Ferreira et al. (2025) Improving ETa Estimation for Cucurbita moschata Using Remote Sensing-Based FAO-56 Crop Coefficients in the Lis Valley, Portugal

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Plants
• Year: 2025
• Date: 2025-10-31
• Authors: Susana Ferreira, Juan Manuel Sánchez, José Manuel Gonçalves, Rui Eugénio, Henrique Damásio
• DOI: 10.3390/plants14213343

Research Groups

The specific research groups, labs, or departments involved are not explicitly mentioned in the provided text. The study focuses on the Lis Valley, Portugal, implying involvement of agricultural research relevant to Mediterranean smallholder irrigation conditions.

Short Summary

This study assessed pumpkin crop water status and evapotranspiration dynamics in the water-scarce Lis Valley, Portugal, by integrating in-situ soil moisture and electrical conductivity measurements with Sentinel-2 derived vegetation indices. It found that this integrated approach enhances precision irrigation strategies and confirmed the applicability of the FAO-56 method for Cucurbita moschata under Mediterranean conditions.

Objective

• To assess crop water status and evapotranspiration dynamics of pumpkin (Cucurbita moschata ‘Butternut’) using integrated in-situ soil moisture and remote sensing data, and to evaluate its potential for enhancing precision irrigation strategies in water-scarce regions.

Study Configuration

• Spatial Scale: Field plots in the Lis Valley, Portugal.
• Temporal Scale: 2020 growing season.

Methodology and Data

• Models used: FAO-56 method (for reference evapotranspiration and crop coefficients), empirical models for deriving actual evapotranspiration (ETa) from vegetation indices.
• Data sources:
  • In-situ measurements: Soil moisture content (SMC) and electrical conductivity (EC) at depths of 10 cm, 20 cm, 30 cm, 50 cm, and 70 cm using a TDR sensor.
  • Satellite data: Sentinel-2 imagery for Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), and Green Chlorophyll Index (GCI).
  • Ground-based sensor: GreenSeeker® sensor for NDVI comparison.

Main Results

• Strong correlations were observed between soil moisture content (SMC) and electrical conductivity (EC) in the upper soil layers.
• Sentinel-2 derived NDVI showed a similar temporal pattern to GreenSeeker® NDVI throughout the growing season.
• Actual evapotranspiration (ETa) estimates derived from remote sensing-assisted vegetation indices agreed with those obtained using the standard FAO-56 method, despite the absence of independent ETa measurements for validation.
• Water Productivity (WP) was estimated at 8.32 kg m⁻³.
• Water Use Efficiency (WUE FAO-56) was calculated at 0.64 kg m⁻³.
• The study reinforced the practical applicability of the FAO-56 method for Cucurbita moschata under Mediterranean conditions, where published references are scarce.

Contributions

• Demonstrates the effectiveness of integrating high-resolution remote sensing with continuous soil moisture monitoring to enhance precision irrigation strategies, increase crop yields, and conserve water resources in data-limited, water-scarce Mediterranean smallholder settings.
• Provides valuable water productivity and water use efficiency data for Cucurbita moschata under Mediterranean conditions, addressing a gap in existing literature.
• Confirms the utility of satellite-derived vegetation indices for replacing standard FAO-56 Kc values to incorporate actual crop condition variability in ETa estimations.

Funding

The provided text does not explicitly mention any specific funding projects, programs, or reference codes.

Citation

@article{Ferreira2025Improving,
  author = {Ferreira, Susana and Sánchez, Juan Manuel and Gonçalves, José Manuel and Eugénio, Rui and Damásio, Henrique},
  title = {Improving ETa Estimation for Cucurbita moschata Using Remote Sensing-Based FAO-56 Crop Coefficients in the Lis Valley, Portugal},
  journal = {Plants},
  year = {2025},
  doi = {10.3390/plants14213343},
  url = {https://doi.org/10.3390/plants14213343}
}

Generated by BiblioAssistant using gemini-2.5-flash (Google API)