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

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.

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Publication Details

Journal
Plants
Published
2026-04-30
DOI
https://doi.org/10.3390/plants15091372
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

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

Ainara López-Maestresalas, Sara León-Ecay, Maider Velaz, Carmen Jaren et al.
Plants
Remote Sensing in Agriculture
article

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

Ainara López-Maestresalas, Sara León-Ecay, Maider Velaz, Carmen Jaren, Silvia Arazuri, Jon Ruiz-de-Gauna, Patricia Viela
article en

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.

PlantsVol. 15(9)
Universidad Pública de Navarra (UPNA) (ES)
Clean water and sanitation
Openalex Percentile: Top 9%
Remote Sensing in Agriculture
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