Barquero (2026) Modelización del impacto interactivo de cubiertas vegetales y condiciones de cambio climático en el crecimiento de vitis vinífera L. Tempranillo mediante redes neuronales profundas

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

Identification

• Journal: Archivo Digital UPM (Universidad Politécnica de Madrid)
• Year: 2026
• Date: 2026-07-01
• Authors: Manuel González Barquero
• DOI: None

Research Groups

• Grupo de Investigación en Viticultura y Enología (GIVE)
• Departamento de Agronomía, Universidad de Córdoba

Short Summary

This study evaluates the impact of global warming and cover crops on young vineyards, developing a predictive tool based on Deep Learning to forecast soil moisture dynamics and plant growth.

Objective

• Investigate the effects of simulated global warming and cover crop management strategies on the establishment of young vineyards (cvs. 'Airén' and 'Tempranillo').

Study Configuration

• Spatial Scale: Field experiment conducted in a 1 ha plot at the Universidad de Córdoba's experimental farm.
• Temporal Scale: The study spanned two growing seasons, with data collected from March to October.

Methodology and Data

• Models used: Multilayer Perceptron (MLP) neural network for predictive modeling.
• Data sources: Telemetric sensor network (54 sensors), edaphic variables, physiological measurements, and climate data.

Main Results

• The use of cover crops protected the soil but triggered severe water competition that compromised vine development, reducing vegetative vigor by 35.6% under herbaceous layers.
• Simulated global warming increased the thermal integral, doubling cover crop biomass and accelerating soil desiccation.
• The MLP model accurately forecasted soil moisture seven days ahead (R² = 0.875; MAE = 0.0103 m³/m³).

Contributions

• This study provides novel insights into the effects of global warming and cover crop management on young vineyards, highlighting the need for predictive tools to mitigate climate-related risks.
• The developed MLP model demonstrates high viability and agronomic applicability, enabling winegrowers to simulate short-term hydric scenarios and adjust irrigation doses.

Funding

• This research was funded by the Spanish Ministry of Science and Innovation (Project Ref. AGL2017-87664-R) and the University of Córdoba's Research Fund (Ref. PFC10-15).

Citation

@article{Barquero2026Modelización,
  author = {Barquero, Manuel González},
  title = {Modelización del impacto interactivo de cubiertas vegetales y condiciones de cambio climático en el crecimiento de vitis vinífera L. Tempranillo mediante redes neuronales profundas},
  journal = {Archivo Digital UPM (Universidad Politécnica de Madrid)},
  year = {2026},
  url = {https://openalex.org/W7219548654}
}