Crop sensitivity to waterlogging mediated by soil temperature and growth stage

Frontiers in Plant Science

Plant Science

Fu-Li Xu¹  Qin-Xue Xiong¹  Xiao Wan¹  Ke Liu²  Pei-Min Hu³  Matthew Tom Harrison⁴ 

[1] College of Agriculture, Yangtze University, Jingzhou, China;College of Agriculture, Yangtze University, Jingzhou, China;Tasmanian Institute of Agriculture, University of Tasmania, Launceston, TAS, Australia;Meteorological Service Center, Jingzhou Meteorological Bureau, Jingzhou, China;Tasmanian Institute of Agriculture, University of Tasmania, Launceston, TAS, Australia;

关键词: waterlogging;    SWAGMAN Destiny;    hypoxia;    anoxia;    abiotic stress;    soil aeration;    crop physiology;    model;   

DOI  :  10.3389/fpls.2023.1262001

 received in 2023-07-19, accepted in 2023-10-09,  发布年份 2023

来源: Frontiers

【 摘 要 】

Waterlogging constrains crop yields in many regions around the world. Despite this, key drivers of crop sensitivity to waterlogging have received little attention. Here, we compare the ability of the SWAGMAN Destiny and CERES models in simulating soil aeration index, a variable contemporaneously used to compute three distinct waterlogging indices, denoted hereafter as WI Destiny, WIASD1, and WIASD2. We then account for effects of crop growth stage and soil temperature on waterlogging impact by introducing waterlogging severity indices, WI Growth, which accommodates growth stage tolerance, and WI Plus, which accounts for both soil temperature and growth stage. We evaluate these indices using data collected in pot experiments with genotypes “Yang mai 11” and “Zheng mai 7698” that were exposed to both single and double waterlogging events. We found that WI Plus exhibited the highest correlation with yield (-0.82 to -0.86) suggesting that waterlogging indices which integrate effects of temperature and growth stage may improve projections of yield penalty elicited by waterlogging. Importantly, WI Plus not only allows insight into physiological determinants, but also lends itself to remote computation through satellite imagery. As such, this index holds promise in scalable monitoring and forecasting of crop waterlogging.

【 授权许可】

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Copyright © 2023 Xu, Hu, Wan, Harrison, Liu and Xiong