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Drought tolerance response of high‐yielding soybean varieties to mild drought: physiological and photochemical adjustments
Author(s) -
Buezo Javier,
SanzSaez Álvaro,
Moran Jose F.,
Soba David,
Aranjuelo Iker,
Esteban Raquel
Publication year - 2019
Publication title -
physiologia plantarum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.351
H-Index - 146
eISSN - 1399-3054
pISSN - 0031-9317
DOI - 10.1111/ppl.12864
Subject(s) - biology , productivity , economic shortage , agronomy , drought tolerance , phenotypic plasticity , population , crop productivity , crop , ecology , linguistics , philosophy , demography , government (linguistics) , sociology , economics , macroeconomics
Soybean is a crop of agronomic importance that requires adequate watering during its growth to achieve high production. In this study, we determined physiological, photochemical and metabolic differences in five soybean varieties selected from the parental lines of a nested association mapping population during mild drought. These varieties have been described as high yielding (NE3001, HY1; LD01‐5907, HY2) or drought tolerant (PI518751; HYD1; PI398881, HYD2). Nevertheless, there has been little research on the physiological traits that sustain their high productivity under water‐limited conditions. The results indicate that high‐yielding varieties under drought cope with the shortage of water by enhancing their photoprotective defences and invest in growth and productivity, linked to a higher intrinsic water use efficiency. This is the case of the variety N‐3001 (HY1), with a tolerance strategy involving a faster transition into the reproductive stage to avoid the drought period. The present study highlights the role of the physiological and biochemical adjustments of various soybean varieties to cope with water‐limited conditions. Moreover, the obtained results underscore the fact that the high phenotypic plasticity among soybean phenotypes should be exploited to compensate for the low genetic variability of this species when selecting plant productivity in constrained environments.