2020 ESA Annual Meeting (August 3 - 6)

PS 63 Abstract - Phenotyping rice genotypes using novel drought response curves

Megan Reavis1, Andy Pereira2, Anuj Kumar2, Sara Yingling2 and Kusum J. Naithani3, (1)Biological Sciences, University of Arkansas, Fayetteville, AR, (2)Crop, Soil, and Environmental Science, University of Arkansas, Fayetteville, AR, (3)University of Arkansas, Fayetteville, AR
Background/Question/Methods

Drought negatively affects crop yield, so understanding and quantifying the response of crops to drought is critical for improving yield predictions under changing climatic conditions. Commonly used crop models quantify physiological responses of crops to changing environments by using response curves (light, CO2 and temperature). However, current literature lacks a method to quantify a plant’s response to drought. Here, we propose an empirical model to quantify a plant’s response to increasing water stress that can be used as a tool to phenotype drought response and be incorporated in crop models for predicting crop yield under changing climate. We measured the response of photosynthesis, stomatal conductance, and transpiration of 16 rice genotypes to progressive drought in a manipulative field experiment using an LI-6400XT.

Results/Conclusions

We classified the genotypes as sensitive (5 genotypes), moderately sensitive (4 genotypes), and resistant (7 genotypes) to drought based on the drought response curve. In moderate and sensitive genotypes, photosynthesis decreased with increasing drought, after the moisture threshold (model parameter) had been reached. The tolerant genotypes show little or no photosynthetic response to change in soil moisture. Classifications based on genetic data and greenhouse experiments for these genotypes partially supports the results of drought response curves conducted in the field, suggesting different drought resistance mechanisms for some genotypes that are expressed under field conditions. For example, O. glaberrima is drought sensitive in greenhouse experiments, but drought resistant under field conditions, suggesting drought avoidance using deep roots. Our results highlight the need to quantify drought response of plants in field settings for improved understanding of drought coping mechanisms and crop modeling under changing climate.