Environ Sci Pollut Res (2014) 21:13560–13571 DOI 10.1007/s11356-014-3286-9

RESEARCH ARTICLE

Screening of Bangladeshi winter wheat (Triticum aestivum L.) cultivars for sensitivity to ozone Costas J. Saitanis & Shafiqul M. Bari & Kent O. Burkey & Dimitris Stamatelopoulos & Evgenios Agathokleous

Received: 19 March 2014 / Accepted: 3 July 2014 / Published online: 16 July 2014 # Springer-Verlag Berlin Heidelberg 2014

Abstract The sensitivity to ozone of ten Bangladeshi wheat cultivars was tested by exposing plants to eight ozone exposure regimes (50, 60, 80, 100, 120, 135, 150, and 200 ppb for 14, 11, 8, 6, 5, 4, 3, and 1 days, respectively, for 8 h/day) in controlled environment chambers. Visible leaf injury, dry weight, chlorophyll, carotenoid content, leaf greenness (SPAD value), quantum yield of photosynthesis, and stomatal resistance were measured to evaluate response. Shoot biomass, total chlorophyll, leaf greenness, and carotenoid content were reduced in ozone-exposed plants. Based on the results of principal component analysis (PCA)-biplot analysis, the order of sensitivity to ozone was: Akbar>>Sufi≥Bijoy≥Shatabdi> Bari-26≥Gourab>Bari-25≥Prodip≥Sourav>>Kanchan. The most important parameters to discriminate cultivars with respect to ozone sensitivity were visible injury and chlorophyll b/a ratio, whereas quantum yield of photosynthesis was less important. Differences in stomatal resistance were not a Responsible editor: Philippe Garrigues C. J. Saitanis (*) : D. Stamatelopoulos Laboratory of Ecology and Environmental Sciences, Agricultural University of Athens, Iera Odos 75, Votanikos, 11855 Athens, Greece e-mail: [email protected] S. M. Bari Department of Agroforestry, Faculty of Agriculture, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh e-mail: [email protected] K. O. Burkey Plant Science Research Unit, USDA-ARS, Raleigh, NC, USA e-mail: [email protected] E. Agathokleous Silviculture and Forest Ecological Studies, Hokkaido University, Sapporo, Hokkaido 060-8589, Japan e-mail: [email protected]

significant factor in ozone response. Regression of cultivars’ PCA scores against year of release revealed no trend, suggesting that ozone tolerance was not incorporated during cultivar breeding. Keywords SPAD . Chlorophyll . Carotenoids . Cluster analysis . Principal component analysis . Biplot

Introduction Ambient ozone (O3) is recognized as being the most important oxidizing gaseous pollutant, and it is now well documented that it occurs at increased levels in many areas around the globe, including agricultural regions and natural remote ecosystems (Saitanis 2003; Emberson et al. 2009; Oksanen et al. 2013). Many studies have shown that ambient O3 levels are high enough to cause yield reduction in cultivated plants in many countries across the world (Fuhrer et al. 1997; Fuhrer and Booker 2003). Recently, Avnery et al. (2011) indicated that, for the year 2000, O3-induced global yield reductions ranged (depending on the metric used) from 8.5 to 14 % for soybean, 3.9 to 15 % for wheat, and 2.2 to 5.5 % for maize. Global crop production losses totaled 79–121 million metric tons, worth $11–18 billion annually (USD2000). Among the most important agricultural plants documented to be negatively affected by O3 is wheat (Triticum aestivum L.) (Velissariou et al. 1992; Fangmeier et al. 1994; Ollerenshaw and Lyons 1999; Danielsson et al. 2003; Pleijel et al. 2006; Biswas et al. 2008; Kaliakatsou et al. 2010; Pleijel 2011). O3 penetrates leaves through the stomata and causes many changes in the plant tissues (alters metabolic activity, impairs photosynthesis, causes protein and chlorophyll (chl) degradation, causes reduction in biomass production, etc.) (Goumenaki et al. 2010; Lorenzini and Saitanis 2004; Mikkelsen et al. 1995; Singh et al. 2014). Generally, it has been shown that differences in O3 sensitivity

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exist among cultivars of the same species (Saitanis and Karandinos 2002; Burkey and Carter 2009), and thus it is important for cultivators, agronomists, and plants breeders to know the relative O3 sensitivity of the available cultivars. Air pollution (including O3 and its precursors) in Bangladesh is poorly investigated, and relevant scientific papers are very limited (Azad and Kitada 1998; Salam et al. 2008; Sikder et al. 2013). O3 levels are not monitored at all in rural areas in Bangladesh; we located only one publication (Sikder et al. 2013) reporting observations of surface O3 and its precursors, in the metropolitan city of Dhaka. However, O3 precursors emissions have been increased in Asia (Ohara et al. 2007), and South Asia is expected to experience the largest, in the world, increase in surface O3 levels, by 2030 (Dentener et al. 2006). Emberson et al. (2009) estimated that, for the growing season of wheat, most of Bangladesh terrain is expected to experience O3 levels (7-h mean O3 concentration), up to 50–90 ppb, if not even higher. Such levels are considered quite high to be phytotoxic at least to sensitive wheat cultivars. Wheat (T. aestivum L.) is considered the second leading cereal crop, after rice, in Bangladesh, playing a vital role in agricultural economy of this country—which is one of the least developed agrarian nations in the world. Current requirements of wheat are estimated to be about 3.0–3.5 million tons with an increasing consumption rate of 3 %/year (Pandit et al. 2007). Wheat was not a significant food crop in Bangladesh before 1970. During the decade of 1960, only about 55,000 ha were cultivated with an average annual production of about 42,000 t and an average yield of about 0.66 t/ha (FAO 2013). Since then, new high yielding cultivars have been introduced, with a potential yield of 3.5–5.1 t/ha (Hasan 2006) (Table 1). However, an alarming gap between the potential yield and the realized yield has been noticed (Hasan 2006); according to the data of FAO (2013) over the last 8 years the realized wheat yield, in Bangladesh, is about 2.11 t/ha (Table 2), well below the average potential yield

(4.19 t/ha) of the ten Bangladeshi wheat cultivars, tested in the present study (Table 1). Akhtar et al. (2010) exposed (in growth chambers) two Bangladeshi wheat cultivars to O3 and found significant reduction in plant dry mass and grain yield. So, a screening of the Bangladeshi wheat cultivars for their sensitivity to O3 is urgently needed. Given the importance of wheat for Bangladeshi agriculture and the foreseen increase of O3 levels in eastern Asia, we conducted O3 fumigation experiments in order to (a) test the relative sensitivity to O3 of the most important Bangladeshi wheat cultivars, (b) test which, among the usually measured parameters, are more important in revealing the relative sensitivity of plants to O3, and (c) test whether resistance to O3 has been incorporated into the most modern Bangladeshi wheat cultivars.

Materials and methods Cultivars tested The following ten Bangladeshi wheat (T. aestivum L.) cultivars were tested: Akbar, Bari-25, Bari-26, Bijoy, Gourab, Kanchan, Prodip, Shatabdi, Sourav, and Sufi. These cultivars were released from 1983 to 2010 and constitute the outcome of wheat breeding programs in Bangladesh; their characteristics are shown in the Table 1. Ozone fumigation regimes The wheat seeds (10–15 per pot) were planted in 0.5 lit plastic pots, filled with the same type of commercial soil substrate (Potgrond P, Klasmann-Deilmann GmbH). A week after germination, pots were selected for uniformity of plants, divided equally between two treatments, control (OZ−) and ozonated (OZ+), and transferred to two identical walk-in chambers

Table 1 Characteristics of the ten Bangladeshi wheat cultivars tested in the present research (Barma et al. 2011) Cultivar

Year of release

Plant height (cm)

No. of tillers

Panicle initiation (days)

Life span (days)

Potential 1,000 grain weight (g)

Potential yield (tons/ha)

1. Akbar 4. Kanchan

1983 1983

92–100 90–100

3–4 4–5

60–65 60–68

105–115 105–112

40–42 40–45

3–4.2 3–4

3. Gourab 7. Sourav 6. Shatabdi 2. Bijoy 5. Prodip 8. Sufi 9. Bari-25 10. Bari-26

1998 1998 2000 2005 2005 2005 2010 2010

90–102 90–100 95–100 95–100 95–100 90–102 95–100 92–96

5–6 5–6 5–6 4–5 3–4 4–5 4–5 5–6

60–65 65–70 65–68 60–65 64–66 58–62 57–62 60–65

100–108 107–112 107–115 103–112 102–110 100–110 102–110 104–110

40–48 40–45 46–48 47–52 48–55 36–42 54–58 48–52

3.6–4.8 3.5–4.6 3.6–5 4.3–5 4.3–5.1 3.6–4.8 3.8–5 4–5

13562 Table 2 Area (in hectares), production (in tons), yield (in kilograms per hectare), and the average realized yield (in tons per hectare) of wheat in Bangladesh for the years 2004–2011 (FAO 2013)

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Year

Area harvested (ha)

Production (tons)

Yield (kg/ha)

Tons/ha

2004 2005 2006 2007 2008

641,875 558,413 479,000 399,000 388,000

1,253,380 975,985 735,000 737,000 844,000

1,953 1,748 1,534 1,847 2,175

1.95 1.75 1.53 1.85 2.18

2009 2010 2011

394,612 376,256 373,708

849,046 901,490 972,085

2,152 2,396 2,601 Average realized yield

2.15 2.40 2.60 2.05

under the same conditions (14:10 h (L/D) photoperiod, 63± 3 % relative humidity, 28 °C temperature and light density 135 μmol m−2 s−1). Plants were watered on a daily base. Seven to 10 pots per treatment per cultivar were used. O3 was produced by an electric generator (Air-Zone® XT-6000) that uses U.S. patented O3 elements producing no NOx byproducts. O3 concentrations were measured by a UV analyzer (Environnement S.A O3 42 M). More details for the used infrastructures have previously been reported (Saitanis et al. 2001; Saitanis and Karandinos 2002). In a series of eight experiments, plants were exposed to O3 concentrations of 50, 60, 80, 100, 120, 135, 150, and 200 ppb for 8 h/day, hereafter mentioned as experiments I, II, III, IV, V, VI, VII, and VIII, respectively. All the plants used in all of the experiments, at the beginning of each exposure were of the same age and the same developmental stage. Each experiment lasted until ∼20 % of the plants of the most sensitive cultivar exhibited 80–85 % visible injury, so the remaining plants had lower injury and thus allowing discrimination between sensitive and resistant cultivars. All the exposures were conducted 3 h after the photoperiod began, when plant photosystems were fully functioning. Within each chamber, the positions of the plants were randomly rearranged daily in order to minimize any chamber edge effects.

Data collection Data of the following parameters was gathered from the 2nd or 3rd (from bottom) oldest leaf, 24 h after the last fumigation of each experiment. For the different parameters different number of initial measurements was taken. For example, for the dry weight of the plants unavoidably only one value per plant was taken, for greenness (soil plant analysis development (SPAD)) two reading per leaf from two to three leaves per plant were taken, etc. Finally, all the measurements taken at leaf or plant level of each pot were averaged at pot level which was considered as a replicate of the cultivar in the experiment.

Visible injury The visible injury index (VII) of leaves was visually estimated and scored in the scale of 0–100 %. Biomass dry weight After the last fumigation of each of the experiments I, II, III, and IV, the plants were cut at the soil surface and the dry weights of the aboveground biomass were taken, after oven drying at 65 °C for a week. SPAD—leaf greenness Leaf greenness/chlorosis was measured, nondestructively, using the Minolta SPAD-502m (Minolta Co, LTD, Osaka, Japan). SPAD was calibrated using the spectrophotometric analysis of about 135 chl extracts, coming from leaf tissues exhibiting different extent of greenness (from very dark-green to quite chlorotic leaves). The relationship between total chl content (considered the independent variable) and SPAD (considered the dependent variable) was examined using 135 wheat leaf tissue samples of varying greenness (ranging from very chlorotic to dark green). SPAD value was measured in the lower, fully expanded, leaves of all the plants across all the experiments. Pigments content determination The chls (a and b) and total carotenoids were measured (in the experiments I, II, III, and V) in acetone extracts, using the formulas of Lichtenthaler (1987); absorbances were measured with a double-beam UV/vis (Model Lambda20, Perking Elmer) spectrophotometer. The area of each leaf sample segment was measured by ADOBE Photoshop CS6, on digital photos of the segments. Finally, the chl content on a “per leaf area” base (μg cm−2) was calculated (Saitanis et al. 2001).

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Quantum yield of photosynthesis Quantum yield of photosynthesis (%) of all leaves of the experiments I to VII was measured using a portable Plant Photosynthesis Meter instrument (PPM of EARS Corp.). The quantum yield of photosynthesis was determined from two chl fluorescence measurements: one under ambient light conditions (Fs) and one at light saturation (F′m); then, quantum yield of photosynthesis was calculated using the formula ΦPSII =(F′m −Fs) / F′m, as suggested by Genty et al. (1989). Stomatal resistance The abaxial stomatal resistance (units, s/cm) of the leaves of three plants per pot, in both OZ− and OZ+ (eight pots per cultivar per treatment), was measured using a porometer (AP4, Delta-T Devices Ltd).

but) with the most resistant cultivar, which showed the lowest injury, in the OZ+ group. Absolute values of the effect size within the arbitrary segments 0–0.2, 0.2–0.5, 0.5–0.8, 0.8–1.1, and 1.1+ indicate small, medium, large, very large, and extremely large effect, respectively. Cluster analysis, based on effect size, in all of the measured parameters, was applied for grouping the cultivars according to their response to O3. Squared Euclidian distance and the complete linkage were used for dissimilarity measure and agglomeration, respectively. Finally, a principal component analysis (PCA), based on effect size, was conducted and the cultivars were ordered for their sensitivity to O3 according to their scores on the first principal components (PC). Data management and statistical analyses were conducted using STATISTICA v.10, (© StatSoft Inc. 1984–2001) and MS EXCEL 2010 (© Microsoft) software.

Data analysis

Results

The collected data were submitted to several alternative statistical tests. The data of each parameter in each experiment was firstly separately submitted to two-way analysis of variance (ANOVA). In order to summarize the information resulted from the eight experiments, the data was submitted to an overall ANOVA. To this purpose, the data of each parameter in each experiment was transformed to z scores (standardized). For each parameter the average z score (per cultivar—per O3 treatment), in each experiment, constituted a replicate for the overall ANOVA. This process, not only eliminates any probable heterogeneity between the experiments, but also allows a fair intercomparison of the measured variables, which have different units and scales, as estimators/indicators of O3-induced stress. For each measured parameter, the effect size, ESi(Cohen 1988) for each cultivar, quantifying the size of the difference between control and O3 exposed plants, was calculated using the formula:

Ozone exposures regimes

h i C iðOZþ Þ −C iðOZ− Þ ESi ¼ vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi    u  u n þ −1 * SD þ 2 þ n − −1*SD − 2 u iðOZ Þ iðOZ Þ iðOZ Þ iðOZ Þ u h i t niðOZþ Þ þ niðOZ− Þ −2

ð1Þ where Ci, SDi, and ni stand for the average score, the standard deviation and the number of observations, respectively, in the O3 exposed (OZ+) and in the control (OZ−) plants (reference group), of the cultivar i. The denominator stands for the pooled standard deviation. For the cases of visible injury, each cultivar in the OZ+ group was compared (not with its counterpart in the OZ− group, where the injury was always zero,

Since the criterion for closing each experiment was to achieve a maximum plant injury of about 85 %, the duration of exposure (in days) differed between the experiments according to the O3 levels: the higher the O3 concentrations the shorter the duration of the experiment. However, this relationship was not linear but a curvilinear; after fitting the curve, it seems that the negative exponential model explains the data sufficiently (R2 =0.982) (Fig. 1). It should be mentioned that an exposure to 300 ppb for only 1 day (8 h; not shown in the figure) was highly injurious and impeded intercomparison of the cultivars. In this study, for each experiment j, of duration dj, the concentration was fixed at cj, and the dose D can be described as: X dj     D¼ w c j c j ¼ d jw c j c j ð2Þ i¼1

where w(cj) is the weight function. Since, in this study, d=32 e−0.016c, the weight function w(cj) can be described as:       cj w c j ¼ D= d j c j ¼ D= 32c j e−0:016 ð3Þ If the weight function was flat (w(cj)=w0), the relationship between the duration, d, and concentration, c, should be a hyperbola, viz:   

  d j ¼ D= w c j c j ¼ D= w0 c j ð4Þ Figure 1 shows the negative exponential relationship, found in this study, along with the hyperbola. It is clear that, the duration of exposure, in the observed data, drops more sharply at higher O3 concentrations than the hyperbola, suggesting greater weight at the high concentration.

13564 16

d = 32 e(-0.016 c) R² = 0.982

14 Duration of exposure, d, (days)

Fig. 1 Relationships between the duration of exposure and ozone concentration with the fixed ozone dose observed in this study in comparison to the hyperbola (dashed line)

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12 10 8 6 4 2 0 0

Visible injury Almost all of the O3-treated plants exhibited visible symptoms consisting of chlorotic and necrotic (usually bifacial) spots developed mainly on the lower leaves; in the young (still expanding) leaves the symptoms were observed as necrosis of the tips (Fig. 2). The different cultivars exhibited important differences in visible injury (F(9, 70) =31.509; p<0.001) (Fig. 3). Although there was variability in the cultivars’ response between the exposure regimes, overall, some cultivars exhibited higher visible injury scores than others in most of the experiments. The lowest injury was observed in Kanchan (19.28 %) and Bari-25 (29.82 %), while those exhibited the highest visible injury scores were Akbar (56.82 %) and Bijoy (47.21 %).

50

100 150 Ozone concentration, c, (ppb)

200

250

biomass (F(1, 60) =16.764; p<0.001), and there was also an important difference between the cultivars (F(9, 60) =16.915; p<0.001); the interaction O3 treatment×cultivar effect was not significant (F(9, 60) =1.321; p=0.2452). The largest dry biomass reduction was observed in Akbar (−24.9 %) and Sufi (−20.2 %), while those exhibiting the smallest effect on biomass production were Kanchan (+0.2 %) and Gourab (−4.8 %). Based on the effect size scores, this reduction would be characterized as very large and large for Akbar (0.965) and Sufi (0.572) cultivars, respectively, and as small for Kanchan (0.008) and Gourab (0.167).

SPAD—leaf greenness

Biomass dry weight

SPAD–chl content relationship

The biomass dry weight per plant was lower in the O3 fumigated plants in comparison with the control ones. O3-affected plants’

The data of the 135 samples showed that the overall relationship between total chl content and SPAD was sigmoidal, and the logistic model was found to fit the data quite well (Fig. 4): Y ¼ 34:85=ð1 þ 7:234  expð−0:2098  X ÞÞ

R2 ¼ 0:848

where X is the total chl content and Y is the SPAD value. ð5Þ In order for this relationship to be utilized in a practical way for the estimation of the total chl content from the SPAD value, the logistic equation solved for X generated the following formula for the total chl estimation: Chl T ¼ ½lnð34:85−SPADÞ−lnðSPADÞ−lnð7:234Þ=−0:2098 ð6Þ Leaf greenness Fig. 2 Visible injury of different extent (the upper leaf is the control one) and type (including necrotic spots and chlorosis) developed on the leaves of Bangladeshi wheat cultivars exposed to ozone, under laboratory conditions

The SPAD value was measured in all the treatments in the lower—fully expanded—leaves. SPAD was affected by O3 treatment (F(1, 140) =893.778; p<0.001) and differed among the cultivars (F(9, 140) =4.023; p<0.0001); the O3 treatment×

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13565

1.92

60

1.50

1.23

Visible injury (%)

c 40

1.23

1.07

50

0.64

0.91

0.77

0.63

bc 30

bc

0.00

ab

20

ab

ab

10

bc

abc ab

a

0 AKBAR

BARI-25

BARI-26

BIJOY

GOURAB

KANCHAN

PRODIP

SHATABDI

SOURAV

SUFI

Fig. 3 The average visible injury (%) of the plants submitted to eight different ozone exposure treatments. The average score per treatment of each cultivar constitutes the real replicate. The vertical lines stand for the

standard errors; the numbers indicate the effect size with Kanchan being the reference cultivar. Cultivars marked with the same letter do not differ statistically, according to Bonferroni test, at level of significance a=0.05

cultivar interaction was not significant (F(9, 140) =1.3394; p=0.2219). The SPAD value was substantially reduced in all the cultivars tested, and the effect size in all the cultivars was always extremely large (ES > 1.1). The highest SPAD value reduction was observed in Akbar (−39 %) and Sufi (38.5 %) while the lowest in Kanchan (25.5 %) and Prodip (31.1 %).

The chl content was measured only in four experiments. However, given that the SPAD values were measured in all the plants used in all of the experiments, the total chl content was estimated using the Eq. (6). These data showed again lower chl content in the O3-treated plants (F(1, 140) = 679.34; p<0.0001) and differences among cultivars (F(1, 140) =3.95; p<0.0001), without the interaction effect being significant (F(9, 140) =1.58; p=0.1237).

Pigment content Chl b/a ratio Chlorophyll content At first glance, no differences were observed in chl b/a ratio. However, the relationship between the percentage change of chl b/a ratio per cultivar calculated as ((chl b/a in OZ+ −chl b/a in OZ−)/chl b/a in OZ−) against the average visible injury per cultivar (shown on the vertical axis of Fig. 3) revealed a significant trend of chl b/a ratio increase with increasing visible injury (Fig. 5). According to the effects size values, the increase in chl b/ a ratio would be characterized as large for Shatabdi (0.631) and Akbar (0.584) and medium for Sufi (0.375) and Bijoy (0.317); for the other cultivars, the effects size was small and even negative in the relatively resistant cultivars (e.g., in Kanchan).

The chls a and b were measured, and the total chl content was calculated as the sum of chls a and b. The total chl content was different between the cultivars (F(9, 60) =3.4779; p=0.0016), and it was negatively affected by O3 (F(1, 60) = 68.318; p<0.0001); the interaction effect was not significant (F(9, 60) =0.7886; p=0.6292). The effect size in all the cultivars was always extremely large (ES>1.1). The highest reduction was observed in Bijoy (65.1 %) and Akbar (52.4 %) while the lowest (although still high) was observed in Kanchan (38.2 %) and Sourav (40.2 %).

40 35

SPAD value (arbitary units)

Fig. 4 The calibration line of SPAD values, estimating the leaf greenness, versus the total chlorophyll content (μg/cm2) of 135 wheat leaves

30 25

20

Y=35/[1+7.234* exp(-0.2098*X)] R2=0.848

15 10 5 0

0

5

10

15

20

25

Total chlorophyll content (μg/cm2)

30

35

40

13566

Environ Sci Pollut Res (2014) 21:13560–13571 35

Fig. 5 The percentage change of Chl b/a ratio per cultivar calculated as ((chl b/a in OZ+ −chl b/a in OZ−) / chl b/a in OZ−) against the average visible injury per cultivar

Y = 0.9645X - 23.655 r = 0.7935, R² = 0.6297 F(1,8)=13.604 p<0.00615

Change in Chl b/a ratio (%)

30

Akbar Shatabdi

25

Bijoy

Sufi

20 15 Sourav Gouvar

10 Prodip

5

Bari-25

0 -5

Bari-26

Kanchan

-10 15

20

25

Total carotenoids

35 40 Average visible injury

45

50

55

the interaction effect (O3 treatment ×cultivar; F(9, 0.7927; p=0.6235) was not significant.

The total carotenoids were found to differ between cultivars (F(9, 60) =4.3312; p=0.0002) but also to be reduced by O3 concentration (F(1, 60) =113.56; p<0.0001); the interaction effect was not significant (F(9, 60) =0.8726; p=0.5544) (Fig. 6). The highest reduction was observed in Bijoy (54.3 %) and Akbar (44.2 %) while the lowest reduction was observed in Kanchan (26.0 %). Among control plants, lower carotenoids levels were observed in Akbar (2.17 μg/cm2) and Bijoy (2.52 μg/cm2), whereas the highest carotenoids levels were observed in Prodip (3.23 μg/cm2) and Bari-25 (3.15 μg/cm2) (Fig. 6).

-33.6% (-0.992)

-34.5% (-1.445)

Multivariate analysis Based on the response of the ten cultivars’ effects size, a cluster analysis was performed and the relevant dendrogram was created (Fig. 7). This analysis revealed the existence of three main groups: the 1st group considered being the most sensitive and consisted of Akbar and Bijoy followed by the subgroup of Shatabdi and Sufi; the 2nd group consisted of Bari-25, Bari-26, Gourab, Prodip, and Sourav (considered to

-40.0% (-1.213)

3.5

3.0 2.5

f

1.5 1.0

Cntrl -38.80% (-1.459)

-26.0% (-0.589)

-30.7% (-1.065)

f

ab

-37.6% (-1.303)

def

cd ef ab cd ef

Oz

ef

f

2.0

abc def

-43.0% (-1.443)

-54.3% (-3.685)

-44.2% (-2.234)

120) =

This data showed that the stomata resistance was different between cultivars (F(9, 140) =14.499; p<0.0001) but not between the O3 treatments (F(1, 140) =0.079; p=0.779); the interaction effect (cultivar×O3 treatment) was not significant either (F(9, 140) =1.519; p=0.1466).

O3 treatment, overall, obviously affected the quantum yield of photosynthesis (F(1, 120) =12.9228; p=0.0004) by the same way in all the treated cultivars (F(9, 120) =1.2447; p=0.2745); 4.0

60

Stomatal resistance

Quantum yield of photosynthesis

Carotenoids (μg cm-2)

30

ab cd ef

ab cd

bc de f

ab cd

ab cd ef

a

ab cd e

ab cd ef

cd ef abc

abc

0.5 0.0 AKBAR

BARI-25

BARI-26

BIJOY

GOURAB

Fig. 6 The total carotenoids of the plants submitted to different ozone exposure treatments (experiments: I, II, III, and V), in comparison with the control plants. The vertical lines stand for the standard errors; the numbers indicate the average change (%) in the total carotenoids caused

KANCHAN

PRODIP

SHATABDI

SOURAV

SUFI

by ozone; the numbers in parenthesis indicate the effect size. Cultivars marked with the same letter do not differ statistically, according to Bonferroni test, at level of significance a=0.05

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13567

AKBAR BIJOY SHATABDI SUFI

BARI-25 BARI-26 GOURAB PRODIP SOURAV KANCHAN 0

20

40

60

80

100

Fig. 7 Dendrogram grouping the ten studied Bangladeshi wheat cultivars, based on their ozone-induced changes for each of the measured parameters: visible injury (Inj), dry weight per plant (DW), leaf greenness value (SPAD), total chlorophyll (chl T), chlorophyll b/a ratio (chl b/a), carotenoids (Car), and quantum yield of photosynthesis (ΦPSII). Dissimilarity measure, squared Euclidean distance; agglomeration method, complete linkage

(−0.728) and explained 64 % of the variance in this component. Figure 8 shows clearly that the visible injury is highly positively correlated with chl b/a ratio and negatively correlated with total chl and carotenoids. In addition, injury is negatively correlated with SPAD and dry weight, suggesting that higher injury is expected to be accompanied by increase in chl b/a ratio and reduction in dry weight and SPAD value, total chl and carotenoids. Furthermore, the high loadings of the visible injury and the chl b/a ratio, followed by SPAD and dry weight, on the PC1, reflect the high correlation of these parameters with PC1. They also suggest that, along with the visible injury, chl b/a ratio would be considered as an interesting index for O3-induced injury to plants in experimental situations where O3 effects are not confounded by the effects of canopy shading.

Discussion

be cultivars of intermediate sensitivity); and the 3rd group consisted of the most tolerant cultivar Kanchan. Given that the measured and analyzed parameters were more or less intercorrelated (Table 3) and, thus, there was a redundancy in information, PCA, based on the effect size (ESi) of each of the measured parameter, was conducted. The resulting biplot of this analysis is shown in Fig. 8. The loadings of the parameters to the first three PC and the percentage of variance explained by each parameter are shown in Table 4. The first two principal axes explained 86.9 % of the total variance, with the PC1 explaining 50.8 %. PC1 would be considered as the major axis for cultivar ordinations (Fig. 8). High loading on PC1 had the variables injury (0.930; explaining 24.3 % of the variance of this factor) (Table 4). In the third PC (PC3) only the chl b/a ratio had high loading

The O3 exposure regimes showed that, for the achievement of the same level of injury, the duration of exposure is decreasing exponentially with increasing O3 levels (Fig. 1). Although it is known that the higher concentrations of O3 when applied for a shorter duration are more injurious to plants in comparison to lower concentrations applied for a longer duration (Lefohn and Runeckles 1987), our observation mathematically demonstrates the rising nature of the weight function against increasing O3 concentration. This finding should be taken into account when indices of plant response to O3 are developed. Based on the O3-induced changes in all of the measured parameters, the tested cultivars would be ordered for their sensitivity to O3, on the first principal axis, as follows: Akbar > Bijoy > Sufi ≥ Shatabdi ≥ Bari-26 ≥ Gourab ≥ Sourav ≥ Prodip≥Bari-25>>Kanchan. The outcome of this analysis is in accordance with that of cluster analysis (Fig. 7).

Table 3 Correlation coefficients between visible injury (Inj), dry weight per plant (DW), leaf greenness value (SPAD), total chlorophyll (Chl T), chlorophyll b/a ratio (Chl b/a), carotenoids (Car), quantum yield of

photochemistry (ΦPSII), and stomata resistance (gs) based on the measured effect size of the ozone-induced changes on each parameter

Inj DW SPAD Chl T Chl b/a Car ΦPSII gs

Inj

DW

SPAD

Chl T

Chl b/a

Car

ΦPSII

gs

1 −0.637** −0.806*** −0.606* 0.456 −0.672** −0.224 −0.298

−0.637** 1 0.681** 0.142 −0.568* 0.329 0.478 0.068

−0.806*** 0.681** 1 0.263 −0.387 0.282 0.486 0.022

−0.606* 0.142 0.263 1 −0.199 0.871**** −0.223 0.293

0.456 −0.568* −0.387 −0.199 1 −0.327 −0.084 −0.466

−0.672** 0.329 0.282 0.871**** −0.327 1 0.059 0.462

−0.224 0.478 0.486 −0.223 −0.084 0.059 1 −0.274

−0.298 0.062 0.022 0.293 −0.468 0.467 −0.274 1

*a=0.1;**a=0.05; ***a=0.01; ****a=0.001—statistically significant correlations

13568

Environ Sci Pollut Res (2014) 21:13560–13571 0.8

Fig. 8 Biplot of the PCA ordination of cultivars based on their effect size (ESi) of the ozoneinduced changes on each of the measured parameters: visible injury (Inj), dry weight per plant (DW), leaf greenness value (SPAD), total chlorophyll (chl T), chlorophyll b/a ratio (chl b/a), carotenoids (Car), and quantum yield of photosynthesis (ΦPSII). The scores of cultivars have been scaled by a factor of 0.6 to fit with the scale of parameters

Chl-T

0.6

SUFI

Car BARI-25

0.4

SOURAV BARI-26

SHATABDI

PC2: 24.30%

AKBAR Chl b/a

0.2 0.0 -0.2 -0.4

KANCHAN SPAD DW

Inj

PRODIP

-0.6

GOURAB

QY

-0.8 -1.0

BIJOY

-1.2 -1.0

-0.8

Visible injury was confirmed by PCA to be a critical index for assessing O3 effects. There was also variability in cultivar response and the order of sensitivity differed between experiments. This inconsistency was more obvious in the cultivars of intermediate O3 sensitivity. Such heterogeneity could be due to the uncontrolled experimental error or to subtle differences in cultivar physiology×O3 interactions. Biomass dry weight reduction is considered as the most obvious (along with the visible injury) O3-induced symptom. Biomass reduction, caused by O3, has been reported for wheat (De Temmerman et al. 1992; Fangmeier et al. 1994; Akhtar et al. 2010; Sarkar and Agrawal 2010). Ollerenshaw and Lyons (1999), who studied the impacts of O3 on the growth and yield of field-grown winter wheat, reported that exposure to elevated O3 decreased the above ground biomass by reducing plant density and individual plant relative growth rate. The O3-induced chl reduction in wheat cultivars has been attributed to the reduction of the chloroplasts caused by Table 4 The factor loading and the contribution of variable (%) after the principal components analysis of cultivars based on their effect size of the ozone-induced changes on each of the measured parameters (variables): visible injury (Inj), dry weight per plant (DW), leaf greenness value (SPAD), total chlorophyll (Chl T), chlorophyll b/a ratio (Chl b/a), carotenoids (Car), and quantum yield of photochemistry (ΦPSII) Factor loadings F1

F2

Contributions of the variables (%) F3

F1

Inj −0.930 −0.086 0.090 24.349 DW 0.781 −0.424 0.168 17.185 SPAD 0.808 −0.359 −0.149 18.411 Chl T 0.613 0.745 −0.158 10.570 Chl b/a −0.616 0.099 −0.728 10.682 Car 0.731 0.558 −0.166 15.040 ΦPSII 0.366 −0.713 −0.433 3.762

F2

F3

0.436 10.609 7.573 32.617 0.586 18.298 29.881

0.972 3.425 2.692 3.006 64.008 3.316 22.582

The first three factors explained a total of 86.9 % (F1, 50.8; F2, 24.3; F3, 11.8)

-0.6

-0.4

-0.2

0.0 PC1: 50.77%

0.2

0.4

0.6

0.8

1.0

O3(Ojanperä et al. 1992; Bindi et al. 2002), since chloroplasts have been shown, by ultrastructural studies, to be the most sensitive to O3 of all cell organelles (Miyake et al. 1989; Sutinen et al. 1990). The estimated chl content (by using the Eq. 6) was in good agreement with the measured total chl content. This suggests that SPAD readings can be used for the estimation of the total chl content (after establishing the appropriate calibration equation for the plant species under investigation). The reduction in SPAD values ranged from about 25 to about 40 %. Thus, this parameter is more sensitive to O3 than plant biomass (maximum reduction about 25 %), especially in the case of short term exposure experiments. It should be noted here that this study revealed that the relationship between chl content (considered the independent variable) and SPAD (considered the dependent variable) is sigmoidal. Previous studies, which have not incorporated very green or very chlorotic leaves, and thus they were restricted to the relatively linear part of the sigmoidal function, have erroneously concluded that this relationship is linear (e.g., Wang et al. 2004). Moreover, other studies have incorrectly used the chl content as dependent variable and SPAD as independent variable and they have concluded that the relationship is exponential (e.g., Uddling et al. 2007). In the latter case, a very small increase in SPAD reading, in very dark-green leaves, erroneously suggests unnaturally high chl content. In addition, a more careful survey of the scatterplots, presenting the exponential relationship in these studies, clearly shows the deviation of the data from the exponential model in the lower part of the curve (in the area of chlorotic leaves). The nonlinear nature of the chl-SPAD relationship has been attributed (i) to the nonuniform chl distribution across the leaf surface (influenced by the structural organization of grana within chloroplasts, the chloroplasts within cells and the cells within tissue layers) (Fukshansky et al. 1993; Uddling et al. 2007) and (ii) to multiple scattering of the radiation entering the leaf (by reflection and refraction at the curved air-cell wall

Environ Sci Pollut Res (2014) 21:13560–13571

13569

interfaces (McClendon and Fukshansky 1990; Uddling et al. 2007). Figure 5 shows that there is a trend of increase in the chl b/a ratio, by an average of 13 %, which, however, was higher in the highly injured cultivars. This is in agreement with the findings of Caregnato et al. (2013) who found an O3-induced increase in chl b/a ratio in an O3-sensitive bean cultivar (Fepagro 26) but not in the resistant one (Irai). The change in the ratio of a and b chl forms could be an indicator of leaves undergoing premature senescence, a process known to be induced by O3. Chl b is associated with the major light harvesting proteins that are located primarily in chloroplast grana stacks. As chloroplasts break down during senescence, the stroma lamellae (unstacked membranes) that contain photosystem I chl a proteins break down first leaving the grana with the higher chl b content (Gepstein 1988). However, in the case of the plants growing under field conditions, senescence related effects on chl b/a ratio will be difficult to be attributed to O3 alone, since canopy shading is known to cause acclimation of chl proteins and accelerated senescence (Burkey and Wells 1996). Many investigations have shown that species or cultivars with increased stomatal conductance allow much more O3 to enter the tissues, thus making them more susceptible to the pollutant. Cultivars with high stomatal resistance are expected to be more tolerant to O3. Salvatori et al. (2013), who recently studied the different response to O3 of sensitive (S156) and resistant (R123) snap bean genotypes (Phaseolus vulgaris L.), which are used as an O3-biomonitoring system (Burkey et al. 2012), found that R123 plants showed an O3-induced stomatal closure (−38.1 % relative to the control) during flowering and the onset of visible injury, a behavior that can be regarded as an O3 avoidance mechanism. In our study, the relatively tolerant cultivars Kanchan and Prodip showed the highest resistance in the control plants, in agreement with the hypothesis that stomatal resistance may play a role in plant response to O3. 5

Linear (All the 10 cultivars included) Linear (All except KANCHAN)

4

Linear (All except AKBAR)

KANCHAN

Linear (All except KANCHAN and AKBAR)

3

Y = -0.1212X + 242.92 R² = 0.3714

2 Score on PC1

Fig. 9 The scores of ten Bangladeshi wheat cultivars on the first principal component axis versus their year of release. The regression lines were drawn as follow: all the ten cultivars included (Y1), all the cultivars included except Kanchan (Y2), all the cultivars included except Akbar (Y3), all the cultivars included except Kanchan and Akbar (Y4)

Several scientific studies have reported evidence suggesting that, in general, the modern wheat cultivars are more sensitive to O3 than the older ones (Velissariou et al. 1992; Pleijel et al. 2006). This was attributed to inadvertent selection by plant breeders (Velissariou et al. 1992). Barnes et al. (1990) attributed the higher sensitivity to O3 of the modern cultivars to the increased use of agrochemicals, in recent decades, many of which are known to act as antioxidants. Given the large gap between the reported average realized and potential yield of the wheat cultivars in Bangladesh, it was expected that breeders would have incorporated the resistance to O3 during the selection process and thus the modern cultivars were expected to be more O3 resistant than the older ones. After having established the relative sensitivity of the tested cultivars to O3, we plotted the scores of the cultivars on the PC1 against their years of release (Fig. 9). When all the cultivars were included in the regression no any trend was observed (r=0.05) with the most sensitive to O3(Akbar) and the most resistant to O3(Kanchan) cultivars released in the year 1983. Excluding either of these two cultivars produced very misleading results and demonstrates the limitation of examining trends with a limited number of cultivars: when Kanchan was removed, a positive strong trend (r=0.61) was appeared, while when Akbar was removed an opposite strong trend (r=0.68) was revealed. When both cultivars were excluded no any trend was observed (r=0.05). This clearly suggests that the cultivars tested here were bred for higher potential yield without incorporating O3 resistance. This is in agreement with the findings of Biswas et al. (2009), who showed that higher O3 concentrations in the breeding sites have played little role in developing O3 tolerance in winter wheat cultivars. This may reflect limited genetic potential within the germplasm used for cultivar development and suggests that progress toward developing O3tolerant cultivars will require an evaluation of O3 tolerance within the genetic base and then incorporating O3 tolerance as a specific breeding objective.

PRODIP

0 -1

BARI-25

SOURAV

1 Y = -0.0015X + 3.0225 R² = 6E-05

GOURAB

BARI-26

Y= 0.0127X - 25.423 R² = 0.0027

SHATABDI SUFI BIJOY

-2 -3

-4 1980

Y = 0.1219X - 244.36 R² = 0.3994 AKBAR

1985

1990

1995

2000

Year of cultivar 's release

2005

2010

2015

13570

A limitation of this study is that the biomass reduction and the leaf response observed in our laboratory experiments do not necessarily reflect the yield response of the cultivars under field conditions in Bangladesh. The results of this study, however, provide strong evidence that the wheat Bangladeshi wheat cultivars are quite sensitive to O3 and reveal the urgent need for the assessment of the ambient O3 effects in wheat and other crops in Bangladesh.

Conclusions After treating ten Bangladeshi wheat cultivars with eight different O3 regimes, the following conclusion were drawn: (a) all the cultivars showed, more or less, O3-induced symptoms; according to their overall response, the order of sensitivity to O3 was as follows: Akbar>>Sufi≥Bijoy≥Shatabdi> Bari-26≥Gourab>Bari-25≥Prodip≥Sourav>>Kanchan. (b) Among the most important parameters for discrimination of the cultivars according to their sensitivity were visible injury and chl b/a ratio, while the least important discrimination parameter was the quantum yield of photosynthesis. (c) The chl-SPAD relationship is better parameterized by the sigmoidal function using chl content as independent variable and SPAD as depended variable. (d) Furthermore, although the more modern tested cultivars are known to be “potentially” more productive in comparison with the older ones, after taking the regression of the overall response to O3 of all the tested cultivars against their year of release no any trend was found, suggesting that the tested Bangladeshi wheat cultivars have not been selected for resistance to O3. After taking into account the foreseen increases in ambient O3 levels across the region, it is suggested that O3 tolerance should be incorporated as an objective in the wheat breeding programs. Acknowledgments The authors thank the Greek State Scholarships Foundation (IKY) for supporting the 1 year postdoctoral scholarship (Ref. 18504a) of the co-author Shafiqul Bari in the Agricultural University of Athens, Greece, where the experiments were conducted. The authors thank all the four unknown reviewers for their valuable suggestions.

References Akhtar A, Yamaguchi M, Inada H, Hoshino D, Kondo T, Izuta T (2010) Effects of ozone on growth, yield and leaf gas exchange rates of two Bangladeshi cultivars of wheat (Triticum aestivum L.). Environ Pollut 158(5):1763–1767 Avnery S, Mauzerall DL, Liu J, Horowitz W (2011) Global crop yield reductions due to surface ozone exposure: 1. Year 2000 crop production losses and economic damage. Atmos Environ 45(13):2284–2296 Azad AK, Kitada T (1998) Characteristics of the air pollution in the city of Dhaka, Bangladesh in winter. Atmos Environ 32(11):1991–2005

Environ Sci Pollut Res (2014) 21:13560–13571 Barma NCD, Malakar PK, Pandit D (2011) Wheat production and seed storage training manual (In Bengali: Gom Uthpadon o Biz Songrokkhon Prosikkhon Nirdeshika). Wheat Research Center, Bangladesh Agricultural Research Institute, Dinajpur, Bangladesh: 1–24 Barnes JD, Velissariou D, Davison AW, Holevas CD (1990) Comparative ozone sensitivity of old and modern Greek cultivars of wheat. New Phytol 116:707–714 Bindi M, Hacour A, Vandermeiren K, Craigon J, Ojanperä K, Selldén G, Högy P, Finnan J, Fibbi L (2002) Chlorophyll concentration of potatoes grown under elevated carbon dioxide and/or ozone concentrations. Eur J Agron 17(4):319–335 Biswas DK, Xu H, Li YG, Sun JZ, Wang XZ, Han XG, Jiang GM (2008) Genotypic differences in leaf biochemical, physiological and growth responses to ozone in 20 winter wheat cultivars released over the past 60 years. Glob Chang Biol 14:46–59 Biswas DK, Xua H, Yang JC, Li YG, Chen SB, Jiang CD, Li WD, Ma KP, Adhikary SK, Wang XZ, Jiang GM (2009) Impacts of methods and sites of plant breeding on ozone sensitivity in winter wheat cultivars. Agric Ecosyst Environ 134:168–177 Burkey KO, Carter TE (2009) Foliar resistance to ozone injury in the genetic base of U.S. and Canadian soybean and prediction of resistance in descendent cultivars using coefficient of parentage. Field Crop Res 111(3):207–217 Burkey KO, Wells R (1996) Effects of natural shade on soybean thylakoid membrane composition. Photosynth Res 50:149–158 Burkey KO, Booker FL, Ainsworth EA, Nelson RL (2012) Field assessment of a snap bean ozone bioindicator system under elevated ozone and carbon dioxide in a free air system. Environ Pollut 166: 167–171 Caregnato FF, Bortolin CR, Divan MA, Moreira JCF (2013) Exposure to elevated ozone levels differentially affects the antioxidant capacity and the redox homeostasis of two subtropical Phaseolus vulgaris L. varieties. Environ Pollut 93(2):320–330 Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn Lawrence Erlbaum Associates Danielsson H, Karlsson GP, Karlsson PE, Pleijel HH (2003) Ozone uptake modelling and flux-response relationships—an assessment of ozoneinduced yield loss in spring wheat. Atmos Environ 37(4):475–485 De Temmerman L, Vandermeiren K, Guns M (1992) Effects of air filtration on spring wheat grown in open-top field chambers at a rural site. I. Effects on growth, yield and dry matter partitioning. Environ Pollut 77:1–5 Dentener F, Stevenson D, Ellingsen K, Van Noije T, Schultz M, Amann M, Atherton C, Bell N, Bergmann D, Bey I, Bouwman L, Butler T, Cofala J, Collins B, Drevet J, Doherty R, Eickhout B, Eskes H, Fiore A, Gauss M, Hauglustaine D, Horowit L, Isaksen ISA, Josse B, Lawrence M, Krol M, Lamarque JF, Montanaro V, Müller JF, Peuch VH, Pitari G, Pyle J, Rast S, Rodriguez J, Sanderson M, Savage NH, Shindell D, Strahan S, Szopa S, Sudo K, Van Dingenen R, Wild O, Zeng G (2006) The global atmospheric environment for the next generation. Environ Sci Tech 40:3586–3594 Emberson LD, Buker P, Ashmore MR, Mills G, Jackson LS, Agrawal M, Atikuzzaman MD, Cinderby S, Engardt M, Jamir C, Kobayashi K, Onah NTK, Quadir QF, Wahid A (2009) A comparison of North American and Asian exposure-response data for ozone effects on crop yields. Atmos Environ 43:1945–1953 Fangmeier A, Brockerhoff U, Grüters U, Jäger HJ (1994) Growth and yield responses of spring wheat (Triticum aestivum L. cv. turbo) grown in open-top chambers to ozone and water stress. Environ Pollut 83:317–325 FAO-Food and Agriculture Organization of the United Nations (2013). http://faostat3.fao.org/faostat-gateway/go/to/download/Q/QC/E. Accessed 15 January 2014 Fuhrer J, Booker F (2003) Ecological issues related to ozone: agricultural issues. Environ Int 29(2–3):141–154

Environ Sci Pollut Res (2014) 21:13560–13571 Fuhrer J, Skärby L, Ashmore MR (1997) Critical levels for ozone effects on vegetation in Europe. Environ Pollut 97(1–2):91–106 Fukshansky L, Martinez A, Remisowsky V, McClendon J, Ritterbusch A, Richter T, Mohr H (1993) Absorption spectra of leaves corrected for scattering and distributional error: a radiative transfer and absorption statistics treatment. Photochem Photobiol 57:538–555 Genty B, Briantais JM, Baker NR (1989) The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochim Biophys Acta 990:87–92 Gepstein S (1988) Photosynthesis. In: Nooden LD, Leopold AC (eds) Senescence and aging in plants. Academic, New York, pp 85–109 Goumenaki E, Taybi T, Borland A, Barnes J (2010) Mechanisms underlying the impacts of ozone on photosynthetic performance. Environ Exp Bot 69:259–266 Hasan MK (2006) Yield gap in wheat production: a perspective of farm specific efficiency in Bangladesh. Dissertation, Bangladesh Agricultural University Kaliakatsou E, Bell JNB, Thirtlen C, Rose D, Power SA (2010) The impact of tropospheric ozone pollution on trial plot winter wheat yields in Great Britain—an econometric approach. Environ Pollut 158(5):1948–1954 Lefohn AS, Runeckles VC (1987) Establishing standards to protect vegetation—ozone exposure/dose considerations. Atmos Environ 21(3):561–568 Lichtenthaler HK (1987) Chlorophylls and carotenoids: pigments of photosynthetic biomembranes. Meth Enzymol 148:350–1382 Lorenzini G, Saitanis CJ (2004) Ozone: a novel plant “pathogen”. In: Sanita’ di Toppi L, Pawlik-Skowrońska B (Eds). Abiotic stresses in plants. Kluwer Academic Publishers: 256 McClendon JH, Fukshansky L (1990) On the interpretation of absorption spectra of leaves—I. Introduction and the correction of leaf spectra for surface reflection. Photochem Photobiol 51:203–210 Mikkelsen TN, Dodell B, Lütz C (1995) Changes in pigment concentration and composition in Norway spruce induced by long-term exposure to low levels of ozone. Environ Pollut 87:197–205 Miyake H, Matsumura H, Fujinuma Y, Totsuka T (1989) Effects of low concentrations of ozone on the fine structure of radish leaves. New Phytol 111:187–196 Ohara T, Akimoto H, Kurokawa J, Horii N, Yamaji K, Yan X, Hayasaka T (2007) An Asian emission inventory of anthropogenic emission sources for the period 1980–2020. Atmos Chem Phys 7: 4419–4444 Ojanperä K, Sutinen S, Pleijel H, Sellden G (1992) Exposure of spring wheat, Triticum aestivum L., cv. Drabant, to different concentrations of ozone in open-top chambers: effects on the ultrastructure of flag leaf cells. New Phytol 120:39–48 Oksanen E, Pandey V, Pandey AK, Keski-Saari S, Kontunen-Soppela S, Sharma C (2013) Impacts of increasing ozone on Indian plants. Environ Pollut 177:189–200

13571 Ollerenshaw JH, Lyons T (1999) Impacts of ozone on the growth and yield of field-grown winter wheat. Environ Pollut 106(1):67–72 Pandit DB, Islam MM, Ur-Rashid MM, Sufian MA (2007) Participatory variety selection in wheat and its impact on scaling-up seed dissemination and varietal diversity. Bangladesh J Agr Res 32(3):473–486 Pleijel H (2011) Reduced ozone by air filtration consistently improved grain yield in wheat. Environ Pollut 159(4):897–902 Pleijel H, Eriksen AB, Danielsson H, Bondesson N, Selldén G (2006) Differential ozone sensitivity in an old and a modern Swedish wheat cultivar—grain yield and quality, leaf chlorophyll and stomatal conductance. Environ Exp Bot 56(1):63–71 Saitanis CJ (2003) Background ozone monitoring and phytodetection in the greater rural area of Corinth—Greece. Chemosphere 51(9):913–923 Saitanis CJ, Karandinos MG (2002) Effects of ozone on tobacco (Nicotiana tabacum L.) varieties. J Agr Crop Sci 188:51–58 Saitanis CJ, Riga-Karandinos AN, Karandinos MG (2001) Effects of ozone on chlorophyll and quantum yield of tobacco (Nicotiana tabacum L.) varieties. Chemosphere 42(8):945–953 Salam A, Hossain T, Siddique MNA, Alam SAM (2008) Characteristics of atmospheric trace gases, particulate matter, and heavy metal pollution in Dhaka, Bangladesh. Air Qual Atmos Health 1:101–109 Salvatori E, Fusaro L, Mereu S, Bernardini A, Puppi G, Manes F (2013) Different O3 response of sensitive and resistant snap bean genotypes (Phaseolus vulgaris L.): the key role of growth stage, stomatal conductance, and PSI activity. Environ Exp Bot 87:79–91 Sarkar A, Agrawal SB (2010) Elevated ozone and two modern wheat cultivars: an assessment of dose dependent sensitivity with respect to growth, reproductive and yield parameters. Environ Exp Bot 69(3):328–337 Sikder HA, Nasiruddin M, Suthawaree J, Kato S, Kajii Y (2013) Long term observation of surface O3 and its precursors in Dhaka, Bangladesh. Atmos Res 122:378–390 Singh AA, Agrawal SB, Shahi JP, Agrawal M (2014) Assessment of growth and yield losses in two Zea mays L. cultivars (quality protein maize and nonquality protein maize) under projected levels of ozone. Environ Sci Pollut Res 21(4):2628–2641 Sutinen S, Skirby L, Wallin G, Sellden G (1990) Long-term exposure of Norway spruce, Picea abies (L.) Karst. to ozone in open top chambers. II. Effects on the ultrastructure of needles. New Phytol 115: 345–355 Uddling J, Gelang-Alfredsson J, Piikki K, Pleijel H (2007) Evaluating the relationship between leaf chlorophyll concentration and SPAD-502 chlorophyll meter readings. Photosynth Res 91(1):37–46 Velissariou D, Barnes JD, Davison AW (1992) Has inadvertent selection by plant breeders affected the O3 sensitivity of Modern Greek cultivars of spring wheat? Agric Ecosyst Environ 38(1– 2):79–89 Wang Q, Chen J, Li Y (2004) Nondestructive and rapid estimation of leaf chlorophyll and nitrogen status of peace lily using a chlorophyll meter. J Plant Nutr 27(3):557–569