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作物对由土壤温度和生长阶段介导的涝渍的敏感性。

Crop sensitivity to waterlogging mediated by soil temperature and growth stage.

作者信息

Xu Fu-Li, Hu Pei-Min, Wan Xiao, Harrison Matthew Tom, Liu Ke, Xiong Qin-Xue

机构信息

College of Agriculture, Yangtze University, Jingzhou, China.

Meteorological Service Center, Jingzhou Meteorological Bureau, Jingzhou, China.

出版信息

Front Plant Sci. 2023 Oct 26;14:1262001. doi: 10.3389/fpls.2023.1262001. eCollection 2023.

Abstract

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 , WI, and WI. We then account for effects of crop growth stage and soil temperature on waterlogging impact by introducing waterlogging severity indices, WI , which accommodates growth stage tolerance, and WI , 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 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 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.

摘要

涝害限制了世界许多地区的作物产量。尽管如此,作物对涝害敏感性的关键驱动因素却很少受到关注。在此,我们比较了SWAGMAN Destiny模型和CERES模型模拟土壤通气指数的能力,该变量同时用于计算三个不同的涝害指数,以下分别记为WI 、WI 和WI 。然后,我们通过引入考虑生长阶段耐受性的涝害严重程度指数WI 和同时考虑土壤温度和生长阶段的WI ,来分析作物生长阶段和土壤温度对涝害影响的作用。我们利用在盆栽试验中收集的数据对这些指数进行评估,试验涉及基因型为“扬麦11”和“郑麦7698”的植株,它们经历了单次和两次涝害事件。我们发现WI 与产量的相关性最高(-0.82至-0.86),这表明整合温度和生长阶段影响的涝害指数可能会改善对涝害导致的产量损失的预测。重要的是,WI 不仅有助于深入了解生理决定因素,还便于通过卫星图像进行远程计算。因此,该指数在作物涝害的可扩展监测和预测方面具有前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b8c/10642075/ceb84b518b86/fpls-14-1262001-g001.jpg

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