Analysis of Tolerance Indices in Some Rice (Oryza sativa L.) Genotypes at Salt Stress Condition

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1 International Research Journal of Applied and Basic Sciences. Vol., 3 (1), 1-10, 2012 Available online at irjabs.com ISSN X 2012 Analysis of Tolerance Indices in Some Rice (Oryza sativa L.) Genotypes at Salt Stress Condition Seyyed Jaber Hosseini 1, Zeiniolabedin Tahmasebi Sarvestani 1 & Hemmatollah Pirdashti 2 1 Department of Agronomy, Tarbiat Modares University, Tehran, Iran, 2 Agronomy and Plant Breeding Department, Genetics and Agricultural Biotechnology Institute of Tabarestan, Sari Agricultural Science and Natural Resources University, Sari, Iran. Corresponding Author: Z. Tahmasebi Sarvestani, Department of Agronomy, Tarbiat Modares University, Tehran, Iran. Tahmaseb@modares.ac.ir ABSTRACT: Rice improvement for salt tolerance requires reliable assessment of salt tolerance variability among segregation genotypes. Sixty five genotypes of rice (traditional, improved and promising lines grown in north of Iran conditions) were evaluated under salt condition containing 0, 3, 6 and 8 ds/m levels during Five salt tolerance indices comprising: stress tolerances (TOL), mean productivity (MP), geometric mean productivity (GMP), stress tolerance index (STI) and stress susceptibility index (SSI) were used. The indices were adjusted based on shoot length and root dry weight under normal and salt conditions. Analysis of variance for shoot length and root dry weight showed that there was a significant genetic variation among genotypes. Cluster analysis of genotypes using Ys, Yp and five other indices categorized genotypes into five groups for both shoot length and root dry weight. Results of cluster analysis distinguished tolerance and susceptible genotypes. It was concluded that the potential of these genotypes to tolerate salt stress was found to high MP, STI and low SSI for both shoot length and root dry weight. Also, based on broad-sense heritability Ys, TOL and MP for shoot length and Ys, TOL and STI for root dry weight can be used as the best indices for breeding program. Also, by cluster analysis based on tolerant indices, all genotypes were segregated into 4 and 3 groups based on both Yp, Ys, MP, GMP and STI and TOL or SSI, respectively. Therefore, genotypes such as IR56, Yosen, 8803, IR58, R3, 8802 and 8810 as tolerant and Abji Boji, IR30, Amol 2, Neda and 8805 as susceptible can be used in breeding programs. Keywords: breeding program, cluster analysis, heritability, mean productivity, root dry weight Introduction Crop production is severely affected by high salinity (sodium chloride, NaCl) of soil and irrigation water worldwide (Maibody & Feizi, 2005; Demiral & Turkan, 2005). Several rice-growing countries, both intropics and in temperate regions, are facing high soil salinity as a major problem. Also,salinity is even more severe in arid, semiarid, and coastal rice-producing areasof the tropics (Lee et al., 2003). Despite the advances in the increase of plant productivity and resistanceto a number of pests and diseases, improvement in salt tolerance of crop plants remains elusive, largely due to the fact that salinity is a complex trait which affects almost every aspect of the physiology and biochemistry of plants (Borsani et al., 2003; Cuartero et al., 2006). Furthermore, salinity tolerance is critical during the life cycle of crop species. It has been shown that crops that are tolerant at seedling stage also show improved salinity tolerance at the adult stage (Shannon et al., 1998; Rao & McNeilly, 1999; Soloviev et al., 2003; Khan et al., 2003). Since screening is considered as an essential part of the breeding programs, several screening and selection schemes have been proposed for salt tolerance improvement in wheat and other crops (Dewey, 1962; Kingsbury & Epstein, 1984, Kelman & Qualset, 1991; Karadimova & Djambova, 1993; Pecetti & Gorham,

2 1997). Also, selection for improved salt tolerance based on seedling stage has been used in various crop species, for example in rice (Shannon et al, 1998), maize (Rao & McNeilly, 1999), wheat (Qureshi et al., 1990; Khan et al., 2003), and tomato (Soloviev et al., 2003). Additionally, selection for salinity tolerance based on seedling response has some variation at this stage which is genetically controlled (Maiti et al., 1996). For enhancing salt tolerance in crop plants, however, it is very essential to find sufficient variation and to devise such screening techniques which are reliable to recognize tolerant genotypes. Variation for salt tolerance has been reported in many crop species, both between and within plant species, including tomato (Saranga et al., 1992; Akinci et al., 2004; Shaaban et al., 2004), wheat (Haq et al., 2003; Sarwar et al., 2003), rice (Alam et al., 2004), cotton (Noor et al., 2001) and other crop plants. Furthermore, selection based on tolerance indices suggested by many researchers such as Golabadi et al., (2006), Mardeh et al., (2006), Fernandez, (1992), Ramirez & Kelly, (1998) and Rosielle & Hamblin, (1981). Some researchers supposed in selection under favorable condition (Richards, 1996; Rajaram & Van Ginkle, 2001; Betran et al., 2003). Selection by the aim of stress condition has been highly suggested too (Ceccarelli, 1987; Ceccarelli & Grando, 1991; Rathjen, 1994). A number of researchers have preferred the mid-way and believe in selection under both favorable and stress conditions (Fischer & Maurer, 1978; Clarke et al., 1992; Nasir Ud-Din et al., 1992; Fernandez, 1992; Byrne et al., 1995; Rajaram & Van Ginkle, 2001). To discriminate tolerant genotypes, several selection indices have been suggested on the basis of a mathematical relationship between stress and non-stress conditions (Clarke et al., 1984; Huang, 2000). Tolerance (TOL) (McCaig & Clarke, 1982; Clarke et al., 1992), mean productivity (MP) (McCaig & Clarke, 1982), stress susceptibility index (SSI) (Fischer & Maurer, 1978), geometric mean productivity (GMP) and stress tolerance index (STI) (Fernandez, 1992) have all been employed under diverse conditions. Fischer & Maurer (1978) explained that genotypes with an SSI of less than a unit are tolerant, since their yield reduction in stress condition is smaller than the mean yield decrease of all genotypes (Bruckner & Frohberg, 1987). Since researches suggested that improvement in salt tolerance in different plant species would be possible through selection and breeding, therefore, the intention of the present study was to generate information on the genetic variability for salinity tolerance based on tolerance indices at the early seedling stage in rice genotypes mainly grown under north of Iran conditions. Material and Methods The experiment was designed to examine a range of genetic variability for salinity tolerance among rice (Oryza sativa L.) genotypes, and to estimate the seedling growth performance. Seeds of all genotypes were provided by Rice and Citrus research Institute and Rice Research Institutes of Iran, Deputy of Mazandaran (Amol) and all of them were stored under normal conditions. Sixty five rice genotypes with representing susceptible (IR29), semi susceptible (IR64) and salt tolerate (Pokkali) were used (Table 1). These genotypes exposed to four NaCl treatments in three replicates. Thus, the whole experiment comprised 780 Petri dishes arranged in a completely randomized design. The seeds were surface sterilized in a 1:10 (v/v) dilution of commercial hypochlorite and rinsed several times with distilled water. Then 50 uniformly seeds of each varieties were allowed to four levels of NaCl solution (0, 3, 6 and 8 ds/m) for 36 h at 25 C. After priming, seeds from each treatments placed on 9 cm-diameter Petri dishes on Whatman filter paper that was moisten with 10 ml distilled water, then Petri dishes kept at 25 C with 12 h photoperiod in a germinator (Iran Khodsaz, IKHRH, IRAN) for germination until seven days. After seven days ten seedling were selected and root length, shoot length, root fresh weight and shoot fresh weight were measured. Also, root and shoot dry weights (10 seedlings) were recorded after oven drying at 70 C for 72 h. Estimation of heritability (H 2 ) for salinity tolerance The root and shoot length, root and shoot dry weight, fresh root and shoot weight data of 30 seedlings (10 from each replicates) of the 65 genotypes assessed under each NaCl concentration and control and then analyzed by partitioning total variances into two components, i.e. variance between accessions and variance within accessions. The variance due to between-accessions and that due to within-accessions were used to calculate broad-sense heritability using the formula given by Falconer and Mackay (1996).

3 H 2 B = Vg / Vp Where, (Vg) genetic variance= (variance between-genotypes variance within-genotypes)/ n (Vp) phenotypic variance= [(variance between-genotypes variance within-genotypes)/n] + variance withingenotypes. n =Number of replicates per treatment Salt tolerance indices Salt tolerance indices were calculated using the following relationships: TOL (Hossain et al., 1990) Mp (Hossain et al., 1990) GMP (Fernandez, 1992) STI (Fernandez, 1992) SSI (Fischer and Maurer, 1978) Where is the yield of cultivar under stress, the yield of cultivar under salt condition, and the mean yield of all cultivars under stress and non stress conditions, respectively, and stress intensity. is the Statistical analysis Data were analyzed using SPSS 11 for the analysis of variance and Duncans multiple range tests value was employed for the mean comparison between groups. Results The results of ANOVA for salt tolerance showed significant differences (P0.01) among genotypes for root and shoot length, root and shoot dry weight and root and shoot fresh weigh (data not shown). Then, selection for salinity tolerance based on broad-sense heritability showed that the shoot length and root dry weight at high salinity (8 ds/m) were the best criteria in breeding program (Table 2). Afterwards, results from variance analysis of tolerance indices were adjusted based on shoot length and root dry weight under normal and salt conditions. Findings showed that there was a significant genetic variation among genotypes for both traits (Table 3). Cluster analysis of genotypes based on shoot length and root dry weight categorized genotypes into five groups for both traits on the basis of Yp, Ys, TOL, MP, GMP,STI and SSI indices, respectively (Table 4). In shoot length, first group had the highest amount of Yp, Ys, GMP and STI, and it was hence known one of the most desirable cluster. Furthermore, group 5 had smaller value in all indices, while the TOL was lower than in group number 2. Therefore, the genotypes of group number 1 are suitable only for stress condition. Group 3, 4 and 5 had low shoot length potential under non- stress condition. Group number 1 had high amount of shoot length under stress condition and ranked as the first best group. Additionally, the genotypes of this group are suitable for stress and non- stress conditions. Also, selection of genotypes in groups 3 and 4 with high SSI indices would not appropriate, but can be used in breeding program aiming at high STI and GPM. Also, on the basis of root dry weight, group number 2 had the highest amount of TOL, MP, GMP and STI, respectively (Table 5). Also in group number 3, only parameter Yp was high and it may hence conclude that there was not any salt tolerance mechanism in these genotypes. The other groups (4 and 5) were not suitable for any conditions and they have the least amount of the suited criteria. In general, salt stress condition was well suited for selecting superior genotypes for salt tolerance while normal condition was relatively suited for selecting well genotypes which adapted to non- stress condition in this genotypes. By the results obtained from correlation analysis based on Yp, Ys and tolerance indices based on shoot length, a positive and significant correlation were found between Ys with GMP (r=0.89 ** ) and STI (r=0.89 ** ). By contrast a significant and negative correlation was observed between Ys and SSI (r=-0.91 ** ). Furthermore,

4 correlation results based on root dry weight indicated a positive and significant correlation between Ys with GMP (r=0.89 ** ) and STI (r=0.89 ** ) (Table 6). By contrast, a significant and negative correlation were observed between Ys with SSI (r=-0.91 ** ) and TOL (r=-0.23 ** ). Heritability (H 2 ) estimated for salt tolerance Estimated broad-sense heritability based on shoot length showed Yp (99), TOL (99), MP (97) and SSI (97) had the highest amount in all H 2, respectively (Table 7). Additionally, TOL (99), STI (96) and SSI (95) obtained highest amount of H 2 from indices of root dry weight, respectively. Analysis of principal component Principal component analysis revealed that the first component explained % of the variation with Ys, MP, GMP and STI in shoot length (Table 8). Also, in root dry weight YP, Ys, MP, GMP and STI obtained % of variation by first principal component analysis. Thus, the first component can be named as the effective salt tolerant factors. The second component explained with high value of SSI (0.635). Therefore the first component can separates the stress-tolerant genotypes from non stress-tolerant. Accordingly, selection of genotypes that have high first component and low second component are suitable. Overlay, by cluster analysis of genotypes based on Yp, Ys, MP, GMP and STI, genotypes segregated into four groups (table 9). Thus, group number 1 were demonstrated as high tolerant, group number 2 as tolerant, group number 3 as susceptible and group number 4 as high susceptible, respectively. Also, cluster analysis based on TOL and SSI categorized genotypes into three groups. Therefore, group number 1 was distinguished as susceptible, group number 2 as semi susceptible and group number 3 as tolerant, respectively. Furthermore, biplot graph exhibited that GMP, STI, MP and Yp indices were the best indices among all evaluated indices (Fig. 1). Discussion Reduction in genetic variability under stress, which has been reported previously in wheat (Singh and Chatrath, 1992; Ashraf, 1994; Ali et al., 2007), tomato (Saeed et al., 2010) and sorghum (Azhar and McNeilly, 1989), suggests rigorous and careful selection of salt tolerant genotypes. Also, the heritability values in a broad-sense are useful as first approximation but not as definitive values for the improvement of salinity tolerance (Ali et al., 2007). Selection for salinity tolerance based on seedling response has recommended that the variation at this stage is genetically controlled (Maiti et al., 1996). It had been suggested that high salinity tolerance are correlated with high MP, GMP and STI (Clarke et al., 1984; Winter et al., 1988; Golabadi et al., 2006; Mardeh et al., 2006). Cluster analysis of genotypes based on shoot length and root dry weight categorized genotypes into five groups for both traits. Golabadi et al., (2006) divided 151 genotypes into six groups by the cluster analysis. Each groups obtained high values of some indices that have been the same opinion with our findings. In addition, similar consequences obtained in the study of Houshmand et al., (2005) and they could recognize genotypes that performed superior under both sanity stress and non-stress conditions. Principal component analysis revealed that the first component explained high amount of variation of Ys, MP and GMP and low amount of SSI for both shoot length and root dry weight. Golabadi et al (2006) observed analogous results, as well. Kaya et al., (2002) were able to reveal that genotypes with larger first principal component and lower second principal component values gave high yields and genotypes with lower first principal component and larger second principal component values had low yields that agreed with our findings. Farshadfar & sutka (2003) suggested that PAC1 explained 66% of variation. This PAC1 was associated to yield positional and stress tolerant. Fernandez (1992) declared among the stress tolerance indicators, a superior rate of TOL and SSI represent relatively more sensitivity to stress, thus a smaller rate of TOL and SSI are favored. Selection based on these tow criteria favors genotypes with low yield potential under non-stress conditions and high yield under stress conditions. On the other hand, selection based on STI and GMP will be resulted in genotypes with higher stress tolerance and yield potential will be selected. Thomas et al., (1996) observed that some of 25 accession of meadow fescue from seven countries that investigated in four experiments could be distinguished based on cluster analysis. Kaya et al., (2002) were able to reveal that genotypes with larger first principal component and lower second principal component scores gave high yields (stable genotypes), and genotypes with lower PCA1 and larger PCA2 scores had low yields (unstable genotypes).

5 Although the studies were based on seedling stage, the same results by Al-Khatib et al., (1993), Maiti et al., (1996) and Salam et al., (1999) supports that there is a positive correlation between seedling performance and adult plant performance. So, it is concluded that genotypes such as IR56, Yosen, 8803, IR58, R3, 8802 and 8810 as tolerant and Abji Boji, IR30, Amol 2, Neda and 8805 as susceptible can be used in breeding programs. Conclusion Biplot graph exhibited that GMP, STI, MP and Yp indices were the best indices among all evaluated indices. Thus, we can predict tolerant genotypes based on Yp, MP, STI and GMP indices. Also, broad-sense heritability and the results of cluster analysis can be used for selecting the tolerant rice genotypes. Overall, we can use these methods and indices for improving rice cultivars to salt stress condition in future breeding programs. Acknowledgements We are very thankful the Genetics and Agricultural Biotechnology Institute of Tabarestan (GABIT) and Rice Research Institute of Iran, Deputy of Mazandaran (Amol) for providing the rice genotypes seeds. Table 1. Number and the name of the genotypes that used in these experiments N. * genotypes N. genotypes N. genotypes N. genotypes Nnajing Pus-ABA Khazar Anbar Bou 36 Neda 53 Sepid Roud 3 Mir 20 Mosa Tarom 37 Ghaem 2 54 IR 3 4 IR R 1 55 Gasmin 5 IR IR R 2 56 IR Salari 40 R 3 57 Abji Boji 7 IR Tetep 58 Shah Pasand 8 Ghaem 1 25 Pokkali Sange Tarom R 9 Nemat 26 IR IR IR Shirodi 27 Pus-ABA-1 44 Gerdeh 61 Foji Minori 11 Sange Tarom 28 Tarom mahhali 45 IR Hasan Sarayi 12 Amol IR IR 2 13 IR Kadous 47 Ghaem 3 64 Yosen 14 Sadri IR Dollar 15 IR 8 32 Gharib 49 Fajr Cp Amol 3 17 Rashti Ahlami Tarom * as number of genotypes

6 Table 2. Estimates of broad-sense heritability of NaCl tolerance in control and three NaCl concentrations at seedling stage based on 6 traits. Character control 3 ds/m 6 ds/m 8 ds/m broad-sense heritability (%) Root length Shoot length Root dry weight Shoot dry weight Root fresh weight Shoot fresh weight Table 3. Analysis of variance for Yp, Ys and salt tolerance indices in rice genotypes. Mean Square trait S O V df Yp Ys MP GMP TOL SSI STI Genotypes ** ** ** ** ** ** ** Shoot length Error Root dry weight Genotypes ** ** ** ** ** ** 0.01 ** Error Table 4. Mean values of groups in cluster analysis for both shoot length and root dry weight. Traits Index Group 1 Group 2 Group 3 Group 4 Group 5 Shoot legth Yp ** a a b b b Ys ** a b bc bc c TOL ** b c b a b MP ** b b b a b GMP ** a b a a b STI ** a b a a b SSI ** b b a a b Root dry weight Yp ** d e a c b Ys ** c b d a e TOL ** c a b e d MP ** b a c e d GMP ** b a d c e STI ** b a d c e SSI ** d c e a b Table 5. Correlation coefficient between Yp, Ys and salt tolerance indices of some rice genotypes based on shoot length Shoot length Yp Ys TOL MP GMP STI SSI Yp 1 Ys TOL -0.25* MP 0.91** GMP ** ** 1 STI 0.24* 0.89** ** 0.99** 1 SSI 0.54** -0.91** ** -0.62** 1

7 Table 6. Correlation coefficient between Yp, Ys and salt tolerance indices of some rice genotypes based on root dry weight Root dry weight Yp Ys TOL MP GMP STI SSI Yp 1 Ys 0.15* 1 TOL -0.31** -0.23** 1 MP 0.94** 0.46** -0.35** 1 GMP 0.58** 0.89** -0.33** 0.80** 1 STI 0.56** 0.89** -0.30** 0.79** 0.99** 1 SSI 0.39** -0.83** ** -0.51** 1 Table 7. Estimates of broad-sense heritability of NaCl tolerance based on tolerant indices at seedling stage Shoot length Vt Ve Vg Vp H 2 B= Vg/ Vp Yp Ys TOL MP GMP STI SSI Root dry weight Yp Ys TOL MP GMP STI SSI Table 8. Principal component loading for the traits measured on some genotypes Traits Shoot length Root dry weight Component 1 Component 2 Component 1 Component 2 Yp Ys TOL MP GMP STI SSI Eigenvalue Percent of Variation Cumulative percentage

8 Table 9. Cluster analysis of genotypes based on Yp, Ys and tolerant indices Groups number Number of genotypes that segregated based on Yp, Ys, MP, GMP and STI Group 1 35, 60, 28, 19, 56, 43, 54, 8, 50, 45, 13, 21, 53, 40, 52, 18, 64, 63, 24, 44, 59, 65, 16, 34 Group 2 5, 51, 25 Group 3 14, 42, 32, 37, 33, 4, 10, 29, 31, 39, 23, 26, 20, 55, 41, 2, 30 Group 4 7, 36, 3, 38, 12, 15, 62, 11, 27, 9, 22, 57, 48, 46, 6, 61, 49, 58, 17, 47, 1 Number of genotypes that segregated based on TOL and SSI Group 1 9, 22, 40, 27, 49, 17, 47, 7, 36, 14, 42, 18, 63, 62, 24, 30, 32, 55, 41, 33, 45, 1, 64, 59, 37, 44, 16 Group 2 25, 46, 12, 15, 5, 51, 65, 38, 4, 10, 3, 58, 11, 48, 57, 34, 52, 20 Group 3 13, 28, 43, 6, 61, 26, 50, 2, 54, 35, 56, 60, 39, 8, 31, 29, 19, 23, 21, SSI Yp MP Component STI GMP -0.9 TOL Ys Component 1 Fig. 1. Graphic display biplot for salt tolerance indices based on 65 rice genotypes References Akinci S, Yilmaz K, Akinci IE (2004) Response of tomato (Lycopersicon esculentum Mill.) to salinity in early growth stages of agricultural cultivation in saline environments. J. Environ. Biol. 25: Alam MZ, Bhuiya MAA, Muttalib MA, Rashid MM (2004) Effect of alternating saline and non-saline conditions on emergence and seedling growth of rice. Pak. J. Bio. Sci. 7: Ali Z, Salam A, Azhar FM, Ahmad Khan I (2007) Genotypic variation in salinity tolerance among spring and winter (Triticum aestivum L.) accessions. South African J. Bot. 73: Al-Khatib M, McNeilly T, Collins JC (1993) The potential for selection and breeding for improved salt tolerance in Lucerne (Medicago sativa L.). Euphytica, 65: Ashraf M (1994) Genetic variation for salinity tolerance in spring wheat. Hereditas, 120: Azhar FM, McNeilly T (1989) Heritability estimates of variation for NaCl tolerance in Sorghum bicolor (L.) Moench seedlings. Euphytica: 43, Betran FJ, Beck D, Banziger M, Edmeades GO (2003) Genetic analysis of inbred and hybrid grain yield under stress and non-stress environments in tropical maize. Crop Sci. 43:

9 Borsani O, Valpuesta V, Botella MA (2003) Developing salt tolerantplants in a new century: a molecular biology approach. Plant Cell Tissue Organ Cult. 73: Bruckner PL, Frohberg RC (1987). Stress tolerance and adaptation in spring wheat. Crop Sci. 27: Byrne PF, Bolanos J, Edmeades GO, Eaton DL (1995) Gains from selection under drought versus multilocation testing in related tropical maize populations. Crop Sci. 35: Ceccarelli S (1987) Yield potential and drought tolerance of segregating populations of barley in contrasting environments. Euphytica, 40: Ceccarelli S, Grando S (1991) Selection environment and environmental sensitivity in barley. Euphytica, 57: Clarke JM, De Pauw RM, Townley-Smith TM (1992) Evaluation of methods for quantification of drought tolerance in wheat. Crop Sci. 32: Clarke JM, Towenley-Smith TM, McCaig TN, Green DG (1984) Growth analysis of spring wheat cultivars of varying drought resistance. Crop Sci. 24: Cuartero J, Boların MC, Asıns MJ, Moreno V (2006) Increasing salt tolerance in the tomato. J. Exp. Bot. 57(5): Demiral T, Turkan I (2005) Comparative lipid peroxidation, antioxidant defense systems and proline content in roots of two rice cultivars differing in salt tolerance. Environ. Exp. Bot. 53: Dewey DR (1962) Breeding crested wheatgrass for salt tolerance. Crop Sci. 2: Falconer DS, Mackay TFC (1996) Introduction to quantitavie genetics. Chapman and Hall, London. Farshadfar E, Sutka J (2002) Multivariate analysis of drought tolerance in wheat substitution lines. Cereal Res. Commun. 31: Fernandez GCJ (1992) Effective selection criteria for assessing stress tolerance. In: Kuo, C.G. (Ed.), Proceedings of the International Symposium on Adaptation of Vegetables and Other Food Crops in Temperature and Water Stress, Publication, Tainan, Taiwan. Fischer RA, Maurer R (1978) Drought resistance in spring wheat cultivars. Part 1: grain yield response. Aust. J. Agric. Res. 29: Golabadi M, Arzani A, Mirmohammadi SAM (2006) Assessment of drought tolerance in segregating populations in durum wheat. Afr. J. Agric. Res. 1 (5): Haq T, Mahmood K, Shahzad A, Akhtar L (2003) Tolerance potential of wheat cv. LU-26S to high salinity and water logging interaction. Int. J. Agric. Bio. 5: Hossain ABS, Sears AG, Cox TS, Paulsen GM (1990) Desiccation tolerance and its relationship to assimilate partitioning in winter wheat. Crop Sci. 30: Houshmand S, Arzani A, Maibody SAM, Feizi M (2005) Evaluation of salt-tolerant genotypes of durum wheat derived from in vitro and field experiments. Field Crops Res. 91: Huang B (2000) Role of root morphological and physiological characteristics in drought resistance of plants. In: Wilkinson, R.E. (Ed.), Plant Environment Interactions. Marcel Dekker Inc., New York, pp Karadimova M, Djambova G (1993) Increased NaCl-tolerance in wheat (Triticum aestivum L. and T. durum Desf) through in vitro selection. In Vitro Cellular and Developmental Biology Plant. 29: Kaya Y, Palta C, Taner S (2002) Additive main effects and multiplicative interactions analysis of yield performances in bread wheat genotypes across environments. Turk. J. Agric. For. 26: Kelman M, Qualset CO (1991) Breeding for salinity-stressed environment: recombinant inbred wheat lines under saline irrigation. Crop Sci. 31: Khan AS, Asad MA, Ali Z (2003) Assessment of genetic variability for NaCl tolerance in wheat. Pak. J. Agr. Sci. 40: Kingsbury RW, Epstein E (1984) Selection for salt resistant in spring wheat. Crop Sci. 24: Lee KS, Chol WY, Kim KJT, Gregorio GB (2003) Salinitytolerance of japonica and indica rice (Oryza sativa L.) at the seedling stage.planta. 216: Maibody SAM, Feizi M (2005) Evaluation of salt-tolerant genotypes of durum wheat derived from in vitro and field experiments. Field Crops Res. 91: Maiti RK, Amaya LED, Cardona SI, Dimas AMO, Dela RM, Castillo HDL (1996) Genotypic variability in maize cultivars (Zea mays L.) for resistance to drought and salinity. J. Plant Physiol. 148: Mardeh A, Ahmadi A, Poustini K, Mohammadi V (2006) Evaluation of drought resistance indices under various environmental conditions. Field Crops Res. 98:

10 Mccaig TN, Clarke JM (1982) Seasonal changes in nonstructural carbohydrate levels of wheat and oats grown in semiarid environment. Crop Sci. 22: Nasir U, Carver BF, Clutte AC (1992) Genetic analysis and selection for wheat yield in drought-stressed and irrigated environments. Euphytica. 62: Noor E, Azhar FM, Khan AA (2001) Differences in responses of Gossypium hirsutum L. varieties to NaCl salinity at seedling stage. Int. J. Agri. Bio. 3: Pecetti L, Gorham J (1997) Screening of durum wheat germplasm for 22Na uptake under moderate salinity. Cereal Res. Commun. 25: Qureshi RH, Aslam M, Nawaz S, Mahmood T (1990) Saline Agriculture Research in Pakistan. In: Proceedings of the India and Pakistan Workshop on Soil Salinity and Water Management PARC, Islamabad. Rajaram S, Van Ginkle M (2001) Mexico, 50 years of international wheat breeding. In: Bonjean, A.P., Angus, W.J. (Eds.), The World Wheat Book: A History of Wheat Breeding. Lavoisier Publishing, Paris, France, pp Ramirez P, Kelly JD (1998) Traits related to drought resistance in common bean. Euphytica, 99: Rao SA, McNeilly T (1999) Genetic basis of variation for salt tolerance in maize (Zea mays L). Euphytica, 108: Rathjen AJ (1994) The biological basis of genotype-environment interaction: its definition and management. In: Proceedings of the Seventh Assembly of the Wheat Breeding Society of Australia, Adelaide, Australia. Richards RA (1996) Defining selection criteria to improve yield under drought. Plant Growth Regul. 20: Rosielle AA, Hamblin J (1981) Theoretical aspects of selection for yield in stress and non-stress environment. Crop Sci. 21: Saeed A, Khan AA, Saeed N, Saleem MF (2010) Screening and evaluation of tomato germplasm for NaCl tolerance. Acta Agric. Scand. Sect. B Soil Plant Sci. 60: Salam A, Hollington PA, Gorham J, Wyn Jones RG, Gliddon C (1999) Physiological genetics of salt tolerance in wheat (Ttiticum aestivum L): performance of wheat varieties, inbred lines and reciprocal F 1 hybrids under saline conditions. J. Agron. Crop Sci. 183: Saranga Y, Cahaner A, Zamir D, Marani A, Rudich J (1992) Breeding tomatoes for salt tolerance: inheritance of salt tolerance and related traits in interspecific populations. Theor. Appl. Genet. 84: Sarwar G, Ashraf MY, Naeem M (2003) Genetic variability of some primitive bread wheat varieties to salt tolerance. Pak. J. Bot. 35: Shaaban MM, El-Fouly MM, El-Zanaty AA (2004) Halophytes and foliar fertilization as a useful technique for growing processing tomatoes in the saline affected soils. Pak. J. Bio. Sci. 7: Shannon MC, Rhoades JD, Draper JH, Scardaci SC, Spyres MD (1998) Assessment of salt tolerance in rice cultivars in response to salinity problems in California. Crop Sci. 38: Singh K, Chatrath N (1992) Genetic variability in grain yield and its component characters and their association under salt stress conditions in tissue culture lines of bread wheat (Triticum aestivum L.). Wheat Information Service 75: Soloviev AA, Kuklev MY, Karnauakhova T (2003) Functional status of some genotypes of tomato under salinity conditions in green house. Acta Horticultural (ISHS). 609: Winter SR, Musick JT, Porter KB (1988) Evaluation of screening techniques for breeding drought-resistance winter wheat. Crop Sci. 28: