PLoS ONE (Jan 2022)
Understanding drought response mechanisms in wheat and multi-trait selection.
Abstract
Wheat crop is very sensitive to osmotic stress conditions. As an abiotic stress, drought may exert a considerable effect on the levels of specialized metabolites in plants. These metabolites may exert beneficial biological activities in the prevention or treatment of disorders linked to oxidative stress in plants and humans. Furthermore, osmoprotector accumulation helps wheat to increase the maintenance of osmotic balance. Therefore, identifying wheat genotypes with better drought tolerance is extremely important. In this sense, this research aimed to understand agronomic, physiological and biochemical responses of spring wheat strains and cultivars to drought stress, under field conditions, and jointly select strains via multi-trait index. We evaluated agronomic, physiological and biochemical variables in 18 genotypes under field condition. The results demonstrated that all variables were affected by the drought. Most genotypes were significantly reduced in grain yield, except VI_14774, VI_14668, VI_9007 and TBIO_ATON. The variables related to photosynthesis were also affected. An increase above 800% was observed in proline contents in genotypes under drought. Sodium and potassium also increased, mainly for VI_131313 (Na), while VI_130758 and VI_14774 presented increased K. We evaluated the antioxidant potential of the different strains and the total content of phenolic compounds. The most drought-responsive genotypes were BRS_264, VI_14050 and VI_14426. Reduced grain yield and photosynthetic variables, and increased specialized metabolism compounds are due to plant defense mechanisms against drought conditions. Furthermore, variation in genotypes can be explained by the fact that each plant presents a different defense and tolerance mechanism, which may also occur between genotypes of the same species. Four strains were selected by the multivariate index: VI_14055, VI_14001, VI_14426 and VI_1466. Such results allow us to predict which genotype(s) performed best in semi-arid environments and under climatic fluctuations.