This research examines crop water demand diagnosis in agriculture, highlighting high-throughput phenotyping methods and challenges.
Accurate diagnosis of crop water demand is a core challenge in alleviating agricultural water scarcity. Traditional methods rely on soil moisture sensors or empirical models based on meteorological data, and have significant limitations. Therefore, developing real-time, non-destructive, and precise diagnostic technologies that reflect the crop's own water status will be crucial. In recent years, the high-throughput phenotyping technology has advanced rapidly and provided revolutionary tools to address this challenge. This paper explores the use of this technology to capture water-sensitive phenotypic traits of crops under water stress and construct water demand diagnosis models for real-time irrigation decision-making. By systematically reviewing research progress, technical methods, modeling strategies, and existing challenges, this study aims to provide theoretical support for precision irrigation and smart agriculture.
No takes yet. Share an insight, caveat, or question.
Shu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: