Evaluation of Stress Tolerance Indices in Iranian Barley Genotypes under Salinity and Drought Conditions

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1 AGRICULTURAL COMMUNICATIONS, 2017, 5(3): Evaluation of Stress Tolerance Indices in Iranian Barley Genotypes under Salinity and Drought Conditions MAJID TAHERIAN, ABDOLRAHMAN RASOULNIA*, MOHAMMAD REZA BIHAMTA, ALI PEYGHAMBARI AND HUSHANG ALIZADEH Department of Agronomy and Plant Breeding, University of Tehran, Karaj, Iran. *Corresponding Author: arasoulnia@ut.ac.ir (Accepted: 2 June 2017) ABSTRACT Abiotic stresses are able to disturb growth and performance of crops. Between the mentioned, drought and salinity are two major worldwide problems, restricting universal crop production substantially. The subject of this study was to assess several selection indices with the aim of identifying the most appropriate indices/cultivars for each environment under different environmental conditions. Sixteen cultivars and promising lines of barely were planted in a randomized complete block design with three replications under three different environments (optimal, salinity stress, and end of season drought stress) during in Agricultural and Natural Research Station of Neishabour, Iran. Thirteen selection indices including abiotic tolerance index (ATI), stress susceptibility percentage index (SSPI), relative drought index (RDI), drought response index (DRI), drought resistance index (DI), yield stability index (YSI), yield index (YI), tolerance (TOL), stress susceptibility index (SSI), stress tolerance index (STI), harmonic mean (HM), geometric mean productivity (GMP), mean productivity (MP) were calculated on the basis of grain yield under non stress, moderate drought stress and sever salinity stress conditions. According to the results of the present study, STI was the merely index that could discriminate high yield cultivars in both salinity stress and non stressed condition. MP, YI, GMP, STI, and DI were more advantageous in identifying tolerant genotypes when the stress was moderate (drought stress). Also Genotypes ranking varied according to the type and severity of the stress. It is concluded that the selection indices should be chosen by breeders based on nature and severity of stress in the target environment. Keywords: Abiotic stress, Hordeum vulgare L., PCA, ranking method, selection indices, tolerance indicators, yield stability. Abbreviations: ATI: Abiotic Tolerance Index; DI: Drought Resistance Index; DRI: Drought Response Index; GMP: Geometric Mean Productivity; HM: Harmonic Mean; MP: Mean Productivity; PCA: Principal Component Analysis; RDI: Relative Drought Index; SSI: Stress Susceptibility Index; SSPI: Stress Susceptibility Percentage Index; STI: Stress Tolerance Index; TOL: Tolerance; YI: Yield Index; YP: Non Stressed Environment; YS: Stressed Environment; YSI: Yield Stability Index. INTRODUCTION Nowadays abiotic stresses are seen as the most important factors that reduce yield and crop production, and managing and/or reducing the effect of stress is considered as a useful strategy for yield increment. Salinity of soil and water resources is one of the major agricultural problems as well, particularly in arid and semi arid regions. After drought, salinity is one of the most important and most prevalent abiotic stresses throughout the world and Iran. Drought and salinity both decrease the available water for plants and have the same effect on different processes which determine the yield in different genotypes (Katerji et al., 2003). For exploiting saline soils and also growing crops in arid regions, the best way is using tolerant cultivars. For this reason, the necessity of applying appropriate criteria is indispensable for selection of genotypes (Munns et al., 2006). Different quantitative criteria are suggested for selecting genotypes based on their yield performance in favourable and stressed conditions. Rosielle and Hamblin (1981) described stress tolerance index (TOL) as the differences in yield between the stressed environment (YS) and nonstressed environment (YP), and Mean Productivity (MP) as the mean yield of YS and YP. In view of the fact that stress can be different in severity and type

2 AGRICULTURAL COMMUNICATIONS in the field environment over the years, Breeders that are keen on relative performance, often utilize Geometric mean productivity (GMP). The STI (Stress Tolerance Index), characterized by Fernandez (1992), can be employed to recognize genotypes with high yield under both stressed and non stressed conditions. Fernandez (1992) classified genotypes into four categories based on their yield performance in stressed and non stressed environments: 1. Genotypes that produce high yield under both stressed and non stressed environments (Group A) 2. Genotypes with high yield only under nonstressed environment (Group B) 3. Genotypes that have relatively good yield in stressed environment (Group C), and 4. Genotypes that perform poorly in both stressed and non stressed environments (Group D). Fischer et al. (1979) proposed another index as relative drought index (RDI). Bidinger et al. (1978) introduced drought response index (DRI) in which positive values indicate stress tolerance. Yield Stability Index (YSI) was also calculated and offered by Bouslama and Schapaugh (1984). For the supposed genotype, this parameter is calculated as the proportion of grain yield under stressed environment to its grain yield under nonstressed environment. Genotypes with high YSI are expected to have high yield in stressed environment and perform poorly under nonstressed environments (Mohammadi et al., 2010). Clark et al. (1992) used SSI for evaluating drought tolerance in wheat genotypes and found year toyear variation in SSI for genotypes and their ranking patterns. Guttieri et al. (2001) utilized SSI in spring wheat cultivars and proposed that SSI>1 showed above average susceptibility to drought stress. Lan (1998) defined a new index as drought resistance index (DRI) was defined by Lan (1998) which generally could identify genotypes with high yield under both stressed and non stressed conditions. DI and STI consider not only the ability of genotypes to grow well under stressed environments, but also good performance in nonstressed environments. Therefore, they identify compatible materials with optimal and stressed conditions for achieving ideotypes which can tolerate either long irrigation intervals or possibly non irrigation in critical growth stage (Jafari et al., 2009). Physiological traits (Na + & K + : Na + ratio) and salinity indices (SSI & STI) were good indices for screening salt tolerant cultivars and these traits are correlated with grain yield and biological yield in wheat (Goudarzi and Pakniyat, 2008). The linear regression coefficient (b) and SSI were suggested as useful indicators for barley breeding, where the stress was severe while MP, GMP and STI were suggested if the stress was moderate (Bchini et al., 2011). The MP, GMP, STI and SSI are suggested as useful indicators for wheat breeding. However under less salinity stress condition, it can be concluded that GMP and STI are able to discriminate group A (Hamam and Negim, 2014). ATI and SSPI indices can segregate relative tolerant and non tolerant genotypes (Moosavi et al., 2008). Also Ranking method has been used for screening drought tolerant cultivars by Khalili et al. (2012) in canola, Farshadfar and Elyasi (2012) and Farshadfar et al. (2012b) in bread wheat. It seems that the fitness of indices depend on on the type and the intensity of stress in stress prone environments. The subject of this study was to examine the mentioned hypothesis in order to recognize the most proper indices/barley cultivars for each environment. MATERIALS AND METHODS Plant Materials and Experimental Design: Sixteen cultivars and promising lines of barely (Hordeum vulgare L.) (Table 1) were planted in a randomized complete block design with three replications under three different environments (optimal, salinity stress, and end of season drought stress) during agricultural season of in Agricultural and Natural Research Station of Neishabour, Iran (latitude N, longitude E, altitude 1,320 m). Culture Practice: Seeding density was considered as 350 seeds per square meter for each plot. Fertilizer used before planting contained 100 kg ha 1 ammonium phosphate, 50 kg ha 1 ammonium nitrate, and in tillering stage 25 kg ha 1 ammonium nitrate. Salt stress experiment was irrigated by saline water about 11 ds m 1 before each irrigation, electrical conductivity (EC) of the soil saturation extract was measured and EC of soil was controlled about 11 ds m 1. At the drought stress experiment, the last irrigation was done when 50 % of plants of each plot were at late booting stage. After booting stage, the irrigation was done twice in normal experiment while there was no irrigation after this stage in drought stress experiment. Both normal and drought stress experiments were irrigated by water with an EC of 0.7 ds m 1. In all three experiments, harvesting area was 4 m 2 from 4 midlines and 5 m in length. Indices Calculation: Stress resistance indices were calculated by the following formulas: 1 ( Ys ) Yp (Fischer and Maurer, 1978) 1) SSI 1 ( Ys Yp) 8

3 TAHERIAN ET AL. 2) RDI ( Ys Yp) ( Ys Yp) (Fischer et al., 1979) 3 ) TOL Yp Ys (Rosielle and Hamblin, 1981) Ys Yp 4) MP 2 Ys Yp 5) STI 2 Yp 6) GMP ( Yp)( Ys) (Rosielle and Hamblin, 1981) (Fernandez, 1992) (Fernandes, 1992) 11) ( ) ( Y ATI P Yp Ys ( Yp )( YS ) Y s ( Y Y ) 2( Y P ) ) SSPI P In the above mentioned formulas, Ys, Yp, Y, S and Y are respectively the yield of each genotype P in stressed and non stressed environments and the mean yield of them in those conditions. YA, YSE, and SES are respectively the estimation of yield in stressed condition through regression, real yield in stressed condition, and the standard error of estimated grain yield of all genotypes. Table 1. Name and cods of genotypes Code Genotype Pedigree 1 Rihane Rihane 2 Rihane03 Rihane03 3 Afzal Chah Afzal 4 Fajr30 Lignee131/Gerbel//Alger Jonoob 5 Kavir Arivat 6 MBS82 4 LB.Iran/una8271//Gloria s/come s/ 3/Kavir 7 MBS M MBS87 12 Roho/Mazorka//Trompi 9 MBS87 15 Afzal/Lignee MBS87 19 CWB /Rojo2 11 Valfajr CI Bahman CWB Yusef 14 Makooyi Star 15 Nik Lignee527/NK1272//JLB Nosrat Karoon/Kavir S Ys 7)YI Ys (Guvuzzi et al., 1997) Ys 8)YSI Yp (Bouslama and Schapaugh, 1984) 9) DRI ( YA YES ) ( S ES ) (Bidinger et al., 1978) 10) DI YS ( YS YP ) YS (Lan, 1998) (Moosavi et al., 2008) (Moosavi et al., 2008) Statistical Analyses: For screening stress tolerant genotypes, mean rank and standard deviation of rank for each genotype were calculated in all environments. Correlation analysis and principal component analysis (PCA) were performed based on rank correlation matrix and biplot analysis using SPSS ver. 16 and STATISTICA ver. 8. RESULTS AND DISCUSSION Stress Tolerance Indices: Data concerning yield and tolerance indices are presented in tables 3 and 4. The estimates of stress tolerance indices (Tables 3 and 4) show that the recognition of tolerant genotypes only based on a single criterion may have inconsistent result with other indicators. For instance, according to STI, GMP, and MP in salinity stress experiment, Rihan03 and Nosrat cultivars; and in drought stress experiment Fajr30, Rihan03, and Yusef were the most relative tolerant. The lowest values of mentioned indices were related to Bahman and Makooei cultivars in salinity stress experiment and in drought stress were related to Afzal and MBS For TOL and SSI indices, the most favourable genotypes in both salinity and drought stress experiments were MBS87 15 and MBS82 5. Table 2. Chemical and physical properties of farm soil (0 to 30 cm) Year ph Electrical Conductivity (ds m 1 ) Sand Silt Clay Potassium (ppm) Phosphor (ppm) Nitrogen (%) Carbon Organic (%) Regarding the YI index, the best cultivars were Rihan and MBS82 4 in salinity stress experiment and Fajr30 and Yusef in drought experiment. Nonetheless, Bahman and Fajr30 under salinity stress and MBS87 12 and MBS87 15 were considered unfavourable for this index. Based on YSI, RDI, SSPI, and ATI indices under both salinity and drought stress conditions, MBS87 15 and MBS82 5 were identified as tolerant, whereas Fajr30 under salinity stress and MBS87 19 under drought condition were as sensitive genotypes. RDI index indicated Rihan and MBS82 5 under salinity stress and MBS82 5 and MBS87 15 under 9

4 AGRICULTURAL COMMUNICATIONS drought stress as the best, while Bahman and Afzal cultivars under salinity stress and MBS87 19 and MBS87 12 under drought stress as the worst relatively tolerant genotypes. According to DI index and under salinity stress, the most desirable genotypes were MBS87 15 and Rihan cultivars, under drought stress they were Yusef and Fajr30, while Bahman and Fajr30 under salinity stress and MBS87 12 and MBS87 19 under drought stress were identified the most sensitive genotypes. In a study, Farshadfar et al. (2012) used 15 stress tolerance indices for screening thirty bread wheat landraces under drought stress condition. Their findings were consistent with the results of our study. Majid et al. (2011) also noted that GMP, STI, and HM indices can similarly separate tolerant and susceptible safflower genotypes in both severe and mild drought stress. Pireivatlou et al. (2010) also have reported that STI can be considered as a reliable index for selecting high yielding genotypes. Table 3. Tolerance indices and their Ranks (R) under sever salinity stressed and non stressed conditions. Genotypes Yp R Ys R MP R GMP R HARM R TOL R STI R SSI R Table 4 (Continue). Tolerance indices and their Ranks (R) under sever salinity stressed and non stressed conditions. Genotypes YI R YSI R DRI R RDI R DI R SSPI R ATI R Correlation Analysis: The yield correlation under salinity condition was negative and insignificant with that of normal condition (Table 5). Yield under salinity stress (YS) was positively and significantly correlated with YI, STI, HM, GMP, DI, RDI, DRI, and YSI. Under salinity stress, YP had a positive and meaningful correlation with DI, YI, STI, HM, GMP, and MP. Accordingly, STI was the merely index that was positively and significantly correlated with grain yield in both salinity stress and non stressed condition. In drought stress experiment, there was a positive and highly significant correlation among DI, YI, STI, HM, GMP, and MP. Also YP had a positive and highly significant correlation with DI, YI, STI, ATI, HM, GMP, and MP (Table 6). 10

5 TAHERIAN ET AL. Table 5. Tolerance indices and their Ranks (R) under moderate drought stressed and non stressed conditions. Genotypes Yp R Ys R MP R GMP R HARM R TOL R STI R SSI R Table 4 (Continue). Tolerance indices and their Ranks (R) under moderate drought stressed and non stressed conditions. Genotypes YI R YSI R DRI R RDI R DI R SSPI R ATI R Based on both conditions of end of season drought stress and non stress, we can consider DI, YI, STI, HM, GMP, and MP as the most appropriate stress tolerance indices. In end ofseason drought stress condition, regarding the severe correlation of grain yield in both drought stress and non stress conditions (r = 0.908**) it was specified that indirect selection based on the yield of optimal conditions can make high yielding genotypes with favourable yield stability for a drought prone environment. Majid et al. (2011) stated that the results of both mild and severe stress experiments showed a positive and significant correlation between YP with MP, TOL, SSI, STI, HM, and GMP indices. They also reported that there is a positive and meaningful correlation between YS and GMP, HM, and STI indices, therefore selection based of these indices can increase yield in stressed and non stressed conditions. Pourdad et al. (2008) notified that STI was the best index for distinguishing superior Safflower genotypes in drought stress and nonstressed conditions. A number of researchers concluded that selection is more effective when the experiments is implemented under both optimal and stress conditions (Rajaram and Van Grinkle, 2001). Screening Genotypes and Stress Tolerance Indices: 1. Principal Component Analysis The relationships among different indicators of stress tolerance were graphically shown in a biplot based on principal component analysis (PCA) (Figures 1 and 2). In salinity stress condition, two first PCA explained % variation among criteria. The PCA1 and PCA2 divided criteria into different groups. A remarkable construal of biplot is that the cosine of the angle between two vectors 11

6 AGRICULTURAL COMMUNICATIONS represents an approximation of the correlation coefficient between them. Cosine of the angles is not the exact interpretation of correlation coefficients, for this reason a biplot does not clarify all existing variation in a set of data. Though, the angles are helpful from this aspect that can offer an outline about the relations among criteria (Yan and Kang 2003). Fig. 1. Biplot analysis of salinity tolerance criteria. Fig. 2. Biplot analysis of drought tolerance criteria. In salinity stress environment, SSI, TOL, SSPI, ATI, and YP were put in group1 (G1). PCs axes segregated MP, GMP, HM, STI, and DRI in a distinct group (G2) and YSI, YI, RDI, DI, and YS indices in another group (G3). Under drought stress condition, the first and second components gave explanation for % variation among indicators. Biplot of drought stress partitioned criteria in three groups. TOL, SSPI, ATI, and SSI located in the first group. Second group included MP, YS, YI, YP, GMP, HM, STI, and DI, and YSI, DRI, RDI put in the third group. Using the biplot of genotypes, (Figure 3) under salinity stress, genotypes 1,6,5,8, and 7 were detected as tolerant and genotypes 13 and 14 as susceptible to salinity. Under drought stress and by using biplot of genotypes (Figure 4), genotypes 15, 16, 13, and 2 were identified as drought tolerant and genotypes 10, 8, 11, 12 and 14 as sensitive to drought. As for the positive correlation between TOL and YP and negative correlation between TOL and YS put forwarded that selection based on TOL will result in reduced yield under non stress conditions. Rizza et al. (2004) have shown that a selection based on minimum yield decrease under stress, as regards favourable conditions (TOL), causes the loss of identifying the best genotypes. In the present study, yields in well watered conditions were much higher than in salinity stress. For the reason that MP is mean production under both stress and non stress environments (Rosielle and Hamblin, 1981), this index was not correlated with yield under severe salinity stress (Table 5). That s why; MP could not separate cultivars belonging to group A from other groups. As Hohls (2001) expressed, selection for MP must boost yield in both stressed and optimal conditions unless the correlation between yields in compared conditions is severely negative. This situation was observed in our salinity experiment. For example cultivars 2, 16, 4, and 13 with a relatively low yield under stressed condition showed high values of MP. MP can only be correlated with yield under stress when stress is not so severe and there is little difference between yield under stress and non stress conditions. This case was observed in our study (Table 6). genotypes with a high MP in such conditions belong to group A. MP was applied by Hossain et al. (1990) as an index of resistance for wheat cultivars in mild stress conditions. GMP is more potent than MP in separating group A and less susceptible to different values of YS and YP. A high GMP value indicates a great relative tolerance. SSI was negatively correlated with yield under salinity stress. Cultivars 9, 7, and 6 which had relatively high yields in salinity stress generated low yields under non stress condition. There was no significant correlation between yield under mild drought stress and SSI which shows that SSI is not able to separate susceptible cultivars to drought in such circumstances. YI suggested by Gavuzzi et al. (1997) demonstrated significant correlation with yield under salinity and drought stress; this criterion orders cultivars only based on their yield under 12

7 TAHERIAN ET AL. stress (Tables 5 and 6) and therefore it cannot separate genotypes of group A. Fig. 3. Biplot of first and second components for indices of salinity tolerance. Fig. 4. Biplot of first and second components for indices of drought tolerance. Table 6. Correlation coefficients among sever salinity tolerance indices. YP YS MP GMP HM TOL STI YP 1 YS ns 1 MP 0.766** ns 1 GMP ns 0.603* 0.935** 1 HM ns 0.815** 0.77** 0.95** 1 TOL 0.898** 0.757** ns ns ns 1 STI 0.516* 0.578* 0.942** 0.998** 0.94** 0.09 ns 1 SSI 0.796** 0.857** ns 0.11 ns ns 0.975** ns YI ns 1** ns ns 0.815** 0.757** 0.58* YSI 0.796** 0.856** ns 0.11 ns ns 0.975** 0.08 ns DRI ns 0.830** 0.581* 0.784** 0.879** ns 0.769** RDI 0.796** 0.856** ns ns ns 0.975** ns DI 0.697** 0.922** 0.08 ns ns 0.527* 0.925** ns SSPI 0.898** 0.757** ns ns ns 1** 0.09 ns ATI 0.965** 0.614** 0.575** ns ns 0.979** ns 13

8 AGRICULTURAL COMMUNICATIONS Table 7 (Continue). Correlation coefficients among sever salinity tolerance indices. SSI YI YSI DRI RDI DI SSPI ATI SSI 1 YI 0.857** 1 YSI 1** 0.857** 1 DRI 0.524* 0.83** 0.524* 1 RDI 1** 0.857** 1** 0.524* 1 DI 0.986** 0.922** 0.985** 0.634** 0.985** 1 SSPI 0.975** 0.757** 0.975** ns 0.975** 0.935** 1 ATI 0.917** 0.614* 0.917** ns 0.917** 0.854* 0.979** 1 Table 8. Correlation coefficients among moderate drought tolerance indices. YP YS MP GMP HM TOL STI YP 1 YS 0.908** 1 MP 0.98** 0.974** 1 GMP 0.975** 0.979** 0.999** 1 HM 0.969** 0.983** 0.998** 0.999** 1 TOL ns ns ns 0269 ns ns 1 STI 0.972** 0.979** 0.998** 0.998** 0.998** ns 1 SSI ns ns ns ns ns 0.94** ns YI 0.908* 1** 0.974** 0.978** 0.983** ns 0.979** YSI ns ns ns ns ns 0.94** ns DRI ns 0.39 ns ns ns ns ns ns RDI ns ns ns ns ns 0.94** ns DI 0.726** 0.947** 0.849** 0.861* 0.872** ns 0.864** SSPI ns ns ns ns ns 1** ns ATI 0.755** ns 0.609* 0.59* 0.572* 0.931** 0.587* Table 9 (Continue). Correlation coefficients among moderate drought tolerance indices. SSI YI YSI DRI RDI DI SSPI ATI SSI 1 YI ns 1 YSI 1** ns 1 DRI ns 0.39 ns 0.913** 1 RDI 1** ns 1** 0.913** 1 DI 0.562* 0.947** 0.562* 0.641** 0.562* 1 SSPI 0.94** ns 0.94** 0.817** 0.94** ns 1 ATI 0.753** ns 0.753** 0.61* 0.753** 0.1 ns 0.931** 1 YSI should be an index of resistant genetic materials in other that it assesses stress yield of a genotype relative to its non stress yield. Therefore it is expected that genotypes with a high YSI have high yield under both stress and non stress conditions. Nevertheless, in this study, genotypes that had the highest YSI showed the lowest yield in non stress situation and the highest yield in salinity stress (Table 3). The higher STI, the higher tolerance, and that STI can separate group A from other groups is the best advantage. ATI and SSPI indicators exhibit the relative tolerance of a genotype against stress. The nature of these two is so that they are dependent on the mechanisms of crop survival in stress situations. However these genotypes could have high or low yield in both conditions, they did not show a significant correlation with YS but showed a meaningful correlation with YP. Indeed this reflects relative stability of yield with altering conditions and the smaller ATI and SSPI demonstrates higher relative tolerance of the crop. However ATI and SSPI select group C and both of them have significant correlation with each other, but ATI has a more emphasis on YP in comparison with SSPI, SSI, and TOL (Tables of 5 and 6). Genotypes are remarkably selected by ATI or SSPI based on yield stability. 2. Ranking Method In order to identify favourable tolerant genotype on the basis of all indices, mean rank and standard deviation of ranks of all tolerance stress indicators in both drought and salinity experiments were computed. Taking into consideration all indices, genotypes 1, 6, 5, 8, and 11 were the most tolerant genotypes to salinity 14

9 TAHERIAN ET AL. (Figure 5) and genotypes 13, 15, 16, 1, and 5 were the most tolerant to drought (Figure 6). Whereas the most sensitive cultivars to salinity belonged to genotypes 13 and 14 and genotypes 9, 3, and 10 were the most sensitive to drought (Figures 5 and 6). Drought tolerance in plants mainly occurs through osmotic adjustment. While salinity stress is performed through osmotic and ion balance adjustments, therefore it could be concluded that genotypes 1 and 5 which exhibited good tolerance in salinity and drought conditions, utilized both mechanisms simultaneously in an optimal way. Genotype 13 which was tolerant to drought was one of the most sensitive cultivars to salinity; this might be for this reason that ion balance adjustment is weak in this cultivar. Ranking method has been used for screening drought tolerant cultivars by Khalili et al. (2012) in canola, Farshadfar and Elyasi (2012) and Farshadfar et al. (2012) in bread wheat. Fig. 5. Ranking of genotypes according to all indices means and standard deviations of ranks of all salinity tolerance criteria. CONCLUSION In the present study, Yp was independent of YS in (severe) salinity stress but it was correlated with YS under mild drought condition. Blum (1996) and Panthuwan et al. (2002) believe that YP has great effect just on yield under moderate drought condition and if the stress is severe enough, it induces genotype environment (G E) interaction for yield. Whether direct or indirect selection is better, it depends on heritability of the selected trait in stress and non stress environments and genetic correlation between those environments (Nasir Ud Din et al., 1992). Provided the strategy of breeding program is to improve yield in a small stressed or non stressed environment, local adaptability is feasible through direct selection in that environment (Hohls, 2001). Though, when the breeder is searching about adaptable cultivars to an extensive range of environments, it is recommended that selection be based on the resistance criteria computed from yield under both conditions. Our findings in this study indicated that the indices should be selected by breeders based on nature and severity of stress in the target environment. In salinity stress condition, just STI could discriminate high yield cultivars in both conditions. MP, YI, GMP, STI, and DI were more advantageous in identifying tolerant genotypes when the stress was moderate (drought stress). Genotypes ranking varied according to the type and severity of the stress. Genotypes 1 and 5 were tolerant under both drought and salinity stress conditions. Genotype 13 was tolerant to end of season drought stress, but sensitive under salinity stress. This demonstrates that drought and salinity tolerance in a genotype can be controlled by different stress response pathways, in a way that in cultivars 1 and 5, possibly both osmotic adjustment and ion balance mechanisms are active while in genotype 13 only osmotic adjustment mechanism is the most dynamic. Therefore, stress tolerance mechanisms can vary in different genotypes and conditions. Fig. 6. Ranking of genotypes according to the all indices means and standard deviations of ranks of all drought tolerance criteria. 15

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