Rapid measurement and statistical ranking of leaf drought tolerance capacity in cotton
Dong, X.; Mott, D. A.; Garg, J.; Zhou, Q.; Sunoj V. S., J.; McKnight, B. M.
Show abstract
Recent progress in ecological remote sensing calls for a more rapid measurement and a closer assessment of crop drought tolerance traits under field conditions. This study addresses three main questions: (1) If leaf dry matter content (LDMC) is equally effective in indicating cotton drought tolerance as leaf osmotic potential at full turgor ({pi}o); (2) if drought tolerance is inversely related to fiber yield/quality in line with the leaf economics spectrum; and (3) if a reliable statistical model can be developed to rank cotton drought tolerance. The values of{pi} o, along with those of LDMC, of 2736 leaves obtained from cotton variety trials conducted during 2020-2022 in both dryland and irrigated regimes were measured using osmometry. The relationships between{pi} o and LDMC, as well as those between traits and lint yield and fiber quality indices, were investigated using regression analysis. A Bayesian hierarchical linear model was developed to rank cotton drought tolerance based on differences (or adjustments) in{pi} o and LDMC between dryland and irrigated sites. LDMC was not only shown to be an alternate and equally effective drought tolerance trait compared with{pi} o obtained from the widely accepted osmometry method, its use is also estimated to lead to a tenfold increase in measuring speed. A stronger drought tolerance capacity of the tested cotton varieties correlated with a lower lint yield and quality, which is generally consistent with the prediction of the leaf economics spectrum. The drought tolerance rankings using the Bayesian hierarchical model help divide the selected 17 cotton varieties into three groups: (a) more-drought tolerant, (b) less-drought tolerant, and (c) intermediate. The ranking results are interpreted using field-measured data of root distribution and diurnal leaf gas exchange from selected cotton varieties. Our work provides new opportunities for a more rapid measurement and an unambiguous ranking of drought tolerance capacity for crop genotypes under various management regimes.
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