Zuo Guanqiang, Feng Naijie, Zheng Dianfeng
College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang 524008, China.
College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China.
Plants (Basel). 2025 May 22;14(11):1571. doi: 10.3390/plants14111571.
Drought stress constitutes one of the most severe constraints to global agricultural productivity. Early drought detection is pivotal for sustainable agriculture, yet current approaches overlook critical dimensions of plant sensitivity. While advancements in photosynthetic parameter analysis (e.g., gas exchange, and chlorophyll fluorescence) have enhanced drought monitoring, three understudied factors limit progress: (1) differential drought sensitivity across plant organs (e.g., root nodules vs. leaves); (2) the selection of sensitive photosynthetic parameters and optimal measurement timing for stress detection; and (3) the identification of leaf layers most responsive to water deficits. By synthesizing insights from nodule physiology in legumes, cross-species evidence on multi-layered leaf senescence, and the temporal dynamics of stress sensitivity, this paper proposes a 'whole-plant sensitivity analysis' framework. Integrating organ-, parameter-, and time-specific perspectives, this paper aims to refine early drought detection in the field and enhance plant resilience research.
干旱胁迫是全球农业生产力面临的最严重制约因素之一。早期干旱检测对可持续农业至关重要,但目前的方法忽略了植物敏感性的关键维度。虽然光合参数分析(如气体交换和叶绿素荧光)的进展增强了干旱监测,但三个研究不足的因素限制了进展:(1)植物器官间不同的干旱敏感性(如根瘤与叶片);(2)用于胁迫检测的敏感光合参数的选择和最佳测量时间;(3)确定对水分亏缺最敏感的叶层。通过综合豆科植物根瘤生理学的见解、关于多层叶片衰老的跨物种证据以及胁迫敏感性的时间动态,本文提出了一个“全株敏感性分析”框架。本文整合了器官、参数和时间特定的观点,旨在改进田间早期干旱检测并加强植物抗逆性研究。