Speaker
Description
With the predicted future climate change, the impact of drought stress on the production of agricultural crops can only be expected to become more severe in many parts of the arid and semi-arid regions. Thus, there is an urgent need to rapidly determine the drought tolerance capacity of agricultural crops. Leaf osmotic potential at full turgor as measured using osmometry has widely been regarded as a fast measurement of plant leaf drought tolerance capacity in the past decade. Based on extensive data collected under the field condition, we found that the measurement can be made ten times faster using leaf dry matter content, the ratio of leaf dry mass to saturated mass. This provides an opportunity for more efficiently calibrating remote sensors for indirectly estimating plant water status. We also developed a Bayesian statistical modeling method for cotton drought tolerance ranking and the results were corroborated with measured leaf carbon isotope ratios. Our work highlights the broad linkages between drought tolerance traits and cotton yield/quality indicators, which has implications for obtaining a deeper understanding of drought stress responses cotton and other crops being cultivated in arid and semi-arid regions.
