STRAWBERRY: Smart real-time analytics for wholesales; boosting waste reduction & efficiency

Merqato has developed an AI-driven forecasting technology designed to address one of the main inefficiencies in fresh produce supply chains: misalignment between supply and demand at the wholesale level. Today, many wholesalers rely on short-term, manual forecasts that struggle to capture seasonality, weather variability, and rapidly changing market conditions. This often results in overproduction, last-minute order changes, unsold produce, and significant food loss.

In the context of the STRAWBERRY project, and with support from EIT Food, Merqato further develops and scales this technology to improve forecasting accuracy and extend planning horizons from two to six weeks. The project focuses on making the platform robust, scalable, and ready for widespread commercial use, supporting production, sourcing, and sales decisions across multiple fresh produce crops.

Alongside the technical development, LUT University conducts a life cycle assessment (LCA) to quantify the environmental, biodiversity, and economic impacts of improved forecasting and reduced food loss. Together, the project aims to deliver a 30% improvement in forecasting accuracy and enable up to a 10% reduction in food loss at the wholesale level, contributing to lower emissions, reduced resource use, and more resilient, sustainable food supply chains.