Drought stress is the most important production constraint in maize (Zea mays L.), especially in rainfed agriculture. To improve productivity of rainfed maize, the development of hybrids with tolerance to drought stress is an important objective in maize breeding programs. The present study was undertaken to identify maize hybrids that perform better under drought-stress and drought-free conditions by using various selection indices. These selection indices were calculated on the basis of yield (t ha–1) performance of hybrids measured under drought stress and optimum environments. A set of 38 cultivars was evaluated at 10 environments (representing five each of drought stress and optimum growing conditions). The average reduction in grain yield due to drought stress was 52%. Effects of genotype, environment and their interaction were significant sources of variation in determining grain yield, respectively explaining 5.0–7.4%, 55.0–60.2% and 12.0–15.0% of total variation in yield under drought-stress and drought-free conditions. Of eight selection indices considered for study, three indices such as harmonic mean, geometric mean, and stress tolerance index were identified as suitable for selection of genotypes capable of performing well both under drought-stress and drought-free environments. Drought response index and drought resistance index were found useful in identifying hybrids that performed better under drought stress. Stress susceptibility index was negatively correlated with yield measured under drought stress. Stress susceptibility index could be used as selection index but only in combination with yield performance data under water-deficit conditions in order to identify drought-tolerant hybrids with reasonable productivity. Test weight, shelling percentage, days to maturity, and ear girth were found to be useful traits for improving yield performance across diverse environments. Cultivation of identified drought-tolerant hybrids would be useful to enhance maize productivity in drought-stress environments.
Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.)
