High-throughput phenotyping of physiological traits for wheat resilience to high temperature and drought stress

Interannual and local fluctuations in wheat crop yield are majorly explained by abiotic constraints. Heatwaves and drought, which are among the top stressors, commonly co-occur, and their frequency is increasing with global climate change. High-throughput methods were optimised to phenotype wheat plants under controlled water deficit and high temperature, with the aim to identify phenotypic traits conferring adaptative stress responses. Wheat plants of 10 genotypes were grown in a fully automated plant facility under 25/18ºC day/night for 30 days, and then the temperature was increased for seven days (38/31ºC day/night) while maintaining half of the plants well irrigated and half at 30% field capacity. Thermal and multispectral images and pot weights were registered twice daily. At the end of the experiment, key metabolites and enzyme activities from the carbohydrate and antioxidant metabolisms were quantified. Regression machine learning models were successfully established to predict plant biomass using image-extracted parameters. Evapotranspiration traits expressed significant genotype-environment interactions (GxE) when acclimatization to stress was continuously monitored. Consequently, transpiration efficiency was essential to maintain the balance between water-saving strategies and biomass production in wheat under water deficit and high temperature. Stress tolerance included changes in the carbohydrate metabolism, particularly in the sucrolytic and glycolytic pathways, and in the antioxidant metabolism. The observed genetic differences in sensitivity to high temperature and water deficit can be exploited in breeding programs to improve wheat resilience to climate change. [Abstract copyright: © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Experimental Biology.