The Research Center for the Management of Agricultural and Environmental Risks (CEIGRAM) of the Universidad Politécnica de Madrid joins the BIGPREDIDATA project, an ambitious R&D initiative of public-private collaboration that aims to develop 4.0 technological solutions to predict vineyard yields and prevent damage caused by climate change.

BIGPREDIDATA addresses the major challenges facing the wine industry in a context of climate change and economic uncertainty. Droughts, frost, pests and diseases have a direct impact on vineyard yields and sustainability. In response to these challenges, the project seeks to generate practical knowledge and innovative solutions to ensure the long-term competitiveness of the sector.

BIGPREDIDATA’s key objectives include:

  • Predicting vine crop yields by integrating agronomic, meteorological and climatic models.
  • Developing solutions to address the incidence of drought and frost, promoting sustainable and efficient viticulture.
  • Pest prevention through sustainable methodologies that optimize the use of resources.
  • Generating climate projections that enable producers to develop effective contingency plans.

The project’s work plan is structured into two major activities: Invespred, focused on industrial research for the evaluation of vineyard yield and drought risk, and Validpred, aimed at the experimental development and validation of a technological platform for the accurate prediction of harvest yield.

Viñedos de Bodegas Martín Codax in Cambados, Pontevedra. DO Rías Baixas

Thanks to its extensive experience in analysis and modeling, CEIGRAM plays a key role in the project’s research tasks. In addition, its participation is part of a long tradition of collaboration with companies in the wine sector. CEIGRAM’s Viticulture Research Group, led by Pilar Baeza, is spearheading the center’s contributions to this initiative, contributing its knowledge and experience to meet the current challenges facing the sector.

BIGPREDIDATA brings together a consortium of six business partners and six research groups. Companies such as Viñedos del Río Tajo, Bodegas Matarromera and Bodegas Martín Códax and DCOOP are involved, through the contribution of their vineyards and personnel to obtain the database that will be the computer support that will later be developed by RawData; AFEPASA also participates through the evaluation of a product against frost and, also, reference institutions such as the National Supercomputing Center, the Universitat Rovira i Virgili, the Polytechnic University of Valencia, AINIA Technology Center, the Chemical Institute of Sarria of the Universitat Ramón LLul. It also has the support of key associations in the wine sector, such as the Spanish Wine Federation (FEV) and the Wine Technology Platform.

The project is co-financed by the European Union and the Center for Technological Development and Innovation (CDTI Innovation) through ERDF funds, within the framework of the Multiregional Operational Program for Intelligent Growth 2021-2027 and the Strategic Program for National Business Research Consortiums (CIEN).

Maite Novellón in Bodegas Martín Codax, in Cambados, Pontevedra. DO Rías Baixas
Wineyards of Daramezas en Guadamur, Toledo, from the company Viñedos Río Tajo.

The CEIGRAM team for this project, in addition to the extensive experience of Dr. Pilar Baeza, also includes Elisa García García, who has collaborated for more than 15 years in Viticulture Research Group projects, and the two most recent additions, Maite Novellón and Sara Lacalle. Maite has a degree in Biotechnology from the University of Oviedo, with a Master’s degree in Biostatistics, and has experience in modeling biological data in order to make predictions and improve agricultural production. Sara has a degree in Agricultural Engineering and a Master in Agronomic Engineering from UPM, and has experience in the National Center for Food Technology and Safety (CNTA), as well as in the field of viticulture.

For complete information on the Project, you can visit the website that has been developed through the following link: https://bigpredidata.com/