Integration of High-Throughput Water-Sensitive Phenotyping for Crop Water Demand Diagnosis: Technical Pathways, Research Progress, and Challenges

Abstract

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.

Plant phenotyping relevance

作物の水ストレス関連形質を高スループットに取得し、水需要診断モデルへ応用するフェノタイピング手法を体系的にレビューしており、方法論が中心である。

Code and data availability

The supplied blocks contain only the title page, copyright notices, and reference list of a review preprint. No phenotype datasets, images, sensor data, author code, models, or supplements with paper-specific assets are mentioned; all URLs are citations to prior work.

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