Relative performance of wheat genotypes under individual and combined water deficit and salinity stress
Abstract
Ascertaining the genetic variability and its relationships among valuable genetic resources is important for crop improvement programme. Here, we assessed the response of eleven wheat (Triticum aestivum L.) genotypes using cluster and principal component analysis (PCA) based on morphophysiological data and yield under nine different environments. Wheat genotype WH 1080 maintained higher photosynthetic efficiency under individual stress of 50% water deficit (drought) and 100 mM NaCl (salt), whereas under interactive stresses KRL 370 and KRL 283 were found to be the best genotypes. The highest value of Na+/K+ ratio in shoots was recorded for WH 1080 (1.167) and lowest in KRL 283 (0.612) under combined stresses. Proline accumulation was maximum in KRL 330 (3.17 mg g-1 FW) and minimum in KRL 283 (2.8 mg g-1 FW). Significantly higher reduction (73.4%) was observed in HD 2009 for grain weight/plant at 100 mM NaCl + 50% WD stress treatment whereas minimum reduction of 39.18% was recorded in KRL 370 in comparison to the control treatment. The PCA showed that the first three components comprising about 91% of the total variation for which the variables were analyzed. AMMI model revealed KRL 210 to be stable genotype as being close to center on biplot. E5 environment (100 mM NaCl) was most stable followed by E9 (50% WD + 100 mM NaCl). HD 2888, C-306, HD 2851 and HD 2009 were having positive interaction with E1 (Control) whereas WH 1080 had positive interaction with water deficit environments i.e. E2 and E3 (25 and 50% WD) while KRL 433 had highest positive interaction with combined water deficit and salt stress environments E6, E7, E8 and E9, followed by KRL 370. Similarly, KRL 283, KRL 330, KRL 210 and Kharchia 65 had high positive interaction with saline environments E4 and E5. Findings of the experiment would be beneficial to wheat breeders, specifically the location-specific promising genotypes could possibly be used to develop/breed MAGIC populations to tag genes/alleles conferring drought and salinity tolerance.
Keyword(s)
Abiotic stressl; Drought; GGE biplot analysis; Triticum aestivum
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