Continuous Plant-Based and Remote Sensing for Determination of Fruit Tree Water Status

Abstract

Climate change poses significant challenges to agricultural productivity, making the efficient management of water resources essential for sustainable crop production. The assessment of plant water status is crucial for understanding plant physiological responses to water stress and optimizing water management practices in agriculture. Proximal and remote sensing techniques have emerged as powerful tools for the non-destructive, efficient, and spatially extensive monitoring of plant water status. This review aims to examine the recent advancements in proximal and remote sensing methodologies utilized for assessing the water status, consumption, and irrigation needs of fruit tree crops. Several proximal sensing tools have proved useful in the continuous estimation of tree water status but have strong limitations in terms of spatial variability. On the contrary, remote sensing technologies, although less precise in terms of water status estimates, can easily cover from medium to large areas with drone or satellite images. The integration of proximal and remote sensing would definitely improve plant water status assessment, resulting in higher accuracy by integrating temporal and spatial scales. This paper consists of three parts: the first part covers current plant-based proximal sensing tools, the second part covers remote sensing techniques, and the third part includes an update on the on the combined use of the two methodologies.

Plant phenotyping relevance

果樹の水分状態という植物生理形質を対象に、近接・リモートセンシング手法を体系的にレビューしており、フェノタイピング手法が中心です。

Code and data availability

This is a review article on proximal and remote sensing of fruit tree water status. It presents no original measurements, datasets, images, code, or models of its own. All referenced resources (SAPFLUXNET, ESA CHIME, Planet imagery, SSRN preprints) are external databases, missions, or cited prior work, not paper-phenen

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