CD at 5% 1.23 0.97 5.07 0.91 0.57 0.48 2.49 2.11 0.21 0.97 0.67 4.12 0.37 0.57 0.46 1.93 0.42 47.67

C.V. 2.57 5.58 5.55 5.54 5.62 5.63 5.27 1.77 5.52 11.53 7.22 2.57 5.67 5.91 6.51 5.55 5.54 5.76

1. Days to 50% flowering 2. No. of branches per plant 3. Plant height (cm)

4. Number of fruit cluster per plant 5. Number of flowers per cluster 6. Number of fruits per cluster

7. Number of fruits per plant 8. Days to first fruit harvest 9. Fruit yield per plant (kg)

10. Fruit length (cm) 11. Fruit diameter (cm) 12. Average fruit weight (g)

13. Number of locules per fruit 14. Pericarp thickness (mm) 15. Total soluble solids (ºBrix)

16. Ascorbic acid content (mg/100g) 17. Dry matter % of fruit 18. Fruit yield per hectare (q)

324 KIRAN KUMAR, DHANANJAY SHARMA, JITENDRA SINGH AND S.S. PAIKRA

RESULTS AND DISCUSSION

The performance of parents and F1 hybrids for yield

and yield related traits were computed and have been

given in table 2 & 3.

Mean values for days to 50 % flowering ranged between 26.67 to 31.33 days with an average value

28.80 days. Among the parents, Pusa Ruby (26.67)

and Arka Vikas & Kashi Anupam (27.67) were

recorded the minimum days 50 % flowering and

among the crosses, minimum days to 50 % flowering

was observed in PR X 14/TLCV-3 (27.00 days) PR

X 15/TLCV-4, PC X 14/TLCV-3, AV X 15/TLCV-2

& H–86 X 14/TLCV-3 (27.33 days). The number of

branches per plant in parents ranged from 8.57 (Pusa

Ruby) to 11.75 (2015/TOLCVRES-4). Among the

crosses, it ranged from 7.27 (KA X 14/TLCV-1) to

13.95 (H–86 X 14/TLCV-3) with an overall average of 10.62. The present result getting support from the

findings of Shankar et al., (2014) and Sujeetkumar

and Ramanjinigowda (2016).

Plant height exhibited variation among 34 treatments

which ranged from 39.14cm to 85.70cm with a mean

value 57.98cm. Among the parents, maximum mean

values for plant height were recorded in Arka Vikas

(85.70cm) and Pusa Ruby (78.13cm) whereas,

among 24 F1s, KA X 14/TLCV-1 (63.10 cm), KA X

15/TLCV-2 (62.40cm) and H–24 X 14/TLCV-1

(61.64 cm) have maximum values for plant height. Results are confirmed with earlier reports of

Ravindra Kumar et al., (2012) and Sunil et al.,

(2013). The mean values of parents for number of

fruit cluster per plant varied from 8.39 (Punjab

Chhuhara) to 11.43 (2014/TOLCVRES-1) with a

grand mean of 9.83. Among hybrids, this character

was ranged from 4.32 (KA X 14/TLCV-1) to 7.12

(PC X 15/TLCV-2) with an overall average of 6.14. .

Maximum mean number of flowers per cluster

among crosses was noted in PC X 15/TLCV-2

(7.12), which is followed by PR X 14/TLCV-3 & PC

X 15/TLCV-4 (6.92). Among the parents, number of flowers per cluster

ranged from 4.51 (Arka Vikas) to 6.38

(2014/TOLCVRES-3). Among the hybrids number

of flowers per cluster were ranged from 4.32 (KA X

14/TLCV-1) to 7.12 (PC X 15/TLCV-2) with an

overall average of 6.14. The results are in close

conformity with the findings of Shankar et al.,

(2014) and Vilas et al., (2015). Among the parents,

number of fruits per cluster ranged from 3.91 (Arka

Vikas) to 4.84 (2014/TOLCVRES-3) with parental

average of 4.40. Among the F1s, maximum values for number of fruits per cluster were recorded in PC X

15/TLCV-2 & H–24 X 15/TLCV-2 (6.32) followed

by AV X 14/TLCV-3 (6.12) and H–86 X 15/TLCV-2

(5.92). The trait number of fruits per plant is very

important as it plays an important role in deciding the

yield. The maximum number of fruits per plant

among parents were recorded in Arka Vikas (31.06)

followed by H-86 (29.99). Among hybrids maximum

number of fruits per plant was observed for AV X

14/TLCV-1 (34.74) which is followed by KA X

14/TLCV-1 (33.92), H–86 X 14/TLCV-3 (33.62) and

PR X 15/TLCV-2 (33.15).

Mean values for days to first fruit harvest in parent

ranged from 70.99 (Kashi Anupam & H-86) to 73.93 (Punjab Chhuhara) days with a parental mean of

72.02. Among the hybrids, minimum days to first

fruit harvest were recorded in PR X 14/TLCV-3

(69.35 days) which was followed by AV X

14/TLCV-3 (70.45 days), KA X 14/TLCV-3 (70.48

days) and PR X 15/TLCV-4 (70.76 days). Mean

values for fruit yield per plant (kg) was ranged

between 1.11 to 3.78 kg and the average value was

2.25kg. Among the parents, maximum values for the

same trait were observed in H-86 (3.78 kg) and

2015/TOLCVRES-4 (2.68kg) whereas, among the 24

cross combinations, KA X 14/TLCV-3 (3.52kg) followed by H–86 X 14/TLCV-3 (3.46 kg) and KA

X 15/TLCV-2 (3.43 kg) showed maximum values for

fruit yield per plant. Same finding for fruit yield per

plant was also reported by Sunil et al., (2013) and

Kumar et al., (2016).

Fruit length (cm) varied from 3.51(Pusa Ruby) to

6.17 cm (2015/TOLCVRES-4) with an overall mean

of 4.93 cm in parents. Although among the 24 cross

combinations, maximum values for fruit length were

recorded in AV X 14/TLCV-1 (6.38 cm) followed by

H–86 X 14/TLCV-3 (6.24 cm) and H–86 X 15/TLCV-4 (5.94 cm). The results are in close

conformity with the findings of Gul et al., (2010) and

Sunil et al., (2013). Among the parents, maximum

values for fruit diameter were recorded in

2015/TOLCVRES-2 (6.44cm), 2014/TOLCVRES-3

(6.26cm) and 2015/TOLCVRES-4 (6.12cm). Among

the crosses, this trait varied from 4.37cm to 7.00 cm

with overall mean 5.70 cm. Maximum fruit diameter

was observed in crosses KA X 15/TLCV-2 (7.00

cm), which was followed by H–86 X 15/TLCV-2

(6.74 cm) and KA X 14/TLCV-3 (6.62 cm). Average

fruit weight contributes to total fruit yield as well as consumer preference for specific fruit size is

considered as one of the major objectives of breeding

programs in tomato. The maximum average fruit

weight was recorded among parents in H-86 &

2015/TOLCVRES-2 (107.06g) and

2015/TOLCVRES-4 (97.79g). Among the crosses,

maximum average fruit weight was recorded in KA

X 15/TLCV-2 (144.50 g) which was followed by H–

86 X 15/TLCV-2 (139.52 g), KA X 14/TLCV-3

(132.83g) and H–86 X 15/TLCV-4 (131.37g) with an

overall cross mean of 97.30 g. The earlier reports also suggested an increase in average fruit weight of

tomato hybrids Padmini and Vadivel (1997) Singh et

al., (2012) and Chauhan et al., (2014).

Among all the parents, number of locules per fruit

ranged from 2.47 (Punjab Chhuhara) to 5.88

(2015/TOLCVRES-2) with an overall parental mean

of 4.23. Among 24 crosses this trait ranged from 2.69

to 5.24 with overall mean 3.96. Highest mean value

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(5) 325

for number of locules per fruit was recorded in

crosses KA X 15/TLCV-4 (5.24) which was

followed by KA X 14/TLCV-3 (5.21) and KA X

15/TLCV-2 (5.02). Pericarp thickness of fruits

ranges from 4.10 (2014/TOLCVRES-1) to 6.18 mm

(2014/TOLCVRES-3) with an overall parental mean of 5.06 mm. The cross performance ranged from 4.27

(KA X 14/TLCV-1) to 7.24 mm (H–24 X 14/TLCV-

1) followed by H–86 X 15/TLCV-2 (6.87 mm), KA

X 15/TLCV-2 (6.81mm) and H–86 X 14/TLCV-3

(6.68 mm) with an overall mean 5.89 mm.

High total soluble solids (TSS) and low acidity are

the major factors well thought-out for manufacture of

processed products. Among the parents, highest TSS

was recorded in 2014/TOLCVRES-3 (4.49°Brix),

Punjab Chhuhara (4.47°Brix) and Pusa Ruby

(4.44°Brix). Among the crosses, this trait ranged

from 3.22 (PC X 14/TLCV-1) to 5.71 ºBrix (KA X 14/TLCV-3) which is followed by PR X 15/TLCV-2

(5.64 ºBrix), AV X 15/TLCV-2 (4.87 ºBrix), KA X

15/TLCV-2 (4.78 ºBrix) and PR X 14/TLCV-3 (4.74

ºBrix) with an overall cross mean of 4.29 ºBrix.

Present findings are in accordance with the reports of

Shankar et al., (2014) and Basavaraj et al., (2016).

Ascorbic acid content is nutritionally an important

constituent. Small fruited genotypes are generally

richer in ascorbic acid content. Among all the

parents, ascorbic acid content ranged from 18.98 to

24.31 mg/100g with an overall parental average of 21.51 mg/100g. Maximum content was recorded by

2014/TOLCVRES-3 (24.31 mg/100g) and Punjab

Chhuhara (22.15 mg/100g). Among hybrids, this

character was varied from 25.01 mg/100g (PR X

14/TLCV-3), which is followed by PR X 15/TLCV-4

(24.34 mg/100g) and KA X 15/TLCV-2 (23.46

mg/100g) with an overall average of 21.16 mg/100g.

Among all the parents, dry matter % of fruit ranged

from 3.48 to 6.21% with an overall parental average

of 4.35%. The highest dry matter % of fruit was

recorded by H-86 (6.21%), Kashi Anupam (5.03%)

and H-24 (5.00%). Among the crosses, dry matter % of fruit ranged from 3.51% (KA X 14/TLCV-1) to

5.28 % (PR X 15/TLCV-4) with overall mean 4.61

%. Maximum dry matter % of fruit was recorded in

crosses PR X 15/TLCV-4 (5.28%), which was

followed by H–24 X 14/TLCV-3 (5.11%).

Mean values for fruit yield per hectare ranged from

295.98 to 659.72q with an overall parental average of

465.43q. The highest mean value for fruit yield per

hectare H-86 (659.72 q), 2014/TOLCVRES-3

(611.04q). Among the crosses this trait ranged from

289.94 to 727.58 q with an overall mean 501.35 q. Maximum fruit yield per hectare was observed in the

cross H–86 X 14/TLCV-3 (727.58 q), followed by

KA X 14/TLCV-3 (724.13 q), H–86 X 15/TLCV-4

(705.76 q), KA X 15/TLCV-2 (702.31 q) and PR X

14/TLCV-3 (671.35 q). From the present findings, it

can be summarized that based on mean worth, top

two parents H-86 and 2014/TOLCVRES-3 and top

five crosses for fruit yield and other traits were H–86

X 14/TLCV-3, KA X 14/TLCV-3, H–86 X

15/TLCV-4, KA X 15/TLCV-2 and PR X 14/TLCV-

3. Hence, these should be utilized for future breeding

programmes for desirable trait improvement.

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