CROP-CARE: Improving agricultural monitoring in the face of climate change: Integrating spectroscopic techniques with machine learning to monitor olive and grape production

PID2024-156237OB-C31:

The CROP-CARE project (Climate-Resilient Olive and Grape Production: Control and Improvement of Agricultural Resistance through Bioextracts) is a coordinated initiative of the 2024-2027 Spanish National Plan for Scientific, Technical, and Innovation Research, bringing together teams from the URV (University of Valencia), IRTA Mas Bové (Mas Bové University), and the UPC (University of Valencia). Its overall objective is to respond to the challenges that climate change poses to Mediterranean agriculture by developing innovative strategies to improve the resilience and sustainability of olive and vineyard cultivation.

The project proposes the creation of a functional algae bioextract, obtained through sustainable processes, that acts as a biostimulant to reduce the effects of water and heat stress on these plants. It also combines this biotechnological approach with advanced analytical and monitoring technologies, allowing real-time monitoring of crop status and prediction of the optimal timing for applying treatments.

Within this framework, the Chemosens group (URV) leads the C31 subproject, entitled "Improving agricultural monitoring in the face of climate change: integrating spectroscopic techniques with machine learning for olive and grape production control." Our team focuses its research on the development of rapid, green, and non-destructive analytical techniques based on spectroscopy (UV-Vis, NIR, MIR, Raman) and image analysis (digital and hyperspectral), combined with machine learning algorithms. The goal is to shape plant development throughout their vegetative cycle and establish objective indicators that allow anticipating stress situations or growth deviations.

With this information, the goal is to design predictive models capable of determining the most appropriate times to apply bioactive algae extracts, optimizing their effectiveness and minimizing their environmental impact. This combination of technology, chemistry, and sustainable agriculture will provide monitoring and decision-making tools for more efficient and resilient production, aligned with the goals of climate-adapted agriculture.