Genetic Basis of Stress-Responsive Traits in Cotton Revealed By Next Generation Phenotyping.

Heat and drought stress represent two of the most common abiotic stresses that plants encounter in modern agricultural production systems, resulting in significant economic losses. As climate change continues to increase the frequency and severity of these conditions, the development of stress-resilient cultivars becomes pivotal to sustaining crop yields. Central to meeting this challenge is the ability to elucidate the genetic and physiological basis of key stress adaptive and agronomic traits. To investigate these traits, multidimensional phenotypic data are needed that capture the dynamic response of plants to continuously changing conditions over the growing season. In light of this, we implemented high-throughput phenotyping of the plant canopy to map quantitative trait loci (QTL) controlling stress-responsive traits in a cotton population evaluated under contrasting irrigation treatments in a hot, arid environment. The ability of the field-based, mobile phenotyping system to collect data throughout the growing season revealed the temporal patterns of QTL expression in response to environmental conditions. A subset of these identified canopy trait QTL co-localized with those found to control variation for several physiological and agronomic traits, suggesting pleiotropic QTL. Furthermore, QTL for canopy temperature and normalized difference vegetative index, traits associated with leaf transpiration and wilting, co-located with candidate genes having known abiotic stress response functions. To further enhance these results, we investigated how seed ionomic profiles varied by preferential uptake of soil elements in response to drought conditions under high temperature, such as calcium which is critical for regulating stomatal aperture. This was done in combination with analyzing the ion profile of the soil itself to assess the effects of spatial variability on the observed phenotypic data. These combined results demonstrate the value of multidimensional data sets generated from novel phenotyping technologies to help provide insight into the varied physiological responses of plants to abiotic stress.