anatomical study of sansevieria zeylanica leaf affected by vehicular emissions

ANATOMICAL STUDY OF Sansevieria zeylanica LEAVES

AFFECTED BY VEHICULAR EMISSIONS

by

Parangat, John Kelly R.

Bayona, Gem L.

Misola, Charisse M.

Bacunot, Lowie S.

Antonio, Nathaniel D.

A special problem submitted to

Prof. Liezel M. Magtoto

Department of Biology

College of Science

University of the Philippines Baguio

In partial fulfilment of the requirements of the course

in Plant Anatomy

September 14, 2012

ABSTRACT

This study deals with the effect of air pollution on different plant structures on the

responses of Sansevieria zeylanica to vehicular emissions in three selected sites in Baguio City:

UP Drive, UP Campus, and Botanical Garden Nursery whose intensities of vehicular emissions

were evaluated by monitoring the vehicular volume along these sites over a 24-hour period.

Since only UP Drive is the site where vehicles can pass through, a qualitative comparison is

made ranging from light, moderate and heavy. The vehicular volume for UP Drive is 48,063.

The responses of S. zeylanica to vehicular emissions were determined using the plant

leaves‟ stomatal index and density, stomatal aperture length, guard cell size, and size of

epidermal cells. Stomatal index and Stomatal Density were calculated using a Low Power

Objective with a magnification of 100x. Stomatal Aperture, Size of Epidermal Cells and Guard

Cells were observed under a compound light microscope at High Power Objective with a

magnification of 400x.

Results showed that samples from Botanical garden have the longest stomatal aperture

among the three sites. UP drive and UP campus have aperture length with means that were

statistically equal. Botanical garden has the smallest epidermal cell area compared to the two

sites. The mean guard cell area of UP Campus was the largest and UP Drive was the smallest.

Lastly, UP Drive has the smallest stomatal index. The indexes of Botanical garden and UP

Campus were statistically equal.

It can be drawn from this study that vehicular emissions decrease the length of stomatal

aperture, increase epidermal cell size, decrease guard cell area and stomatal index. Results were

analyzed using One-way ANOVA, further supported by SNK, Dunkan Test and Pearson‟s

Correlation test.

INTRODUCTION

In today‟s growing economy, there is a great increase in pollution as the population also

increases. One of the major environmental threats that our country is facing today is vehicular

emissions. Vehicular emission remains a threat to environmental problem which is expected to

increase as the vehicle ownership increases in the country. In response to this problem, there has

been attention drawn to the effect of these vehicular emissions to the growth of the plants. There

is a growing concern that vehicular emissions generally affect the gas exchange in plants.

In this study, the leaves of Sansevieria zeylanica were examined. A leaf epidermis is

composed of compactly arranged cells, cuticle and stomata. The leaf may be amphistomatic,

epistomatic or most commonly, hypostomatic. The stomata are scattered in the broad dicotyledon

leaves while they occur in rows parallel with the long axis of the leaf in the narrow elongated

leaves of monocots. The stomata may be located above the surface of the epidermis, on the same

level or below it.

Stomata are small apertures found in the epidermis of vascular plants, (Esau 1965)

specifically they occur on stems, leaves, flowers and fruits but not on aerial roots. They occur on

both surfaces of many leaves (amphistomatous) or on only one surface (hypostomatous or

epistomatous). Stomata are bounded by guard cells. Stomata, from the Greek word stoma which

means “mouth” provides an essential connection between the internal air spaces of plants and the

external atmosphere. These pores are associated with cuticle bordered by pairs of structurally and

physiologically specialized guard cells and adjacent epidermal cells termed subsidiary cells.

These subsidiary cells, (Jarvis and Mansfield, 1981) form the stomatal complex and facilitate gas

movement through the epidermis. In the absence of stomata, most plants will not survive the

terrestrial environment since supply of carbon dioxide will be inadequate for photosynthesis, but

at the same time the unavoidable loss of water vapor through them creates the danger of

dehydration. Therefore, according to Cowan, 1982 and Raschke, 1976 the capability of the

stomata to adjust their apertures is very important for the survival of the plants.

According to literatures, at maturity of a leaf, the number of stomata per unit leaf area

may or may not be constant. The number of stomata in a certain leaf area may be affected by

different environmental factors, one of which is pollution caused by vehicular emissions.

There are several researches and articles concerning the relationship of the stomata and

atmospheric condition. One of these was Alistair M. Hetherington & F. Ian Woodward‟s article

“The role of stomata in sensing and driving environmental change”. The art icle explains how the

stomata on the surface of the leaves and stalks regulate gases in and out of the plants body. It

also showed recent data from diverse fields that establish their central importance to plant

physiology, evolution and global ecology. According to the authors, “Stomatal morphology,

distribution and behaviour respond to a spectrum of signals, from intracellular signalling to

global climatic change. Such concerted adaptation results from a web of control systems,

reminiscent of a „scale-free‟ network, whose untangling requires integrated approaches beyond

those currently used.”

The study “Stomatal density and stomatal index as indicators of paleoatmospheric CO2

concentration” was also concerned in the inverse relationship between atmospheric CO2

concentration and stomatal density and/or stomatal index. This study was done by D.L. Royer of

the Yale University Department of Geology and Geophysics, New Haven, USA. Some excerpt of

the study‟s abstract said that:

According to Duldulao and Gomez, leaf gross morphological changes like as yellowing

and browning, deformity in shape, spotting, drying of leaf margins and less hairy features were

more experiential in plants from the more polluted site than in the control site. In the study the

stomatal size and stomatal index was considered significant in affecting interaction of plant site

and growth stage. The two factors, plant site and plant type significantly affects chlorophyll

content of the leaves. Epidermal leaf surface features, including stomates, trichomes and

chlorophyll content in plants growing along roadsides were altered due to the stresses of

vehicular exhaust emission with high traffic density in urban areas. The alterations can be

considered as pointers of environmental stresses.

The effects of pollution on plants include mottled foliage, “burning” at leaf tips or

margins, twig dieback, stunted growth, premature leaf drop, delayed maturity, abortion or early

drop of blossoms, and reduced yield or quality. In general, the visible injury to plants is of three

types: (1) collapse of leaf tissue with the development of necrotic patterns, (2) yellowing or other

color changes, and (3) alterations in growth or premature loss of foliage. Injury from air

pollution can be confused with the symptoms caused by fungi, bacteria, viruses, nematodes,

insects, nutritional deficiencies and toxicities, and the adverse effects of temperature, wind, and

water.

Plant injury caused by air pollution is most common near large cities, smelters, refineries,

electric power plants, airports, highways, incinerators, refuse dumps, pulp and paper mills, and

coal-, gas-, or petroleum-burning furnaces. Plant injury also occurs near industries that produce

brick, pottery, cement, aluminum, copper, nickel, iron or steel, zinc, acids, ceramics, glass,

phosphate fertilizers, paints and stains, rubbers, soaps and detergents, and other chemicals.

Damage in isolated areas occurs when pollutants are spread long distances by wind currents.

Factors that govern the extent of damage and the region where air pollution is a problem are

(1) type and concentration of pollutants, (2) distance from the source, (3) length of exposure, and

(4) meteorological conditions. For some pollutants, damage can occur at levels below

Environmental Protection Agency standards.

Other important factors are city size and location, land topography, soil moisture and nutrient

supply, maturity of plant tissues, time of year, and species and variety of plants. A soil moisture

deficit or extremes of temperature, humidity, and light often alter a plant‟s response to an air

pollutant.

Dr. Kent reports that nitrogen dioxide, a byproduct of combustion from car engines or open

fires, can slow the growth of plants. Fortunately, rainfall transforms nitrogen dioxide into nitric

acid, which adds nitrogen to the soil and actually benefits plants. However, carbon monoxide is

less benign. This component of car exhaust is poisonous to humans and will stunt the growth of

plants. Some evergreens will drop their leaves completely when exposed to carbon monoxide.

Plant responses to air pollution are helpful in the following ways. It establishes the early

presence of air-borne contaminants, determines the geographical distribution of the pollutants,

and helps estimates the concentration of pollutants. It also provides a passive system for

collecting pollutants for chemical analyses later and obtains direct identification of different air

pollutants on the basis of plant species and variety affected.

Sansevieria zeylanica commonly known as snake plant or bowstring hemp is a succulent

plant that can be grown in high light. This plant can tolerate low humidity, low water and

feeding. Plants often form dense clumps from a spreading rhizome or stolons.

An attempt was then made in this study to know and identify the plant structures that

may serve as an indicator of the levels of carbon dioxide and other pollutants in the atmosphere.

Attention was primarily focused on the stomata of Sansevieria zeylanica leaf. Stomata have been

shown to affect the cellular respiration of Sansevieria zeylanica.

This paper aims to (1) compare the anatomical differences of Sansevieria zeylanica

exposed to vehicular emissions with plants from the unpolluted site, (2) note the effect of air

pollutants in the anatomy of the test plant, and (3) correlate results from literatures with that of

the study.

This study is important because it is used to monitor the ability of Sansevieria zeylanica

to adapt to the environment and its capability as a bio-indicator for air pollution. The study will

significantly back up the recent studies on increasing air pollution and its anatomical effect on

plant. This information gathered can be used to monitor air quality by using anatomical structure

as the parameters of air pollution caused by vehicular emissions.

The study focuses on the microscopic epidermal effects of air pollution on different

parameters on the plant species. The microscopic epidermal parameters used are size of

epidermis, size of guard cells, stomatal aperture, stomatal size and stomatal index. The study is

limited to the effects of air pollution in just one plant species Sansevieria zeylanica. It is also

well stated in the study that only surface sections were done and no cross sections were made.

Also, the age of each plant is only assumed by measuring the height. The researchers were not

able to plant cuttings of S. zeylanica and three sites were only selected because of the limited

time.

METHODOLOGY

Study Area

Three locations were identified for the collection of the specimen in different places of

Baguio City namely University of the Philippines drive (UP Drive) at Governor Pack Road,

inside the campus of University of the Philippines Baguio beside Human Kinetics Program

(HKP) building and Botanical garden‟s nursery beside the forest located in Leonard wood road

which is the controlled variable.

The three areas are receiving different intensities of air pollutants and exhaust particles from

smoke produced by vehicles passing in the said areas. The sites will be rated in terms of the

Botanical

Garden

UP Campus

UP DRIVE

vehicular volume passing in it, the one with the greatest vehicular volume will be regarded with

high air pollutants from vehicular emissions followed by moderate and then low.

Monitoring the vehicular Flow

The density of vehicles passing through the roads of University of the Philippines‟ Drive (UP

drive) was known from a recent thesis last 2012 which was quantified by number of vehicles

passing in each sites in a 24-hour cycle (Salvador, 2011). The highly polluted site which is the

UP Drive has 48, 063 vehicles/24-hour cycle.

Test specimen

Kingdom: Plantae

Phylum: Magnoliophyta

Class: Liliopsida

Order: Asparagales

Family: Asparagaceae

Genus: Sansevieria

Species: Sansevieria zeylanica

Sansevieria zeylanica is a monocot plant, succulent herb without stem having thick

fibrous leaves transversely banded in light and dark green crossbands. Its leaves are concave in

the middle which can grow up to 60 cm. Its common names are devil‟s tongue and tiger plant

(Madulid, as cited by Lallana, 2011).

Sampling Method

Three replicates of Sansevieria zeylanica leaves ranging from 24 – 32 inches, assuming

that the plants are of similar ages were selected randomly from each site. It was immediately put

to a polyethylene bag and was returned to lab for preparing and cutting sections as soon as

possible to prevent high rate of dehydration. (Duldulao, 2008) In each plant, surface sectioning

in the Adaxial and Abaxial region of the leaf were done and 10 samples were measured in each

sections for statistical analysis. A total of 60 samples were measured in each site for more

reliable results.

Test Protocol and Parameters

Fine sections of leaves were taken from the surface and were put to clean water to

prevent dehydration. Sections were fixed with FAA, dehydrated with 40% ethanol for about 30-

60 seconds and were rinsed with 50%ethanol. Specimens were then mounted with Canada

Balsam. Prepared sections were examined under the microscope for observing its stomatal index,

guard cell area, size of stomatal aperture and size of epidermal cells. Stomatal type and

epidermal cells were also identified. The abaxial and adaxial parts of the leaf were used as a

separate component.

Stomatal Index

The stomatal index was computed using the formula

using Low Power

Objective under the magnification of 100x with an eyepiece of 10x.

Stomatal Density

As adapted from Wuytack, the stomatal density was calculated by the number of stomata

per 1mm2 under a magnification of 100x, a Low Power Objective and an eyepiece of 10x.

Guard Cells, Epidermal Size, Size of Stomatal Aperture

Other parameters such as length of stomatal aperture, area of guard cell, and epidermal

size were measured by calibrated ocular micrometer using High Power Objective with an

eyepiece of 10x.

Data Analysis

The stomatal index, stomatal density, guard cell area, size of stomatal aperture and size of

epidermal cells of leaves of Sansevieria zeylanica were compared through one-way Anova using

SPSS v. 20 further supported by SNK, Dunkan Test and Pearson‟s Correlation test.

RESULTS AND DISCUSSION

Vehicular Volume in the Three Study Sites

There were three sites where the specimens were collected--UP Drive , UP Campus and

Botanical Garden. The UP Drive was set as the polluted site and the Botanical Garden was the

non-polluted site. UP drive was one of the busiest roads in Baguio City. It was being used by

vehicles starting from motorcycles to Public Utility Vehicles like jeepneys and buses. Dark

smokes in the UP drive were always seen because the road was an inclined so the vehicles are

required to change gear and release black smokes from their engines. The UP Campus was set as

the semi-polluted site because vehicles were passing by the UP Campus but not as much as in the

UP Drive but not lesser than in the Botanical Garden. The Botanical Garden was the least

polluted in the site and it was more far from the main road. The vehicular volume was set to

heavy, medium or light. The most polluted site was set as Heavy. The intermediate site was set

as medium and the least polluted site was listed as light.

Data Analysis

The researchers used One-way Anova to analyse the Aperture length, ordinary epidermal

size (Length, width and area), Guard cell size (Length, width and area) and stomatal index that

were gathered from the specimens of the three different sites. The software IBM SPSS Statistics

version 20 was used in the analysis.

This analysis involved a sample, a sampling distribution and a population therefore

certain parametric assumptions were required to ensure the compatibility of the components.

These assumptions were: a) the data were independent from each other, b) the data were

normally distributed and c) the observations in the different groups have nearly equal variances.

The first assumption of independence was met in this study because the samples were

randomly chosen from the different sites and so were the areas of the leaf where the surface

sectioning was done. Almost all of the data gathered in the study were also qualitative and were

actual measurements of the parameters being studied. The subjects were also measured only

once.

The next assumption was that the data came from a normal population or that data were

normal. Kolmogorov-Smirnov goodness-of-fit test was used to test this assumption.

Table 1. One-Sample Kolmogorov-Smirnov Test For Normality

Parameter Significance Value

Aperture length .008

Epidermal Width .000

Epidermal Length .071

Epidermal Area .187

Guard Cell Width .000

Guard Cell Length .000

Guard Cell Area .098

Stomatal Density .792

Stomatal Index .856

If the significance value was greater than .05, the data set was normal and not normal if it

was less than 0.05. Based in table 1 above, the significance value of the guard cell area,

epidermal area, epidermal length, stomatal index and stomatal density were greater than 0.05

therefore these parameters are normal (Appendix, Table 1). The aperture length, epidermal

width, guard cell width and guard cell length are non-normal data. These parameters did not

meet the assumption of normality of Anova. However, Anova can still be used on these

observations because biological data are usually non-normal data.

The final assumption of Anova is that the data are homoscedastic. The researchers used

Leven‟s test to validate this homogeneity of the variances.

Table 2. Test of Homogeneity of Variances





Epidermal Area .660





Stomatal Index .441

If the significance value was greater than .05, the data set was not normal and normal if it

was less than 0.05. Table 2 shows that only the data on the guard cell length have equal variances

(Appendix, Table 2). All of the other parameters were not homoscedastic.

If the assumptions of Anova were not met, the level of significance of the test and the

sensitivity of the F statistic to real departures from the null hypothesis would be affected and as a

result, the results‟ validity might also be affected. Anova was still used and to ensure the

accuracy and validity of the test, the data were also analysed using the nonparametric tests

Kruskal-Wallis Analysis of Ranks and Duncan analysis.

The null hypothesis in this analysis was that the aperture length, epidermal wall width,

epidermal wall length, guard cell width, guard cell length, epidermal area, guard cell area,

stomatal density and the stomatal index of the Sansevieria zeylanica species from the three

different places with varying air conditions were equal. The alternative hypothesis was that there

were significant differences in these parameters between the specimens from the three different

sizes.

Table 3. ANOVA





Epidermal Area .001





Stomatal Index .001

Table 3 above showed the result of the analysis of variance. The significance values of

the parameters of the aperture length, epidermal width, epidermal length, epidermal area, Guard

cell width, guard cell length and guard cell of the specimens were less than 0.05(Appendix,

Table 3). This means that these parameters in the three different sites have significant difference.

The significance value of the stomatal density was greater than 0.05, therefore the plants from

the three different sites have no significant difference in their stomatal density.

Since some of the assumptions of Anova are not met, the post hoc tests Kruskal-Wallis

Analysis of Ranks and Duncan analysis were used to ensure the validity of the Anova.

STOMATAL APERTURE LENGTH

Table 4. Aperture Length

Location Mean Aperture Length (µm)

UP Drive 29.5208

UP Campus 30.3333

Botanical Garden 34.7292

The results of the data analysis showed that the aperture length of the specimens from UP

Drive and UP campus were the same and were smaller than the aperture length of the specimens

from Botanical Garden (Appendix Table 4). The Botanical garden specimens have the longest

aperture with a length of 34.72 micrometers. The aperture lengths of the specimens of UP Drive

and UP campus which were 29.52 and 30.33 micrometers have no significant difference. Thus

the level of air quality is directly proportional to the size of the stomatal aperture which is as the

level of air quality increase, the larger the stomatal aperture and as the level of air quality

decrease, the smaller the stomatal aperture is.

According to Robinson, et. al. air pollutants such as SO2 and O3 in high concentrations

can usually cause stomatal closure. At low concentration, stomatal conductance is often

increased. There are two mechanisms underlying the example, the need to suppress transpiration

may take interference with stomatal control have recently been precedence over the intake of

CO2 for photosynthesis identified, one involving O3 and the other CO2.

The study of Omasa and Oneo shows that stomatal aperture has a significant difference

when air pollutants is present. The stomatal aperture is inversely proportional to the level of air

pollutants which is as stomatal aperture decreases as the level of air pollutants increases. Their

study focused on the digital image processing technique of capturing images of the stomata as it

is adapting to the artificial environment that was created by the researchers.

In the second half of their study, Omasa and Oneo examined the responses to SO2 of

neighboring stomata in a small leaf region of an intact growing plant. These stomata showed

almost uniform and constant k, until about 20 min after the start of the exposure, and then a wide

variety of stomatal movements began; the largest value in k, was about twice as large as the

smallest value at 45 min and became about three times as large at 90 min. Water-soaking and

wilting began to appear in the subsidiary cells at about 55 min, when k, was a local maximum

value, and then all the stomata began to close. This phenomenon was assumed to be caused by

increased water loss from the subsidiary cell due to SO2, which affects the membrane and

osmotic pressure, with a difference resulting in the turgor between the guard cell and the

subsidiary cell (Heath, 1980 as cited by Omasa and Oneo).

EPIDERMAL SIZE AND AREA

Table 5. Epidermal Width

Location Mean Epidermal Width (µm)


UP Campus 19.1667

UP Drive 20.7083

The result of SNK analysis showed that the plant from UP drive has the widest epidermal

width which has a width of 20.71 micrometers (Appendix, Table 5). It also showed that the

epidermal width of the specimens from Botanical garden and UP campus were 18.50

micrometers and 19.167 micrometers respectively. The Duncan analysis also showed the same

result, that the epidermal width of specimens from Botanical garden and UP campus are the same

and are smaller than the Epidermal width of specimens from UP drive.

Table 6. Epidermal Length

Location Mean Epidermal Length (µm)


UP Drive 71.3333

UP Campus 80.5833

The Epidermal cells of the Sansevieria specimens fom UP campus have the longest

epidermal with a mean size of 80.58 micrometers based on the SNK test. Duncan analysis has

the same result with SNK, which was, the epidermal of the specimens from Botanical garden and

UP Drive which have lengths of 67.63 µm and 71.33 µm respectively, were equal but were

shorter compared to the epidermal length of specimens from UP campus (Appendix, Table 6).

Table 7. Epidermal Area

Location Epidermal Area (µm)2


UP Drive 1480.7292

UP Campus 1540.9375

Both of the SNK and Duncan test showed that the specimens from UP campus have the

highest epidermal area while those from Botanical garden have the lowest epidermal area. The

area of the specimens from UP, UP drive and Botanical garden were 1540.94 µm2, 1480.73 µm

2

and 1269.06 µm2 respectively (Appendix, Table 7).

The epidermic cells generally have a decreased size in the leaves exposed to the

pollutants(GOSTON,2009). In the paper of Meerabai, the pigeon pea plants growing in the

vicinity of a silicon industry decreased in size, Average size of the epidermal cell decreases as

pollutants increases. Various authors underlined the reduction of plant growth, as a consequence

of pollution stress (Gupta and Iqba, 2005; Maruthi Sridhar et al., 2005, 2007; Gostin, 2009).

In this paper, plants from UP Campus and UP – Drive have almost the same epidermal

area size, 1540.94 µm2And 1480.73 µm

2 respectively, while replicates from Botanical Nursery

have an epidermal are size (are) of 1269.06 µm2.

GUARD CELL SIZE AND AREA

Table 8. Guard Cell width

Location Guard Cell Width (µm)

UP Drive 8.5000


UP Campus 11.3542

The SNK and Duncan analysis showed the same result in the guard cell width of the three

different sites (Appendix, Table 8). UP and botanical garden specimens have widest guard cells

with sizes of 11.35 µm and 11.14 µm respectively. The table also showed that the UP Drive

specimens have the smallest width of 8.5 µm.

Table 9. Guard Cell Length

Location Guard Cell Length (µm)


UP Campus 39.3583

UP Drive 40.3958

Both of the non-parametric analysis showed that the specimens from Botanical garden

have the shortest epidermal cell (Appendix, Table 9). The guard cell length from the site was

37.17 µm. The specimens from UP drive and UP campus have no significant difference in their

guard cell length but are longer than the Botanical Garden specimens.

Table 10. Guard Cell Area

Location Guard Cell Area (µm)2

UP Drive 343.4896


UP Campus 447.7135

The post hoc tests showed the same results in the Guard Cell Area (Appendix, Table 10).

Table 10 above showed that the guard cells from UP drive have the smallest area of 343.49 µm2

while the specimens from UP campus have the highest guard cell area of 447.71 µm2. In other

words, the guard cell area from UP Drive is lower than the specimens from botanical and the

guard cell area of Sansevieria from botanical garden is lower than the area from UP campus.

Being one a highly populated and industrialized area in the country, City of Baguio has a

serious problem on air pollution. Since air pollution is one of the major problem in many heavily

populated and industrialized countries (Kambezidis et al. 1996). Vehicular emissions, one cause

of air pollution have direct or indirect effect on the metabolism of the roadside plants( Viskari et

al., 2000). Opening of stomata ideally achieves an acceptable compromise between the plant‟s

need to acquire carbon dioxide from the atmosphere for photosynthesis and water loss by

transpiration (Harrison, 2001).

Based on the results of the statistical tests done, the guard cell areas from the three

different site: Boatanical garden, UP campus and UP drive have a significant differences. Carbon

monoxide, oxides of nitrogen and sulfur, different particulate matters, lead and other substances

are the different pollutants that are released to the atmosphere as a result of incomplete

combustion in the automobile engines. Along with the study, the effect of these emissions on the

length and width of the guard cells were studied.

In the previous studies, it was shown that the guard cell size is generally affected by

pollutants. In correlation with the past study of Irina Neta Gostin about air pollution effects to

some Fabaceae species, plants exposed to vehicular emissions tend to have a smaller guard cell

size. As for the result of the study, Specimens from UP drive being the most polluted site among

the three experimental site, have the smallest size. While specimens collected from the botanical

garden (control variable) has the largest stomatal guard cell size.

STOMATAL DENSITY

Table 11. Stomatal Density

Location Stomatal Density

UP Drive 10.1667


UP Campus 13.5000

The results of the post hoc analysis on the stomatal density are the same with the Anova

(Appendix, Table 11). There was no significant difference between the stomatal densities of the

leaves from the three different sites. The Duncan analysis however showed a different analysis.

According to the Duncan test, there was a difference in the stomatal density of the specimens

from Botanical garden and from UP campus

When plants are exposed to air pollutants, a physiological and anatomical change takes

place and may exhibit visible damage to its part. As plants are immobile and more sensitive in

terms of physiological reaction to the most prevalent air pollutants than humans and animals,

they better reflect local conditions (Nali and Lorenzini 2007). For these reasons, plants are the

most common used bio-indicators in air quality biomonitoring studies. As cited in Wuytack,

more specifically, its morphological and anatomical parameters are used, such as specific leaf

area and stomatal density which have been proven to be useful as indicators of air quality

(Balasooriya et al.,2009)

Grasses typically have lower stomatal densities than deciduous trees. The size and shape

of stomata also vary with different plant species and environmental conditions. For example,

grasses have guard cells that resemble slender dumbbells whereas trees and shrubs have guard

cells that resemble kidney beans. (Swarthout, 2010). Results show that a low mean of

11.72222222 is found in the species of Sansevieria considering the three sites.

To optimize stomatal closure efficiency, stomatal density increases and stomatal pore

surface decreases due to increasing levels of air pollution. (Balasooriya et al. 2009; Elagoz et al.

2006; Verma and Singh 2006)

http://www.eoearth.org/profile/Debbie.swarthout

While studying the stomatal density (Wuytack, 2010), their results showed that the

stomatal density in Antwerp city, the highly polluted area was higher than in Zoersel, the less

polluted area. Their study confirmed that stomatal density increases due to increasing levels of

air pollution.

The exchange of CO2 and water vapour between leaf and atmosphere is principally

controlled by stomatal density and their mean aperture. (Lake and Woodward 200) stomatal

densities change cin responae to changing atmospheric levels of co2 and pollutants. Places with

high amounts of atmospheric pollutants tend to have increased number of leaf stomata, while

lower amounts of atmospheric pollutants promotes a decreased number of stomata.(Kouwenberg

et al,2003)

The modification of the frequency and sizes of stomata as a response to the

environmental stress is an important manner of controlling the absorption of pollutants by

plants(Gostin,2009). Stomatal characteristics are often used for bio monitoring of air quality and

the majority of the results on the response of the stomatal characteristics to air pollution are

unanimous (Balasooriya et al, 2009) to optimize stomatal closure efficiency, stomatal density

increases and stomatal pore surface decreases due to increasing levels of air pollution. This

adaptation could decrease the amount of poisonous gases getting into leaf tissues and thus protect

the plant against pollution.

In this experiment, the plants from the UP Campus have the highest stomatal density of

13.5 while plants from the UP Drive have the lowest value with a mean of 10.16666667. This

doesn‟t parallel most related literatures. However, the increase of SI is not a common feature of

plant species exposed to air pollution. Verma et al. (2006) find a significant decrease of stomatal

density and stomatal index in Ipomea pes-tigridis grown under various degrees of environmental

stresses (coal-smoke pollutants).

A reduction of stomata is also found in response to elevated CO2 concentrations,

frequently present in city centres (Williams et al. 1986). The reduction in stomatal densities and

their pore size may be important for controlling absorption of pollutants (Verma et al. 2006), but

will limit photosynthesis at the same time.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2929435/#CR32

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2929435/#CR28

STOMATAL INDEX

Table 12. Stomatal Index

Location Stomatal Index

UP Drive .6983333


UP Campus 1.3155500

The two non-parametric showed the same result on the specimens‟ stomatal index

(Appendix 12). The specimens from UP campus and botanical garden have the same stomatal

index. Their stomatal indexes were higher compared to the stomatal index of the specimens from

UP drive.

Nowadays, there have been observed increased in number of industries and automobile

vehicles which continuously add toxic gases and other substances to the environment. These

toxic or pollutants have long term effects on plants by influencing CO2 contents, light intensity,

temperature and precipitation. (Jahan, 1992)

As seen in Table 12 of appendix, UP campus and botanical garden have the higher mean

of stomatal index than stomatal index of the specimens from UP Drive. It also showed that there

is a significant difference between the stomatal index of leaves from UP Drive and stomatal

indices of leaves from UP Campus and botanical garden. Also, implicitly stated, stomatal index

was inversely proportional to the site with high pollution. This suggests that pollution might have

cause a decrease in stomatal index of the plant because it might have damage the stomata and

leaf epidermal cells (Salvador, 2011).

The shift in the stomatal index can be attributed to high amounts of carbon dioxide and

sulfur dioxide emitted by automobiles. (Tanner et al., as cited by Salvador, 2011) Also, long term

exposure to elevated sulfur dioxide levels triggers a phenotypic response of reduced number of

stomata compared to the number of epidermal cells in order to minimize the inhibiting effects of

SO2 on photosynthesis. The presence of particles which was brought from pollution in the

stomata can be seen caused by increase in temperature of foliage (Rai and Kuretshtha as cited by

Salvador, 2011).

Correlations

Pearson‟s Correlation Analysis has shown that the stomatal index was positively

correlated with the aperture length and guard cell area (see Appendix, Table 13). Moreover, the

stomatal index and stomatal density were significantly correlated with each other.

CONCLUSION

The study was done to compare the effects of air pollution in the stomatal aperture length,

epidermal size (length, width and area), guard cell size (length, width and area), stomatal index

and stomatal density of the Sansevieria zeylanica in three different locations with varying air

conditions. These parameters vary in the different sites of the study. Botanical garden was the

least air-polluted site, UP campus was the moderately polluted site and UP Drive was the most

polluted site.

The results revealed that Botanical garden has the longest stomatal aperture among the

three sites. UP drive and UP campus have aperture length with means that were statistically

equal. Botanical garden has also the smallest epidermal wall area compared to the two sites. UP

campus and UP drive have their epidermal wall areas statistically equal. The mean guard cell

area of UP Campus was the largest and UP Drive was the smallest. Lastly, UP Drive has the

smallest stomatal index. The indexes of Botanical garden and UP Campus were statistically

equal.

Objectives were met. It can be drawn from this study that vehicular emissions decrease

the length of stomatal aperture, increase epidermal cell size, decrease guard cell area and

stomatal index. Results were analyzed using One-way ANOVA, further supported by SNK,

Dunkan Test and Pearson‟s Correlation test.

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APPENDIX

DATA ANALYSIS

Table 1. One-Sample Kolmogorov-Smirnov Test

Apertu

reLeng

th

Epider

malWid

th

Epider

malLen

gth

Epider

malAr

ea

Guard

Cellwi

dth

GuardC

ellLengt

h

Guard

CellAr

ea

Stomat

alDensi

ty

Stoma

talInde

x

N 180 180 180 180 180 180 180 18 18

Norm

al

Para

meter

sa,b

Mea

n

31.527

8

19.458

3 73.1806

1430.2

431

10.333

3 38.9736

401.85

07

11.722

2

1.0901

833

Std.

Dev

iatio

n

3.7571

1

3.7022

1

15.6110

0

425.83

264

2.0494

9 3.46959

84.635

67

2.6302

7

.36551

610

Most

Extre

me

Differ

ences

Abs

olut

e

.125 .218 .096 .081 .152 .155 .091 .153 .143

Posi

tive .125 .218 .081 .081 .133 .099 .091 .133 .135

Neg

ativ

e

-.119 -.126 -.096 -.043 -.152 -.155 -.074 -.153 -.143

Kolmogoro

v-Smirnov

Z

1.671 2.928 1.293 1.089 2.040 2.082 1.227 .650 .606

Asymp.

Sig. (2-

tailed)

.008 .000 .071 .187 .000 .000 .098 .792 .856

a. Test distribution is Normal.

b. Calculated from data.

Table 2. Test of Homogeneity of Variances

Levene Statistic df1 df2 Sig.

ApertureLength 2.516 2 177 .084

EpidermalWidth .534 2 177 .587

EpidermalLength 1.912 2 177 .151

EpidermalArea .416 2 177 .660

GuardCellwidth 2.752 2 177 .067

GuardCellLength 10.190 2 177 .000

GuardCellArea 1.443 2 177 .239

StomatalDensity .212 2 15 .811

StomatalIndex .865 2 15 .441

Table 3. ANOVA

Sum of

Squares

df Mean

Square

F Sig.

ApertureLength

Between

Groups 942.205 2 471.102 52.624 .000

Within Groups 1584.531 177 8.952

Total 2526.736 179

EpidermalWidth

Between

Groups 153.958 2 76.979 5.925 .003

Within Groups 2299.479 177 12.991

Total 2453.437 179

EpidermalLength

Between

Groups 5344.653 2 2672.326 12.357 .000

Within Groups 38278.229 177 216.261

Total 43622.882 179

EpidermalArea

Between

Groups 2446876.736 2 1223438.368 7.215 .001

Within Groups 30011807.943 177 169558.237

Total 32458684.679 179

GuardCellwidth

Between

Groups 303.802 2 151.901 60.005 .000

Within Groups 448.073 177 2.531

Total 751.875 179

GuardCellLength

Between

Groups 326.147 2 163.073 15.784 .000

Within Groups 1828.666 177 10.331

Total 2154.812 179

GuardCellArea

Between

Groups 339937.599 2 169968.799 31.928 .000

Within Groups 942274.600 177 5323.585

Total 1282212.198 179

StomatalDensity

Between

Groups 33.778 2 16.889 3.022 .079

Within Groups 83.833 15 5.589

Total 117.611 17

StomatalIndex

Between

Groups 1.392 2 .696 11.881 .001

Within Groups .879 15 .059

Total 2.271 17

Table 4. Aperture Length

Location N Subset for alpha = 0.05

1 2

Student-Newman-Keulsa

UP Drive 60 29.5208

UP 60 30.3333

Botanical 60 34.7292

Sig. .139 1.000

Duncana

UP Drive 60 29.5208

UP 60 30.3333


Sig. .139 1.000

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 60.000.

Table 5. Epidermal Width


1 2



UP 60 19.1667

UP Drive 60 20.7083

Sig. .312 1.000

Duncana


UP 60 19.1667

UP Drive 60 20.7083

Sig. .312 1.000



Table 6. Epidermal Length


1 2



UP Drive 60 71.3333

UP 60 80.5833

Sig. .169 1.000

Duncana


UP Drive 60 71.3333

UP 60 80.5833

Sig. .169 1.000



Table 7. Epidermal Cell Area


1 2



UP Drive 60 1480.7292

UP 60 1540.9375

Sig. 1.000 .424

Duncana


UP Drive 60 1480.7292

UP 60 1540.9375

Sig. 1.000 .424



Table 8. GuardCellwidth


1 2


UP Drive 60 8.5000


UP 60 11.3542

Sig. 1.000 .474

Duncana

UP Drive 60 8.5000


UP 60 11.3542

Sig. 1.000 .474



Table 9. GuardCellLength


1 2



UP 60 39.3583

UP Drive 60 40.3958

Sig. 1.000 .079

Duncana


UP 60 39.3583

UP Drive 60 40.3958

Sig. 1.000 .079



Table 10. GuardCellArea


1 2 3


UP Drive 60 343.4896


UP 60 447.7135

Sig. 1.000 1.000 1.000

Duncana

UP Drive 60 343.4896


UP 60 447.7135

Sig. 1.000 1.000 1.000



Table 11. StomatalDensity


1 2


UP Drive 6 10.1667

Botanical 6 11.5000

UP 6 13.5000

Sig. .067

Duncana

UP Drive 6 10.1667

Botanical 6 11.5000 11.5000

UP 6 13.5000

Sig. .344 .163



Table 12. StomatalIndex


1 2


UP Drive 6 .6983333


UP 6 1.3155500

Sig. 1.000 .679

Duncana

UP Drive 6 .6983333


UP 6 1.3155500

Sig. 1.000 .679



Table 13. Correlations

ApertureLe

ngth

EpidermalWall

Area

GuardCell

Area

StomatalIn

dex

StomatalDe

nsity

ApertureLengt

h

Pearson

Correlat

ion

1 -.086 .145 .543* .290

Sig. (2-

tailed)

.249 .053 .020 .244

N 180 180 180 18 18

EpidermalWall

Area

Pearson

Correlat

ion

-.086 1 -.039 -.011 .073

Sig. (2-

tailed) .249

.603 .967 .774

N 180 180 180 18 18

GuardCellArea

Pearson

Correlat

ion

.145 -.039 1 .523* .396

Sig. (2-

tailed) .053 .603

.026 .104

N 180 180 180 18 18

StomatalIndex

Pearson

Correlat

ion

.543* -.011 .523

* 1 .798

**

Sig. (2-

tailed) .020 .967 .026

.000

N 18 18 18 18 18

StomatalDensit

y

Pearson

Correlat

ion

.290 .073 .396 .798**

1

Sig. (2-

tailed) .244 .774 .104 .000

N 18 18 18 18 18

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

COMPUTATION FOR THE CALIBRATION CONSTANT

Tabe 14. Computation of the calibration constant for LPO

Average: 1 x 10= 1 cc

Tabe 15. Computation of the calibration constant for HPO

HPO

Trial 1 Trial 2 Trial 3

Stage 5 10 15

Ocular 20 40 60

Average: .25 x 10= 2.5 cc

LPO

Trial 1 Trial 2 Trial 3

Stage 10 5 10

Ocular 10 5 10

anatomical study of sansevieria zeylanica leaf affected by vehicular emissions

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