International Research Journal of Plant Science (ISSN: 2141-5447) Vol. 2(4) pp. 099-106, April, 2011
Available online http://www.interesjournals.org/IRJPS
Copyright © 2011 International Research Journals
Full length Research Paper
Anticipated performance index of some tree species
considered for green belt development in an urban area
Dali Mondal a, Srimanta Gupta a* and Jayanta Kumar Datta a
a
Department of Environmental Science,University of Burdwan, Golapbag, Burdwan-713104, West Bengal, India
Accepted 4 April, 2011
In the present study, the Air Pollution Tolerance Index (APTI) of ten plant species collected from an
urban area has been evaluated by analyzing important biochemical parameters. High values of APTI
were recorded in Psidium guajava (31.75%); Swietenia mahoganii(28.08%); Mangifera indica (27.97%);
Polyanthia longifolia (25.58%) and Ficus benghalensis (25.02%). The Anticipated Performance Index
(API) of these plant species was also calculated by considering their APTI values together with other
socio-economic and biological parameters. According to API most tolerant plant species for green belt
development were Ficus benghalensis (87%); Mangifera indica (87%); Swietenia mahoganii (87%) and
Saraca indica (81%).
Keyword : Air Pollution Tolerance Index; API; Suitability for green belt development; Burdwan; West Bengal.
INTRODUCTION
Air pollution control is more complex than most other
environmental challenges. No physical or chemical
method is known to ameliorate aerial pollutants. A
suitable alternative may be to develop a biological
method by growing green plants in and around industrial
and urban areas ( Agarwal, 1988; Santra, 1995; Thakre,
1995; Shannigrahi et al.,2003; Sivasamy and Srinivasan,
1996; Fukuoka, 1997; Ghosh and Majee, 2001).
Plants, the main green belt (GB) component, act as a
sink and as living filters to minimize air pollution by
absorption, adsorption, detoxification, accumulation
and/or metabolization without sustaining serious foliar
damage or decline in growth, thus improving air quality by
providing oxygen to the atmosphere (Sharma et al., 1994;
Rawat and Banerjee, 1996; Beckett et al., 1998). Plants
differ markedly in their responses to pollutants, some
being highly sensitive and others hardy and tolerant
(Singh and Rao, 1983; Shannigrahi et al.,2003).
Parameters used in defining sensitivity or resistance of
plants towards different air pollutant concentrations are
ascorbic acid content (Keller and Schwager, 1977),
relative water content (RWC) (Sen and Bhandari, 1978),
*Corresponding author: Email: srimantagupta@yahoo.co.in
chlorophyll content (Bell and Mudd, 1976), and leaf
extract pH (Chaudhary and Rao, 1977). Categorization of
plants as sensitive or tolerant is determined by the level
of these parameters in plants, and thus plants show
different susceptibility to different pollutants. Sensitive
species are early indicators of pollution, and the tolerant
species help in reducing the overall pollution load (Rao,
1983). Singh and Rao (1983) have developed the Air
Pollution Tolarence Index (APTI), which is based on four
biochemical properties of leaves: ascorbic acid, total
chlorophyll, relative water content and leaf extract pH.
Plant sensitivity and tolerance to air pollutants varies with
these parameters. Chlorophyll content decreases due to
production of reactive oxygen species (ROS) in the
chloroplast under water stress (ROSs are very small
reactive molecules that can cause damage to cell
structures during environmental stress). Higher ascorbic
acid content of leaves might be an effective strategy to
protect thylakoid membranes from oxidative damage
under such water stress (Tambussi et al., 2000), as
ascorbic acid is critically involved in the defense against
ROS produced by the photosynthetic apparatus
(Smirnoff, 1996).
The present study the selection of plant species which
can be grown around industrial/urban areas in India.
Plants differ considerably with reference to their respons-
100 Int. Res. J. Plant Sci.
es towards pollutants, some being highly sensitive and
others hardy and tolerant. On the basis of the APTI and
some relevant biological and socioeconomic characters,
the anticipated performance index (API), from best to not
recommended, of various plant species was determined
for GB development.
Statistical analysis
MATERIALS AND METHODS
RESULTS AND DISCUSSION
Selection of sampling area and sampling details
The research work was mainly confined in Burdwan town, West
Bengal. As per Gupta et al., (2009) ambient air quality status of this
town i.e. the average concentration (µg/m3) of SO2, NO2 and RSPM
(Respirable Suspended Particulate Matter) are 8.59, 176.06 and
59.94 respectively. Ten plant species were selected during the
summer season of 2010 from Golapbag campus of Burdwan
University. The screening and selection of the plant species was
partly based on literature survey of similar work and guidelines of
Central Pollution Control Board (1999 - 2000). The ten plant leaf
samples were collected at the lower most position of canopy at a
height of 6-7ft from the ground surface. Samples were cleaned with
distilled water and then refrigerated (22ºC)under suitable condition
for further biochemical analysis.
Method for biochemical parameters
Various biochemical parameters such as leaf extracts pH (Sing and
Rao, 1983), relative water content (Sen and Bhandari, 1978), total
chlorophyll (Arnon, 1949), ascorbic acid (Keller and Schwager,
1977), soluble sugar (Sadasivam and Manikam, 1996) and protein
(Lowry et al., 1951) were done from the collected leaf samples.
Calculation of Air Pollution Tolerance Index (APTI) of plants
Air pollution tolerance index (APTI) was proposed by Singh and
Rao, (1983) to assess the tolerant/resistance power of plants
against air pollution. The air pollution tolerance index was
calculated using the formula:
APTI =
A (T + P ) + R
10
Where: A =Ascorbic Acid (mg/g)
T =Total Chlorophyll (mg/g -f.w)
P = pH of the leaf extract
R = Relative water content of leaf (%).
Based on the development and evaluation of APTI values among
the samples they were categorized into three groups, namely <10 is
sensitive species, >10-16 is intermediate species and >17 is
tolerant species.
Calculation of Anticipated Pollution Index (API)
By combining the resultant APTI values with some relevant
biological and socio-economic characters (plant habit, canopy
structure, type of plant, laminar structure and economic value), the
API was calculated for different species. Based on these
characters, different grades (+ or _) are allotted to plants. Different
plants are scored according to their grades. The criteria used for
calculating the API of different plant species are given in Table 1
and 2.
Linear regression analysis was performed between independent
variables viz. Chlorophyll, pH, RWC, ascorbic acid and dependent
variable such as APTI by using XL STAT (Version 10) software.
These scatter plots illustrated the degree of correlation (R2)
between the said variables.
Discussion on experimental results of biochemical
parameters
Plants have been categorized into groups according to
their degree of sensitivity toward and tolerance of various
air pollutants on the basis of experiment and available
data ( Kagamimori et al., 1978; Bhattacharya, 1983; Khan
and Abbasi, 2002). Levels of tolerance to air pollution
vary from species to species, depending on the capacity
of plants to withstand the effect of pollutants without
showing any external damage. APTI is a unique index
because it incorporates
four different biochemical
parameters: total chlorophyll, pH of leaf extract, ascorbic
acid, and relative water content. The APTI has been
determined for 10 plant species (Table 3). As shown in
Table 3, the highest mean total chlorophyll content (in
mg/g fresh wt) was recorded in Saraca indica (2.47)
followed by Psidium guajava (2.19), Fiscus religiosa
(2.17) respectively. Higher chlorophyll content in plants
might favour tolerance to pollutants (Joshi et al., 1993).
Whereas a considerable loss in total chlorophyll, in the
leaves of plants exposed air pollution stress supports the
argument that the chloroplast is the primary site of attack
by air pollutants such as SPM, SO2 and NOX (Tripathi and
Gautam,2007). Air pollutants make their entrance into the
tissues through the stomata and cause partial
denaturation of the chloroplast and decrease pigment
contents in the cells of polluted leaves (Rao and Leblanc,
1966). High amount of gaseous SO2 causes destruction
of chlorophyll and that might be due to the replacement of
2+
Mg
by two hydrogen atoms and degradation of
chlorophyll molecules to phaeophytin (Rao and Leblanc,
1966). The mean value of leaf extract pH ranged from
that of Swietenia mahoganii recorded at 5.83 to that of
Ficus benghalensis at around 6.81 (Table 3). The low pH
of the leaf extract showed a relationship with the type of
air pollution. The more acidic nature demonstrates that
the air pollutants, mostly gaseous types, namely SO2,
NOX diffuse and form acid radicals in the leaf matrix by
reacting with cellular water. This further effect the
chlorophyll molecules (Turk and Wirth, 1975). A pH on
the higher side improves tolerance against air pollution
(Agarwal, 1986). Mean values of ascorbic acid content of
ten plants are depicted in Table 3. The mean relative
water content (RWC) was lowest in Ficus hispida
(69.96%) and highest in Mangifera indica (84.66%)
(Table 3). The Relative Water Content(RWC) indicates
Mondal et al. 101
Table 1. Gradation of plant species on the basis of air pollution tolerance indexn(APTI ) and other biological and socioeconomic characters.
Pattern of assessment
Grade
allotted
12.0-16.0
+
16.1-20.0
20.1-24.0
24.1-28.0
28.1-32.0
32.1-36.0
++
+++
++++
+++++
++++++
Small
Medium
Large
+
++
Sparse/Irregular/Globular
Spreading crown/Open/Semi
dense
Spreading dense
-
++
Deciduous
Evergreen
+
Size
Small
Medium
Large
+
++
Texture
Smooth
Coriaceous
+
Hardiness
Delineate
Hardy
+
Less than three uses
Three or four uses
Five or more uses
+
++
Grading Character
(a) Tolerance
(b) Biological and
Socio-Economic
Air
Pollution
Index(APTI)
Tolerance
(i) Plant Habit
(ii)
Canopy
Structure
(iii)Type of Plant
(iv)Laminar
structure
(v)Economic
Value
+
Maximum grades that can be scored by a plant = 16
change in leaf matrix hydration condition and will
generate higher acidity condition when RWC is low. The
RWC also helps to maintain physiological balance under
stress condition higher relative water content is
advantageous for drought resistance in plants (Dedio,
1975).The highest content of ascorbic acid (in mg/gm
fresh wt) was found in Swietenia mahoganii (29.50),
followed by Psidium guajava (28.90), Polyanthia longifolia
(25.10), Mangifera indica (24.50) respectively. The lowest
mean value was recorded in Ficus hispida (8.04).
Ascorbic acid is regarded as an antioxidant. It is found in
large amounts in all growing plant parts and influences
102 Int. Res. J. Plant Sci.
Table 2. Anticipated Performance Index (API) of plant species.
Grade
0
1
2
3
4
5
6
7
Score (%)
Up to 30
31 – 40
41 – 50
51 – 60
61 – 70
71 – 80
81 – 90
91 – 100
Assessment category
Not recommended
Very poor
Poor
Moderate
Good
Very good
Excellent
Best
Table 3. Mean value of biochemical parameters along with APTI of the leaf samples. (Units are expressed
as mg/g-f.w. except pH and Relative Water Content which is expressed in units and percentage
respectively).
Sl
No
Local
Name
1
Asoke
2
Debdaru
3
Banyan
4
Dumur
5
Guava
6
Sisoo
7
Mango
8
Chattim
9
Mahagunii
10
Asattha
Scientific
Name
Saraca indica
Polyanthia
longifolia
Ficus
benghalensis
Ficus hispida
Psidium
guajava
Dalbergia
sisoo
Mangifera
indica
Alstonia
scholaris
Swietenia
mahoganii
Ficus religiosa
Chlorophyll
pH
Mean ± SD
Mean ± SD
2.47 ± 0.97
6.49 ± 0.28
0.77 ± 0.22
6.31 ± 0.27
1.17 ± 0.49
6.81 ± 0.43
1.60 ± 0.64
6.58 ± 0.62
2.19 ± 0.75
6.36 ± 0.42
1.84 ± 0.78
6.27 ± 0.60
2.13 ± 0.76
6.33 ± 0.63
1.49 ± 0.56
5.94 ± 0.69
1.52 ± 0.72
5.83 ± 0.55
2.17 ± 0.16
6.30 ± 0.18
RWC
Mean
SD
80.12
6.56
83.05
4.96
83.45
4.20
69.96
±10.60
77.69
5.98
73.91
±15.20
84.66
6.46
79.76
9.88
70.73
±14.40
73.64
3.24
±
±
±
±
Ascorbic
Acid
Sugar
Protein
APTI
Mean ± SD
Mean ± SD
Mean ± SD
Mean ± SD
32.90
4.69
25.80
1.83
19.20
10.64
21.90
6.54
36.20
15.68
38.70
5.45
58.20
8.89
18.40
6.46
43.80
8.99
26.20
3.48
23.90
3.31
25.58
6.93
25.02
7.43
13.26
3.65
31.75
5.20
21.04
4.66
27.97
6.90
16.92
3.39
28.08
5.73
15.11
2.88
18.50 ± 5.43
25.10
10.98
21.80
10.87
±
±
8.04 ± 3.19
±
28.90± 9.82
17.50 ± 7.25
±
±
24.50
11.70
±
13.20 ± 5.94
29.50 ± 8.33
±
9.06 ± 2.78
59.24
19.69
62.01
28.18
62.48
22.15
35.42
10.53
56.58
14.56
49.19
24.34
79.88
16.21
51.49
15.04
105.40
33.65
37.42
6.589
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
* Standard deviation
resistance to adverse environmental conditions, including
air pollution (Keller and Schwager, 1977; Lima et al.,
2000). Pollution load dependent increase in ascorbic
content of all the species may be due to the more rate of
production of reactive oxygen species (ROS) such as
SO3-, HSO3-, OH-, and O2- during photo-oxidation of SO3-
to SO4- where sulphites are generated from SO2
absorbed. The free radical production under SO2
exposure would increase the free radical scavengers,
such as ascorbic acid, super oxide dismutase,and
peroxidase . (Pierre and Queirz, 1981) based on dosage
and physiological status of plant. Increase level of
±
±
±
±
±
±
±
±
±
±
Mondal et al. 103
Table 4. Evaluation of plant species on the basis of their APTI value and some biological and socio-economic characters.
Assessment Parameter
Grade
Allotted
Laminar
Sl
No
Local
Name
Scientific Name
APTI
Tree
Habit
Canopy
Structure
Type
Tree
1
Asoke
Saraca indica
++++
+
++
2
Debdaru
Polyanthia longifolia
++++
+
3
Banyan
Ficus benghalensis
++++
4
Dumur
Ficus hispida
+
5
Guava
Psidium guajava
6
Sisoo
7
Mango
8
9
10
Size
Texture
Economic
Importance
Hardness
Total
Plus
%Scoring
+
++
+
+
+
13
81
6
+
+
+
+
-
+
10
62
4
++
++
+
+
+
++
+
14
87
6
+
-
-
+
+
+
-
5
31
1
++++++
+
-
-
+
+
++
+
12
75
5
Dalbergia sisoo
+++
++
+
+
-
-
+
+
9
56
3
Mangifera indica
+++++
++
+
+
+
+
++
+
14
87
6
Chattim
Alstonia scholaris
++
+
++
+
+
+
+
-
9
56
3
Mahagunii
Swietenia mahoganii
+++++
++
++
+
-
+
++
+
14
87
6
Asattha
Ficus religiosa
+
++
++
+
+
+
++
+
11
69
4
ascorbic acid may be due to the defense
mechanism of the plant. Increased levels of
ascorbic acid in leaves will increase air pollution
tolerance in plants (Chaudhury and Rao, 1977).
Soluble sugar is an important constituent and
source of energy for all living organisms. Plants
manufacture this organic substance during
photosynthesis and breakdown during respiration.
They exist as free sugar and polysaccharide.
Decrease in soluble sugar content in plants with
increased in gaseous pollutants level in industrial
regions was reported by Tzvetkova and Kolarvo
(1996). Among the studied species the mean
sugar content (mg/g-f.w.) was lowest in Ficus
hispida (35.42) and highest in Swietenia
mahoganii (105.40) (Table 3). The concentration
of soluble sugars is indicative of the physiological
activity of a plant and it determines the sensitivity
of plants to air pollution. Reduction in soluble
sugar content in industrial area can be attributed
to increased respiration and decreased
of
API
Grade
CO2 fixation because of chlorophyll deterioration.
Pollutants like SO2, NO2 and H2S under hardening
conditions can cause more depletion of soluble
sugars in leaves of plants grown in polluted area
(Davison and Barners, 1986). The reaction of
sulfite with aldehydes and ketones of
carbohydrates can also cause reduction in
carbohydrate content. Protein is one of most
essential foliar biochemical constituents of plants
and is required for enzymatic activity in plant
species. Protein content in plants exhibits both
increasing and decreasing trend in response to
pollution stress depending on the plant species
and its inherent resistance against pollution. The
mean protein content (mg/g-f.w.) was lowest in
Alstonia scholaris (18.40) and highest in
Mangifera indica (58.20) (Table 3). Reduction in
protein content might be due to the enhanced rate
of protein denaturation which is also supported by
the findings of Prasad and Inamdar (1990).
Constantinidou and Kozlowski (1979) found
enhanced protein denaturation and breakdown of
existing protein to amino acid as the main causes
of reduction in protein content.
As shown in Table 3, plant species with higher
APTI values were Psidium guajava (31.75),
Swietenia mahoganii (28.08), Mangifera indica
(27.97),
Polyanthia longifolia (25.58),Ficus
benghalensis (25.02), and Saraca indica (23.90).
Scatter Plot Interpretations
Figure 1 shows the linear regression plots
individual variables with APTI. It is observed that a
high positive correlation (p<.05 and p<.01) exists
between APTI and Relative Water Content and
APTI and ascorbic acid. It indicates that ascorbic
acid and RWC of leaf are the most significant and
determining factors on which the tolerance
depends.
104 Int. Res. J. Plant Sci.
90
35
ASCO R BIC A CID ( m g /g )
80
70
RWC(% )
60
50
y = 0.4434x + 67.661
R2 = 0.2556
40
30
20
10
0
0.000
10.000
20.000
30.000
40.000
30
25
20
15
10
y = 1.2226x - 8.5106
R2 = 0.9545
5
0
0.000
10.000
20.000
30.000
40.000
APTI
APTI
(Figure 1a)
(Figure 1b)
7
2.5
6.6
1.5
6.4
pH
Ch loroph yll (mg /g f.w.)
6.8
2
6.2
1
0.5
y = 0.0134x + 1.3586
R2 = 0.0258
y = -0.0041x + 6.4163
R2 = 0.0081
6
5.8
0
0.000
10.000
20.000
30.000
40.000
APTI
(Figure 1c)
5.6
0 .000
10.000
2 0.000
30.000
40.000
APTI
(Figure 1d)
Figure 1. Scatter plot of various biochemical parameters with APTI values.
Anticipated Performance Index (API) of plant species
in a Green Belt (GB) plantation
Plant species for plantation in industrial urban areas were
evaluated for various biological and socio-economic as
well as a few biochemical characteristics, viz. APTI, plant
habit, canopy structure, type of plant, laminar structure
and economic value. These parameters were subjected
to a grading scale to determine the anticipated
performance of plant species as advocated in reference
(Sing and Rao, 1983). The grading pattern of ten plant
species evaluated in Table 4, and which fit into the
grading pattern with respect to their anticipated
performance index (API) were recommended (Table 5)
for plantation in an industrial/urban area. A comparison of
the assessment parameters with respect to grading
characters using a multiplication or summation of the
anticipated performance of plant species found those
parameters to be quite similar. Table 5 showed that out of
10 species, Ficus benghalensis, Mangifera indica,
Swietenia mahoganii and Saraca indica were the most
tolerant plant to grow in industrial areas and can be
expected to perform well. It has a dense plant canopy of
evergreen like foliage, which may afford protection from
pollution stress. The economic and aesthetic value of this
tree is well known and it may be recommended for
extensive planting as a first curtain. Psidium guajava was
judged to be very good performers, while Polyanthia
longifolia and Ficus religiosa qualified for the good
performer category. Besides these 7 good performing
species, 3 were found to be unsuitable as a pollution sink
because of their lower anticipated performance but have
been planted in industrial areas for their aesthetic value
and other economic uses. The latter species are
attractive plants that certainly enhance the aesthetic
value of the industrial/urban areas. Thus, an evaluation of
anticipated plant performance might be very useful in the
selection of appropriate species.
Mondal et al. 105
Table 5. Anticipated Performance Index (API) of studied plant species.
Sl No
Local Name
Scientific Name
Grade
Allotted
API
Value
Total
%
Assessment
1
Banyan
Ficus benghalensis
14
87
6
Excellent
2
Mango
Mangifera indica
14
87
6
Excellent
3
Mahagunii
Swietenia mahoganii
14
87
6
Excellent
4
Asoke
Saraca indica
13
81
6
Excellent
5
Guava
Psidium guajava
12
75
5
Very Good
6
Debdaru
Polyanthia longifolia
10
62
4
Good
7
Asattha
Ficus religiosa
11
69
4
Good
8
Sisoo
Dalbergia sisoo
9
56
3
Moderate
9
Chattim
Alstonia scholaris
9
56
3
Moderate
10
Dumur
Ficus hispida
5
31
1
Very Poor
CONCLUSION
The present study reveals that evaluation of anticipated
performance of plants might be very useful in the
selection of appropriate tree species for urban green belt
development. This study indicates Ficus benghalensis,
Mangifera indica, Swietenia mahoganii and Saraca indica
are the most tolerant plant to grow in industrial areas and
can be expected to perform well for the development of
green belts.
ACKNOWLEDGEMENTS
The authors wish to thank Dr A.R.Ghosh (Associate
Professor) and Dr N.K.Mondal (Assistant Professor),
Department of Environmental Science, The University of
Burdwan, for their constant support and valuable
suggestions during the course of the investigation.
Sincere thanks are also due to all the reviewers of this
manuscript.
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