Screening drought-tolerant bread wheat genotypes using yield-based stress indices

Abstract

Global wheat (Triticum aestivum L.) productivity suffers severely from drought stress. Exploiting natural variation in drought tolerance among genotypes offers a promising avenue to counter yield losses and breed superior varieties. As yield is the key trait in wheat breeding, selecting genotypes based on both yield and drought tolerance indices remain a viable strategy. To identify tolerant genotypes using yield and yield-based indices, a comprehensive investigation was conducted in a factorial fashion of 56 wheat genotypes under two water regimes (control and drought) over two distinct growing years. This approach employed a split-plot design to ensure the statistical robustness of the results. Drought stress significantly reduced grain yield regardless of genotype or growing season. Strong correlations were observed between yields and yield-based drought tolerance indices, with most associations being strongly positive for both control and drought-stressed conditions. Both hierarchical cluster analysis and principal component analysis produced well-correlated results, revealing three distinct genotypic clusters: 6 tolerant and high-yield, 31 mid-tolerant, and 19 susceptible and low-yield genotypes. Statistical analysis showed that eight drought tolerance indices, viz. stress tolerance index (STI), modified stress tolerance index (mSTI), mean productivity (MP), geometric mean productivity (GMP), harmonic mean index (HMI), relative efficiency index (REI), relative decrease in yield (RDY), and superiority index (Pi) effectively distinguished the genotypic clusters, indicating their usefulness in selecting drought-tolerant and high-yielding wheat genotypes. The genotypes from the tolerant cluster: BARI Gom 33, BARI Gom 21, BAW-1147, BD-9910, BD-600, and BD-9889 exhibited better yield protection under drought stress compared to the other genotypes, demonstrating their potential for cultivation in water-deficit environments.

Ann. Bangladesh Agric. (2023) 27 (2): 41-58