Payares et al. (2025) Assessing Plant Water Status and Physiological Behaviour Using Multispectral Images from UAV in Merlot Vineyards in Central Spain

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Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-07-02
• Authors: Luz K. Atencia Payares, Juan C. Nowack, Ana M. Tarquís, María Gómez del Campo
• DOI: 10.3390/rs17132273

Research Groups

Not specified in the provided text.

Short Summary

This study evaluates the efficacy of UAV-acquired high-resolution multispectral imagery in estimating vine water status in a Merlot vineyard. The results demonstrate that midday measurements using NDVI and combined red/NIR bands can effectively predict stem water potential.

Objective

• To assess the potential of high-resolution multispectral imagery acquired by UAVs to estimate vine water status under different irrigation regimes.

Study Configuration

• Spatial Scale: Commercial Merlot vineyard in Yepes (Toledo, Central Spain).
• Temporal Scale: Two growing seasons (2021 and 2022), with data collection at 09:00 and 12:00 solar time.

Methodology and Data

• Models used: Simple linear regression (using NDVI) and Multiple linear regression (incorporating red and NIR bands).
• Data sources: UAV-based multispectral imagery and in-situ physiological measurements (Stem Water Potential [SWP], chlorophyll content, and photosynthesis).

Main Results

• Stem water potential (SWP) showed the strongest and most stable associations with vegetation indices (VIs) and the red spectral band during midday (12:00) measurements.
• A simple linear regression model based on NDVI explained up to 58% of SWP variability.
• Multiple linear regression models using red and NIR bands improved predictive power, achieving an $R^2 = 0.62$.
• Midday measurements were significantly more effective at capturing water stress effects than morning measurements.

Contributions

• Validates UAV-based multispectral imagery as a non-destructive, scalable, and reliable alternative to labor-intensive traditional in situ methods for monitoring vine water status in field conditions.

Funding

Not specified in the provided text.

Citation

@article{Payares2025Assessing,
  author = {Payares, Luz K. Atencia and Nowack, Juan C. and Tarquís, Ana M. and Campo, María Gómez del},
  title = {Assessing Plant Water Status and Physiological Behaviour Using Multispectral Images from UAV in Merlot Vineyards in Central Spain},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17132273},
  url = {https://doi.org/10.3390/rs17132273}
}