Published: January 2026
As agrivoltaics (AgriPV) rapidly expands across Europe, combining agricultural land use with solar power generation presents a transformative opportunity. However, growing high-value crops beneath photovoltaic panels fundamentally changes microclimates, light availability, and crop dynamics. Traditional farm management systems – built strictly for open-field, full-sun environments – simply cannot account for these shaded, variable conditions.
To solve this gap, REDIGA proudly announces the successful completion of the TALOS Project in January 2026.
Through TALOS, we have successfully developed, field-tested, and validated PVgrow – an AI-native intelligence layer purpose-built to monitor crop health, predict growth trajectories, and automate decision-support in complex AgriPV environments.
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The Challenge: Why Standard Smart Farming Tools Fall Short in AgriPV
Most precision agriculture platforms rely on macro-level weather forecasts or simple open-field soil sensors. When solar modules shade crop rows at varying intensities throughout the day, standard agronomic models lose predictive accuracy.
AgriPV growers need more than energy telemetry; they need crop-first intelligence that understands how modified microclimates directly impact plant development, stress levels, and yield timing.
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What We Achieved in the TALOS Project
Conducted in real-world field conditions at a European commercial demonstration site,the TALOS initiative validated an end-to-end autonomous monitoring framework.
Key milestones achieved during the project include:
- Field-Validated Off-Grid Hardware Infrastructure:
Deployed autonomous, solar-powered field units equipped with specialized environmental sensors and multi-zone optical monitoring to capture microclimate variations across differing shading profiles.
- Growth-Stage Aware Phenology Tracking:
Implemented computer vision and environmental analytics to track key crop development phases – from dormancy and flowering to fruit set and final harvest window prediction. - Early Stress & Anomaly Identification:
Integrated automated visual and environmental detection models designed to spot early signs of crop stress, disease risks (such as rust), and extreme weather risks before visible yield loss occurs. - Actionable Decision-Support System:
Developed an intuitive, central dashboard that synthesizes complex multi-sensor data streams into clear, prioritized alerts and agronomic recommendations for farm operators.
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Looking Ahead: Scaling PVgrow
The completion of the TALOS project marks a crucial stepping stone, showcasing our technology and validation in real operating environments. But this is just the beginning.
As we transition into 2026 and beyond, REDIGA is accelerating the commercial deployment of PVgrow:
- Expanding Crop Varieties:
Scaling our predictive models beyond orchard fruit to cover additional high-value specialty crops and regional plant varieties.
- Automated Farm Integrations:
Expanding platform capabilities to integrate directly with automated farm infrastructure.
- Strategic Partnerships:
Collaborating with agricultural cooperatives, associations, and agronomists to expand software adoption, co-develop crop-specific models, and scale PVgrow across diverse farming operations.
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Join Our Early Adopter Program
Are you an AgriPV project developer, agricultural asset owner, or orchard manager looking to optimize crop yield under solar installations?
We are actively onboarding forward-thinking growers and project developers for our next phase of commercial pilots.
Contact our team today to learn how PVgrow can bring real-time, data-driven clarity to your fields.
