Original Article
Differential Activity of Antioxidant Enzymes and Physiological Changes in Wheat ( Triticum aestivum L.) Under Drought Stress
Kamal MIRI-HESAR, Ali DADKHODAIE*, Saeideh DOROSTKAR, Bahram HEIDARI
Shiraz University, School of Agriculture, Department of Crop Production and Plant Breeding, Shiraz, Iran; [email protected] [email protected] (*corresponding author); [email protected]; [email protected]
Abstract
Drought stress is one of the most significant environmental factors restricting plant production all over the world. In arid and semi-arid regions where drought often causes serious problems, wheat is usually grown as a major crop and faces water stress. In order to study drought tolerance of wheat, an experiment with 34 genotypes including 11 local and commercial cultivars, 17 landraces, and six genotypes from International Maize and Wheat Improvement Center (CIMMYT) was conducted at the experimental station, School of Agriculture, Shiraz University, Iran in 2010-2011 growing season. Three different irrigation regimes (100%, 75% and 50% Field Capacity) were applied and physiological and biochemical traits were measured for which a significant difference was observed in genotypes. Under severe water stress, proline content and enzymes’
activities increased while the relative water content (RWC) and chlorophyll index decreased significantly in all genotypes. Of these indices, superoxide dismutase (SOD) and RWC were able to distinguish tolerant genotypes from sensitives. Moreover, yield index (YI) was useful in detecting tolerant genotypes. The drought susceptibility index (DSI) varied from 0.40 to 1.71 in genotypes. These results indicated that drought-tolerant genotypes could be selected based on high YI, RWC and SOD and low DSI. On the whole, the genotypes 31 (30ESWYT200), 29 (30ESWYT173) and 25 (Akbari) were identified to be tolerant and could be further used in downstream breeding programs for the improvement of wheat tolerance under water limited conditions.
Keywords: antioxidant enzymes; drought stress; grain yield; landraces; wheat
AcademicPres Notulae Scientia Biologicae
Print ISSN 2067-3205; Electronic 2067-3264 Not Sci Biol, 2019, 11(2):266-276. DOI: 10.15835/nsb11210390
Introduction
Drought stress is known to be the most important environmental factor that limits plant’s growth and production (Kirigwi et al., 2004; Almeselmani et al., 2011) and has been a great threat to wheat production worldwide.
For example, in 1999, about 9 mt wheat grains was harvested from an area of 6.5 m ha in Iran, which increased to 15 mt in 2005, but decreased to 11 mt in 2016 predominantly due to the dwindling water resources and increasing drought intensity (FAO STAT, 2017).
Accordingly, it is vital to understand wheat’s response to drought stress throughout growth stages to mitigate its detrimental effects.
Drought stress responses are altered by changes in the expression level of various compatible solutes/osmolytes and the reactive oxygen species (ROS), which in turn affect plant at morphological, physiological and biochemical levels (Shinozaki et al., 2007; Sheoran et al., 2013). Moderate to
severe stresses drastically affects wheat’s various physiological traits such as relative water content (RWC), chlorophyll content and chlorophyll fluorescence.
Therefore, chances are there that genotypes may respond differentially under moderate to severe water stress at a similar growth stage. Also, during drought stress, plant water relations play a key role in the activation and/or modulation of the antioxidant defense mechanism (De Carvalho, 2008). The elimination of O2− by superoxide dismutase (SOD) generates H2O2, which is removed by catalase (CAT) and peroxidase (POX) (Bartosz, 1997). A number of studies have indicated that higher activity levels of antioxidant enzymes contribute to better drought tolerance in wheat through increasing its protection capacity against oxidative damage (Sairam et al., 1997;
Almeselmani et al., 2006). However, change in activities of antioxidant enzymes under drought stress depends on plant species, genotype and stress intensity and duration (DaCosta and Huang, 2007).
Received: 11 Oct 2018. Received in revised form: 15 Feb 2019. Accepted: 22 Jun 2019. Published online: 28 Jun 2019.
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Experimental design and field evaluations
The experimental frame was as a split-plot design where irrigation regimes (100% field capacity (FC), 75% FC and 50% FC) were used in larger main plots in a randomized complete block design with three replications and genotypes were allocated to smaller sub-plots. The soil was silty clay in which the percentages of silt, clay and sand in the depth of 0-30 cm soil profile were 42.72%, 52% and 5.28%, respectively. The electrical conductivity of the soil was 0.395 dS m−1 with pH 7.8. The genotypes were planted in four 2.5-meter-long rows with a density of 300 seeds m−2. An amount of 110 kg ha−1 urea fertilizer (46% nitrogen) was distributed at planting and ear emergence stages. Drought stress was applied based on field capacity and the amount of water per irrigation was determined based on soil moisture content as below.
where:
Fc is field capacity, dn is height of required water for irrigation, θm is soil moisture content, ρb is soil apparent density, D is depth of soil sampling, FW and DW are fresh and dried weights of soil, respectively (Zimmerman, 2002).
Weather information for the experimental site is given in Table 2. Samples for measuring grain yield, thousand kernel weight (TKW) and plant height were taken from the middle rows at physiological maturity leaving 50 cm either side as border.
Understanding the association of antioxidant enzyme activity, physiological responses and variation in drought tolerance of genotypes is important to further decipher factors that control plant defense. Iran, with more than 50%
of its agricultural land allocated to wheat production, suffers from low rainfall and consequently, grain yield shows a significant fluctuation in consecutive years. At the same time, it benefits from a rich germplasm compatible to local conditions. Despite this, the genetic resources have been underutilized. Therefore, the present study was conducted to evaluate the physiological traits and antioxidant responses of wheat landraces and some other genotypes under drought stress, at different levels of irrigation. Our hypothesis is that water stress at different levels can change the physiological and biochemical responses of plants and some genotypes may display higher tolerance.
Materials and Methods Plant materials
Thirty-four wheat genotypes including eight commercial cultivars (‘Arvand’, ‘Karaj3’, ‘Darab2’,
‘Khazar1’, ‘Sepahan’, ‘Shiraz’, ‘Cross Boolani’ and
‘Bezostaya’), six CIMMYT- derived lines (30th Elite Spring Wheat Yield Trials released by International Maize and Wheat Improvement Center (CIMMYT) in 2011) and twenty landraces consisting of ‘Shahani’, ‘Hawasi’, ‘Akbari’
and ‘17 KC’-designated genotypes were used in current study (Table 1). Field evaluations were performed at the research station (52˚ 32´ E and 29˚ 36´ N, 1810 m above sea level), School of Agriculture, Shiraz University, Iran.
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Table 1. List of 34 hexaploid wheat genotypes (landraces and cultivars) used to evaluate drought stress response
code Genotype Origin Code Genotype Origin Code Genotype Origin
1 ‘Arvand’ Iran 13 KC136 Iran 25 Akbari Iran
2 ‘Karaj3’ Iran 14 KC184 Iran 26 30ESWYT105 CIMMYT
3 ‘Darab2’ Iran 15 KC29 Iran 27 30ESWYT120 CIMMYT
4 ‘Khazar1’ Iran 16 KC68 Iran 28 30ESWYT160 CIMMYT
5 ‘Sepahan’ Iran 17 KC201 Iran 29 30ESWYT173 CIMMYT
6 ‘KC185’ Iran 18 KC219 Iran 30 30ESWYT184 CIMMYT
7 ‘KC161’ Iran 19 KC50 Iran 31 30ESWYT200 CIMMYT
8 ‘KC41’ Iran 20 KC211 Iran 32 Shiraz Iran
9 ‘KC187’ Iran 21 KC227 Iran 33 Cross Boolani Iran
10 ‘KC132’ Iran 22 KC91 Iran 34 Bezostaya Iran
11 ‘KC174’ Iran 23 Shahani Iran
12 ‘KC99’ Iran 24 Hawasi Iran
The genotypes preceded by KC, were obtained from Seed and Plant Improvement Research Institute in Karaj, Iran. Genotypes designated with ESWYT are from 30th Elite Spring Wheat Yield Trials released by International Maize and Wheat Improvement Center (CIMMYT) in 2011
Table 2. Some weather parameters for the experimental site in 2010-2011 growing season
Month Temperature (°C)
Relative humidity (%) Precipitation (mm)
Minimum Maximum
November - 6.94 18.20 30.85 0.00
December - 5.79 12.30 42.93 48.5
January - 1.30 10.26 48.98 107.5
February 0.89 16.27 49.47 76.8
March 3.32 20.31 50.02 30.5
April 7.83 27.50 48.27 0.00
May 12.39 34.10 24.47 0.00
June 15.30 35.77 20.92 0.00
Total - - - 263.3
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Physiological traits
Determination of relative water content (RWC)
The relative water content in flag leaves was measured using twenty randomly-chosen fully expanded leaves based on the following formula, where FW is fresh weight, TW and DW are their turgid and dry weights, respectively (turgid weight was measured when leaves were put in distilled water for 16-18 hours while their dry weight was measured after being oven-dried at 70 °C for 72 hours (Schonfeld et al., 1988).
RWC = ×100
−
− DW TW
DW FW
Chlorophyll content
Chlorophylls a, b and total chlorophyll were calculated based on Lichtenthaler and Wellburn method (1983).
According to this method, 25 g of flag leaf tissue was homogenized using 5 ml 80% acetone. Then the absorption was read at λ=663 and 646 nm with spectrophotometer (S2100 Diode Array model, WPA, UK). The amount of chlorophyll was calculated using the following formulas:
Chl a = (12.25 A663 – 2.79 A646) Chl b = (21.21 A646 – 5.1 A663) Chll = Chl a + Chl b
Yield traits and drought index
Plant height in a sample of 10 plants was measured from the soil surface to the tip of the spike, excluding awns. Plants were harvested at physiological maturity and TKW and grain yield were measured using an electric balance. The drought susceptibility index (DSI) and yield stability were calculated as follows:
DSI= (Fischer and
Maurer, 1978)
YSI= (Bouslama and Schapaugh, 1984) YD and Y are the grain yield for each genotype under water stress and control, respectively. D and are mean grain yield of all genotypes under water stress and control, respectively.
Enzyme extraction and determination of their activities To extract enzymes, 0.5 g of fresh tissue was homogenized in 2 ml buffer (pH=7.8), consisted of 0.607 g Tris, 0.05 g PVP (polyvinylpyrrolidone) and 50 ml water.
Then, the homogenate was transferred to a new tube and centrifuged at 13000 rpm for 15 min at 4 ˚C. Finally, the supernatant was used for the spectrophotometric assay of different antioxidant enzymes (Sairam and Saxena, 2000;
Sairam and Srivastava, 2001).
Superoxide Dismutase (SOD) was measured based on its ability to stop light reviving of NBT in the presence of riboflavin and light using Beauchamp and Fridovich method (1971). The concentration of peroxidase (POX) activity was determined based on guaiacol oxidation using the method described by Chance and Maehly (1995).
Catalase (CAT) activity was determined based on the consumption of H2O2 as described by Rao et al. (1996).
Proline content
Proline concentration was measured following the method by Bates et al. (1973). Five ml sulfosalicylic acid (3%) was added to 0.5 g frozen leaf tissue homogenized and passed through filter paper. Then two ml of this solution was mixed with an equivalent volume of ninhydrine (consisting of 1.25 g ninhydrine (Sigma-Aldrich, USA), 30 ml acetic acid and 20 ml 6M phosphoric acid) and two ml acetic acid. Samples were placed in water bath at 100 °C for one hour, after which were incubated in cold water for 15 minutes. Following this, four ml toluene was applied to each tube. Two hours later, two phases formed, of which the liquid phase was used to measure proline concentration at λ=520 nm with a spectrophotometer (S2100 Diode Array model, WPA, UK). Proline concentration was calculated using the following formula:
Where M is the value shown for each sample by the spectrophotometer, T is toluene volume (ml) and W is tissue weight (g).
Statistical analysis
Experimental data were analyzed using SAS (SAS, 2004) and MINITAB software and mean comparison was performed using LSD test at 5% probability level. The Excel software was used to draw graphs and diagrams.
Results and Discussion Relative water content
Significant differences for genotype and irrigation were observed with respect to RWC (Table 3). Overall, genotypes’ RWC changed from 83.1% under normal condition to 58.9% under 75% FC and 54.2% under 50%
FC treatments in all thirty-four genotypes, the latter showing higher reduction (Fig. 1). The highest and lowest RWC contents belonged to genotypes number 20, 8, 2 and 29, 25, 5, 3 under normal condition, genotypes 28, 24, 19, 1 and 22, 21, 17 under 75% FC drought stress, and genotypes 28, 24, 19 and 33, 22, 13, 2 under 50% FC drought stress, respectively. Results showed that some genotypes maintained relatively higher RWC compared to others under both treatments (50% and 75% FC). The genotypes of former group were found to have low DSI and high YI and therefore were drought tolerant. Conversely, genotypes with high DSI and low YI were sensitive to drought. This indicates that RWC as a primary trait responding to drought reduces significantly in sensitive genotypes compared to tolerant genotypes. Variation in RWC also may be attributed to differences in the ability of a genotype to absorb more water from the soil and/or to control water loss through the stomata (Keyvan, 2010). This trait as an indicator of cell water status has been shown to be significantly associated with yield and stress tolerance (Almeselmani et al., 2006; 2011).
Chlorophyll index
Total chlorophyll content reduced significantly in all genotypes under drought stress (Table 4).
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Under normal condition, the highest total chlorophyll content belonged to genotypes 32 and 27, while the lowest amount was detected in genotypes 22, 21 and 6. Under 75%
FC drought condition, the highest and lowest total chlorophyll content belonged to genotypes 34, 24, 3, and 22, 12, 6, respectively. Under 50% FC drought, genotypes 34, 31, 30, 25, 3, 2 and 1 showed the highest content whereas genotypes 32, 17 and 6 had the lowest total chlorophyll content. The amount of chlorophyll reduction in some genotypes was lower (for example 35% in genotype 34) while others experienced higher reduction (64%
reduction in genotype 32). The former genotype was found to be tolerant while the latter was sensitive to drought stress.
It has been shown that chlorophyll loss is associated with environmental stress, and higher chlorophyll/carotenoids ratio might be a good indicator of stress tolerance in plants (Hendry and Price, 1993). Many previous studies have reported that wheat tolerant genotypes have higher chlorophyll content and predominantly experience lower chlorophyll reduction under stress (Castrillo and Calcargo, 1989; Sairam et al., 1997; Nyachiro et al., 2001). This clearly shows that maintaining chlorophyll concentration under stress conditions is a strategy that plants undertake to overcome drought stress and helps them to stabilize photosynthesis. For this reason, this trait has been successfully employed by many researchers to screen and
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select for drought tolerant wheat genotypes (Castrillo and Calcargo, 1989; Almeselmani et al., 2011).
Similar to total chlorophyll, drought stress also caused a significant reduction in both chlorophyll a and chlorophyll b contents. This reduction in tolerant genotypes, however, was lower than sensitive ones. Genotypes with high chlorophyll content under higher water stress conditions also had higher yields (Table 5) which was reflected by a significant correlation between chlorophyll index and yield.
Similar results reported by Sheoran et al. (2015) showed that high chlorophyll content and its lower reduction could be used as index to select for tolerant genotypes. They also concluded high chlorophyll a and b contents under both stress and non-stress could stabilize photosynthesis.
Plant height
Basically, plant height is a hereditary trait related to plant maturity. In this regard, late-matured genotypes mostly have higher height compared to early-matured ones (Mittler, 2006). According to the results, plant height decreased significantly under drought stress (Table 5). The CIMMYT-derived genotypes i.e 26, 27, 28, 29 and 30 had significantly lower height than other ones under both normal and stress conditions. Taller genotypes (6 and 9) had a significant reduction in height in comparison with shorter ones (29 and 34).
Table 3. Statistical significance of the source of variations in analysis of variance for RWC of 36 hexaploid wheat genotypes under non-stress (NS, 100% FC) and stress (75 and 50% FC) conditions
SOV Degree of Freedom RWC
Block 2 0.0079
Irrigation 2 2.43*
Error (a) 4 0.01930048
Genotypes 33 0.0078*
Irrigation×genotypes 66 0.0069
Error (b) 198 0.0055
Fig. 1. Relative water content (RWC) in thirty-four hexaploid wheat genotypes under normal and stress irrigation (75 and 50 % field capacity) conditions. (LSD5% = 12.1)
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These two genotypes were also shorter than sensitive ones under non-stress conditions. Genotypes 24 and 25 had lower height reduction most likely because water limitation led to food source restriction and therefore plants were forced to slow down their vegetative growth and consequently enter into reproductive phase. As a result, characters such as plant height, growth period, etc decrease.
Such a mechanism known as drought escape (Mitra, 2001) which also includes rapid phenological development (flowering and early maturity), developmental flexibility and remobilization of assimilate to grains before flowering, has a dominant effect on plant's adaptation to the environment for maximum production (Passioura, 2007).
Thousand kernel weight
Applying water stress at different levels showed a significant effect on TKW of genotypes as an important grain yield component (Table 5). Under normal condition,
the highest and lowest TKW belonged to genotypes 30 (41.83 g), 28 (44.51 g), 23 (41.65 g), 20 (46.18 g), 16 (43.08 g), 7 (43.3 g) and 15 (35.05 g), 13 (34.05 g), 12 (33.98 g), 2 (33.43 g), 9 (29.15 g), respectively. When 75% FC water stress was imposed, the genotypes 29, 23, 21, 20, 16 and 5 with 36.73, 34.5, 35.06, 37.56, 34.58 and 35.11 g had the highest TKW while genotypes 33, 32, 9, 8, 2 and 1 with 30.88, 31.13, 27.68, 29.01, 31 and 28.51 g had the lowest TKW. At 50% FC water stress, the highest and lowest amounts of TKW belonged to genotypes 34, 28, 23, 19, 6 (32.63, 31.75, 31.45, 34.38, 33.01 g) and 18, 12, 10, 1 (26.61, 25.56, 24.31, 24.3 g), respectively. TKW reduction in response to drought stress indicates that the photosynthetic materials’ supply cannot keep with the demand to fill grains under these conditions. Such patterns were also found in studies by Saini and Westgate (2000);
Dorostkar et al. (2015) and Sheoran et al. (2015) who reported significant effects of drought stress on TKW of
Table 4. Photosynthetic pigments; chlorophylls a, b and total (mg g-1 FW) for thirty-four wheat genotypes under different water deficit regimes and their corresponding LSD5% values
Genotype code
Chlorophyll a Chlorophyll b Total chlorophyll
100%FC 75% FC 50% FC 100%FC 75% FC 50% FC 100%FC 75% FC 50% FC
1 12.47 11.79 9.86 6.86 6.21 4.82 18.32 18.00 14.68
2 11.60 10.81 10.39 7.54 4.65 4.23 25.14 15.46 14.62
3 13.55 12.22 9.68 6.30 6.28 5.21 19.86 18.50 14.89
4 9.49 9.14 8.32 5.33 4.18 3.86 14.82 13.33 12.18
5 10.95 8.52 5.77 5.65 3.32 3.35 15.60 11.84 9.11
6 9.55 8.18 5.75 4.61 3.43 2.27 14.16 11.61 8.02
7 12.81 10.53 8.37 8.00 5.18 4.07 20.80 15.72 12.45
8 11.90 9.94 9.74 5.20 4.25 4.20 17.10 14.19 13.94
9 10.68 9.69 7.07 7.03 5.61 2.82 17.71 15.30 9.89
10 11.02 10.78 7.54 5.73 4.75 4.40 16.75 15.52 11.94
11 11.99 9.43 7.48 6.66 3.86 3.20 18.65 13.30 10.68
12 9.11 5.21 5.57 3.86 3.63 2.84 12.98 8.84 8.41
13 12.33 10.94 7.87 7.23 5.10 4.19 19.56 16.04 12.06
14 13.79 10.53 9.43 5.81 5.31 4.77 19.60 15.84 14.20
15 10.99 10.07 9.34 7.91 5.23 4.52 18.90 15.30 13.85
16 12.01 10.08 6.66 7.51 5.79 3.41 19.51 15.88 10.07
17 12.46 12.08 6.60 5.67 4.73 3.38 18.13 16.80 9.99
18 10.37 4.90 9.25 5.02 3.97 3.64 15.39 8.87 12.89
19 12.27 9.98 8.73 5.97 4.68 3.55 18.24 14.66 12.28
20 11.89 9.89 9.63 5.26 4.57 3.87 17.15 14.46 13.50
21 9.61 8.72 7.56 4.94 3.44 3.49 14.55 12.16 11.05
22 10.07 8.28 7.33 4.46 3.33 3.12 14.53 11.61 10.45
23 11.10 10.79 5.46 6.29 4.58 3.60 17.39 15.37 07.9
24 13.08 10.63 8.64 8.80 5.54 3.84 21.88 16.17 12.49
25 10.33 9.18 8.3 4.70 4.80 4.48 15.02 14.61 12.51
26 11.64 10.44 9.36 5.88 4.30 3.87 17.52 14.74 13.23
27 14.14 10.87 7.79 8.83 5.18 2.49 22.97 15.06 12.46
28 11.81 9.69 8.75 5.15 4.10 3.64 16.95 13.79 12.39
29 12.89 7.89 6.82 6.62 5.35 3.37 19.52 13.24 10.55
30 10.72 10.32 9.89 6.74 5.91 3.97 17.45 16.23 13.86
31 13.59 10.17 9.61 5.33 4.35 4.03 18.93 14.53 13.64
32 13.47 7.49 5.36 7.18 5.44 3.14 20.66 12.93 8.50
33 15.14 10.31 7.29 7.04 5.15 4.32 22.17 15.47 11.60
34 12.54 11.01 8.42 6.73 5.69 3.97 19.27 16.70 12.40
LSD (5%) 2.595 1.108 3.745
FW: Fresh weight, FC: field capacity, LSD: Least significant difference.
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wheat genotypes which mainly related to their sensitivity or tolerance to stress. Moreover, decreased kernel weight could be a consequence of low water supply and soluble carbohydrates and a reduction in the number of endoplast cells and amyloplasts in grain (Saini and Westgate, 2000).
It seems that under stress conditions and short supply of photosynthetic materials, the balance between source and sink is maintained through lower seed number and as a result, the remaining grains in the spike gain higher weight.
Otherwise, under these photosynthetically restricted conditions, increase in seed number will be accompanied by a reduction in seed weight and will not result in improved grain yield. González et al. (1999) also reported a lack of correlation between seed number per spike and grain yield under drought stress conditions. Similarly, it has been reported that a significant proportion of grain weight during the grain filling period is obtained from the current photosynthesis (Emam and NikNejad, 1994) and hence, decrease in moisture content reduces the current photosynthesis and as a result, seed weight decreases (Ehdaie et al., 2008).
Grain yield and yield stability
Grain yield per plant reduced significantly in all genotypes (Table 5). Under normal conditions, the highest grain yield belonged to genotypes 32 (7961 kg ha-1), 30 (8287.17 kg ha-1) and 27 (8173 kg ha-1) and the lowest grain yield related to genotypes 10 (4515.03 kg ha-1), 9 (4205.02 kg ha-1) and 4 (4873.5 kg ha-1), respectively. In 75% FC condition, genotypes 34, 33, 30 and 29 had the highest grain yield (5899.5, 6156, 6903.3 and 5765.07 kg ha-1, respectively) and genotypes 28, 16 and 9 produced the lowest yield (5595.5, 3698.67 and 3733.5 kg ha-1, respectively). In 50% FC, the highest (5148.17, 4908.33, 5283.67, 5810.83, 5333.83, 4686.67, 4080.85 kg ha-1, respectively) and lowest (3218.83, 2979.83, 2873.75 kg ha-1, respectively) grain yield belonged to genotypes 34, 33, 31, 30, 29, 18, 25, and 32, 12, 8, respectively. To achieve drought-tolerant and high yielding genotypes, simultaneous selection of yield and yield stability can be used under non- stress and stress conditions, respectively. The results of this study indicated genotypes 34 and 29 had high yield stability under 75% FC with 0.880 and 0.888, respectively and
Table 5. Average plant height (cm), TKW thousand kernel weight (g), grain yield (kg ha-1) and YSI (yield stability index) of 34 hexaploid wheat genotypes under non-stress and stress conditions
Genotype code
Plant height TKW Grain yield YSI
100% FC 75% FC 50% FC 100% FC 75% FC 50% FC 100% FC 75% FC 50% FC 75% FC 50% FC
1 87 86.3 83.6 37.88 28.51 24.3 5370.3 4112.43 3243.93 0.766 0.604
2 95.3 77 84.3 33.43 31 26.63 6504.33 4937.5 3572 0.759 0.549
3 85.6 72 68 37.6 33.61 30.48 4877.58 3808.87 3679.85 0.781 0.754
4 85 80.6 80.6 37.05 33.41 32.63 4873.5 3760.8 3274.33 0.772 0.672
5 82.6 69.3 66.6 37.75 35.11 31.23 6431.5 4243.33 3603.67 0.66 0.56
6 139 125.3 113.3 40.76 34.4 33.01 6038.83 3970.62 3863.33 0.658 0.64
7 132 127.3 129 43.3 32.91 32.83 7479.67 3990 3382.32 0.533 0.452
8 120.3 118.3 118.3 37.46 29.01 26.7 6045.17 4067.58 2873.75 0.673 0.475
9 131.6 131.3 118.3 29.15 27.68 28.56 4205.02 3733.5 3415.25 0.888 0.812
10 120 122 128 39 31.86 24.31 4515.03 4019.45 3315.32 0.89 0.734
11 153.3 139.3 133.6 37.41 32.1 28.51 6488.5 3825.33 3651.17 0.59 0.563
12 131.6 131.3 123.6 33.98 31.33 25.56 6122.75 4816.5 2979.83 0.787 0.487
13 143 127.6 124.3 34.05 31.16 27.26 6726 4041.3 4018.5 0.601 0.597
14 120.6 125.3 114.3 35.1 32.85 30.33 5131.27 3847.5 3379.17 0.75 0.659
15 122 111.3 115.3 35.05 33.35 30.41 7219.68 4173.67 3458.63 0.578 0.479
16 120.3 117 112 43.08 34.58 30.5 4939.68 3698.67 3366.17 0.749 0.681
17 123.6 120.6 108 38.55 32.91 31.13 5378.58 4006.15 3895 0.745 0.724
18 130.6 131.3 126.3 40.6 32.76 26.61 6270 5085.67 4686.67 0.811 0.747
19 116.6 111 94.3 38.68 34.23 34.38 5520.17 4240.17 3663.5 0.768 0.664
20 132.3 124.6 119.3 46.18 37.56 31.28 5041.97 3945.67 3762 0.783 0.746
21 110.3 111.3 110 38.48 35.06 27.36 6238.33 4037.5 4018.5 0.647 0.644
22 115.6 108 109.3 39.38 32.81 29.71 6499.58 3841.17 3651.17 0.591 0.562
23 94.6 91 95.6 41.65 34.5 31.45 6422.95 4819.67 3698.67 0.75 0.576
24 110 104 100 37.36 31.66 25.85 5640.5 4166 3870.33 0.721 0.727
25 95.3 91.6 91 37.76 33.83 29.1 5732.97 4491.92 4080.85 0.784 0.712
26 71.3 66.3 66.3 36.8 32.51 30.11 7239.95 3919.07 3866.5 0.541 0.534
27 81.6 83.3 77 35.56 31.35 29.81 8173 5595.5 4036.23 0.631 0.455
28 82 71 67.3 44.51 34.16 31.75 6247.52 3421.58 3255.33 0.548 0.521
29 80.6 81.3 74.6 39.5 36.73 28.88 6548.67 5765.07 5333.83 0.88 0.814
30 80.6 82 81.3 41.83 34.51 30.85 8287.17 6903.33 5810.83 0.833 0.701
31 79.3 70.3 65 36.73 32.6 30.38 6949.57 5864.67 5283.67 0.844 0.76
32 95.3 89.3 86 37.38 31.13 26.98 7961 5291.5 3218.83 0.665 0.404
33 80 87.3 83.6 35.4 30.88 27.41 7102.83 6156 4908.33 0.867 0.691
34 99 94.3 89 40.48 33.6 32.63 6640.5 5899.5 5148.17 0.888 0.775
LSD (5%) 16.194 6.726 260.856
Notes: non-stress condition: 100% FC, stress conditions: 75% FC and 50% FC.
significantly (Fig. 3). The SOD increase was higher in tolerant genotypes than in sensitive ones. The highest and lowest amounts of SOD belonged to genotypes 14, 17 and 19, 30 under normal condition, while genotypes 22, 19 and 27, 31 under 75% FC had the highest and lowest activities, respectively. The genotypes 29, 30 and 15, 28 had highest and lowest figures under 50% FC, respectively. The high activity of superoxide dismutase in genotype 29 under severe drought indicates that this genotype has high tolerance to stress which is reflected in its high yield under stress conditions with good yield stability (Table 5), possibly an indication of SOD efficiency in altering O2to H2O2. Similar results were obtained by Apel and Hertz (2004), Shao et al.
(2005), Wang et al. (2010) and Dorostkar et al. (2016) who reported that superoxide dismutase as one of the most important antioxidants had higher production in wheat drought tolerant genotypes. Since superoxide dismutase converts super-oxygen to hydrogen peroxide which is in turn removed by other antioxidants, increase in this enzyme’s activity should be accompanied with production of other antioxidants.
Likewise, peroxidase (POD) activity increased significantly under drought stress (Fig. 3). Its increase in tolerant genotypes was more pronounced than sensitive ones. Under normal condition, the genotypes 34, 33, 27 and 12 had the lowest amount of this enzyme while the highest activity belonged to genotypes 29, 22, 19 and 11. Under 75% FC, the highest and lowest levels of peroxidase belonged to genotypes 29, 19 and 10, 12, respectively. Also, under 50% FC stress conditions, the least amount was detected in sensitive genotypes; 32 and 8 and the highest was produced in genotypes 29 and 19. As mentioned earlier, POD is another key enzyme that reduces the amount of H2O2 produced in chloroplasts. Therefore, its concentration is always higher in tolerant genotypes (Asada, 1992; Sarvajeet and Narendra, 2010; Wang et al., 2010;
Pourtaghi et al., 2011). Several studies have reported that peroxidase activity increases greatly in response to water stress in wheat (Zhang and Kirkham, 1994; Khanna- Chopra and Selote, 2007). Similarly, in the industrial crop;
Nicotiana tabacum, higher peroxidase activity was shown to be associated with higher water retention (Mercado et al., 2004).
under 50% FC, 0.814 and 0.775, respectively. In addition, these genotypes showed high yield under non-stress condition and therefore, they were classified as tolerant.
Concerning this index, maintaining grain yield potential under water stress can be considered as a physiological criterion for drought tolerance. In this context, genotypes with a high percentage of grain yield reduction under stress conditions can be categorized as susceptible. Alternatively, the combination of yield under both stress and non-stress conditions can be considered as a criterion for drought tolerance (Sio-se Mardeh et al., 2006). Genotypes 34, 31, 30, 29, and 25 produced relatively high yields under both conditions of stress and non-stress (Table 5). Moreover, they had high yield stability in comparison to the others.
Genotypes 32, 12 and 8 which showed a higher yield reduction under drought stress, had lower yield stability than the others (Table 5). The negative effect of drought stress as a major problem on yield has been well documented in many studies worldwide (Passioura, 2007). However, investigating different traits including genotypes’ relative yield under stress and non-stress conditions would be a starting point to understand the drought tolerance process and choose genotypes for breeding in dry environments.
Drought susceptibility index
Relative drought tolerance, i.e. drought susceptibility index (DSI) of genotypes, was calculated based on grain yield/plant as given in Fig. 2. DSI values ranged from 0.40 to 1.71 under 75% FC and 0.30 to 0.97 under 50% FC.
Genotypes with a DSI less than 1.0 were considered as drought tolerant and those above 1.0 were regarded as drought susceptible (Guttieri et al., 2001). Based on DSI, genotypes 31, 20, 17, 10, 9 and 3 were tolerant and genotypes 26, 15, 13 and 8 were sensitive. Similarly, Dorostkar et al. (2015) reported that genotypes with DSI less than 1, produced high yield under both stress and non- stress conditions and consequently showed high yield potential. Therefore, DSI is a suitable index for selecting genotypes under stress conditions.
Antioxidant enzyme activity
In the present study, SOD activity was recorded under stress and non-stress conditions. The results showed that drought stress affected the activity of this enzyme
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Fig. 2. Drought susceptibility index (DSI) of thirty-four wheat genotypes under different levels of water deficit stress
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Proline content
Proline showed a significant increase in all genotypes under water deficit conditions compared to controls, i.e Shiraz and Bezostaya (Fig. 4). Under normal irrigation conditions, the highest amount of proline belonged to genotypes 32, 29, 27, 25, 20 and 13 and the lowest accumulation was observed in genotypes 34, 30, 22, 18, 15, 11 and 8. Under 75% FC condition, the highest and lowest proline content, belonged to 34, 31, 29, 25, 19, 13, 6 and 32, 24, 22, 21, 17, 11, 8 respectively. Under 50% FC, the proline content increased more than that of 75% FC and genotypes 34, 31, 29, 25, 24, 22, 19 and 3 had the highest while genotypes 33, 32, 18, 17, 11 and 1 had the lowest amount of proline (Fig. 4).
The data showed that proline content was higher in tolerant genotypes than susceptible ones under stress conditions (Fig. 4). Proline increase under stress conditions helps to protect cells by balancing the osmotic pressure of cytoplasm as well as the vacuoles and the surrounding environment. In addition to preserving the osmotic balance of cytoplasm, proline affects cellular macromolecules such as enzymes and leads to the stability of their structure and function (Shimshi et al., 1982). Also, genotypes with higher proline content under stress conditions produce a relatively higher yield. Some researchers believe that proline accumulation in plants under drought stress, acts as a compatible solute and serves as a source of nitrogen and carbon, while others maintain the view that proline protects the protoplasm against drought. These results are consistent with those of Pireivatloum et al. (2010) and Dorostkar et al.
(2016) who showed that drought stress increased proline accumulation significantly in different stages of growth of wheat.
Similarity of genotypes with respect to traits
The tree dendrogarm showing similarities between tested genotypes is displayed in Fig. 5. In this analysis, the highest similarity was observed between genotypes 22 and 11 with a distance of 0.0059 while the lowest similarity distance belonged to genotypes 27 and 30.
This means genotypes maintaining higher peroxidase activity in leaves under water stress may also have higher water retention and subsequently tolerate stress.
Similarly, drought stress increased catalase (CAT) activity in the studied genotypes, and this increase was more pronounced in tolerant genotypes (Fig. 3). For example, in genotype 23, CAT increased more than twice, while in genotype 32, only 30% increase was detected compared to normal irrigation conditions. Genotypes 15 and 10 had the highest and the genotypes 8 and 7 had the lowest CAT activity under non-stress condition. Genotype 29 showed the highest CAT activity under both 75% and 50% FC conditions. Environmental stresses especially abiotic ones increase the production of active oxygen species such as superoxide (O2) and hydrogen peroxide (H2O2) in plants, which leads to lipid peroxidation and cell death. Catalase is one of the enzymes plants produce when various types of O2
expose them to drought stress in order to reduce the damage caused. Antioxidant enzymes such as catalase have largely contributed to plants’ tolerance to drought stress due to the removal of free oxygen radicals (Apel and Hirt, 2004; Shao et al., 2005; Asada and Takahashi, 2006; Wang et al., 2010).
Since both catalase and peroxidase function as detoxifying H2O2, catalase activity can be compensated by increase in peroxidase activity in tolerant cultivars. Under drought stress, an increase in peroxidase activity has been earlier reported in wheat (Devi et al., 2012; Valifard et al., 2012).
Conversely, a decreased catalase activity with a simultaneous increase in peroxidase activity under heat stress has been reported in leaves and roots of creeping bentgrass (Liu and Huang, 2000).
The wheat genotypes responded differently to water stress in terms of activities of SOD, CAT and POX. SOD and POX had higher expression in tolerant genotypes than sensitive ones. This further suggests that different wheat genotypes have discrete water stress thresholds and therefore they have different physiological adaptive mechanisms to regulate their redox status (Shao et al., 2005).
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Fig. 3. Changes in the enzymatic activities (Superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT)) for thirty-four genotypes under stress and non-stress conditions in Ug-1 FW (Units g-1 fresh weight). Different letters indicate significant differences. FC stands for field capacity
Conclusions
Oxidative damage is an important factor that could decrease plant yield. Drought tolerant genotypes in current study showed higher RWC compared to controls, however, the fact that the activity of any antioxidant enzyme cycle was superior to that of the control may be indicative of cultivar stability. Our results indicated that drought tolerant wheat genotypes had higher enzymes activities and higher proline content than drought sensitive ones, protecting themselves more efficiently under drought stress. Of biochemical enzymes, superoxide dismutase had higher ability to detect tolerant and sensitive genotypes, because this enzyme had a significantly higher activity in tolerant genotypes than sensitive ones under drought stress conditions. Based on the results, the high yielding genotypes under normal, 75% FC and 50% FC conditions were 27, 30, 32 and 30, 33, 24, 29 and 18, 25, 29, 30, 31, 33, 34, respectively. In general, genotypes 24, 25, 29, 30, 31, 34 were categorized as tolerant and 7, 27, 32 ranked as sensitive due to measured indices. These tolerant genotypes, 25 (‘Akbari’), 29 (‘30ESWYT173’) and 31 (‘30ESWYT200’) are of great value for potential use in breeding programs.
Acknowledgements
The first author would like to thank the Department of Crop Production and Plant Breeding, School of Agriculture, Shiraz University for supporting him during MSc studies.
Conflict of Interest
The authors declare that there are no conflicts of interest related to this article.
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