Monitoring Water Stress in Grapevine ( Vitis vinifera L.) Using Proximal Hyperspectral Imaging.

Abstract

This study addresses the early detection of water stress in grapevines ( Vitis vinifera L. cv. Monastrell), a key challenge for precision irrigation. The main objective is to assess the feasibility of VIS-NIR hyperspectral imaging (400-1000 nm) to anticipate water stress, relating the spectral signal to stem water potential. This study was developed over two campaigns, in 2024 and 2025, using 18 potted plants. In 2024, eight vines were irrigated, and the remaining 10 were subjected to water-deprivation treatments, whilst in 2025, all plants were irrigated, but half at a control dose and the rest at a reduced dose equivalent to 33% of the control. Images were acquired over five dates in June 2024 and over seven in June 2025 using a Specim IQ camera; stem potential was also measured to provide a physiological reference. Individual time series were developed, calculating the Mahalanoubis distance in a PCA space. Results revealed a change window between 10 and 13 June, consistent with the divergence in water potential from 17 to 24 June. PCA highlighted spectral regions related to changes in pigments, nitrogen and water content as main indicators of water stress. We conclude that HSI is a promising tool for early water stress detection.

Plant phenotyping relevance

ブドウの水ストレス状態を近接ハイパースペクトル画像から推定・早期検出する方法が研究の中心であり、生理学的基準との比較も行っている。

Code and data availability

The article describes hyperspectral imaging of grapevines and MATLAB custom-script analysis, but contains no data availability statement, no public repository deposit of images, spectra, stem water potential measurements, or author code. The only URLs present are external references (Meteo Navarra weather station pages

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