@article{Venera Karabekovna_2023, title={Evaluation of wheat (Triticum aestivum L.) lines for drought tolerance in Kyrgyzstan}, volume={35}, url={https://ejfa.me/index.php/journal/article/view/3099}, DOI={10.9755/ejfa.2023.v35.i5.3099}, abstractNote={<p>The study was carried out to explore drought stress indices in F4 hybrid generations of <em>Triticum aestivum</em> L. to select drought stress tolerant lines for rainfed areas of Kyrgyzstan. Wheat is the main food crop in Kyrgyzstan. There are about 0.3 million ha allotted for wheat, more than half of these sown areas (0.2 million ha) are in rainfed farming zones, where the amount of precipitation rarely exceeds 300-400 mm per year. The study was conducted in 2019 at the experimental field of Agricultural Faculty of Kyrgyz-Turkish Manas University. Eighteen hybrid lines of spring wheat and two released varieties (standard) were evaluated under irrigated and non-irrigated conditions. The results of the study show that the mean grain yield of evaluated lines under stress condition as compared to non-stressed condition was decreased  by  51.72%.  The  analysis  of correlation  coefficient  indicated  that  the  productivity  of  lines  under  both  conditions  highly depends from their stress tolerance indexes (STI) (0.769 to 0.928). Tolerance index (TOL) and stress susceptibility index (STI) were negatively correlated (-0.411 to -0.813) with yield of genotypes under stress condition (YS). The correlation between yield stability index (YSI) and yield of genotypes under stress condition (YS) was strongly and highly positive (1.000). Based on provided analysis, Line-1, Line-3, Line-5, Line-12, Line-13, Line-14 and Line-15 were selected as potential genotypes to cultivate in drought areas of Kyrgyzstan and can be used as drought tolerance genetic resources in crop improvement programs.</p> <p><br />Keywords: Correlation; Drought tolerance; Hybrid lines; Stress tolerance indices; <em>Triticum aestivum</em> L.</p>}, number={5}, journal={Emirates Journal of Food and Agriculture}, author={Venera Karabekovna, Isaeva}, year={2023}, month={May} }