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Insights from SILL 3:

Smart Computer Vision Helping Greenhouse Producers Cut Food Loss

Advanced computer vision and AI are enabling greenhouse growers to forecast yields more accurately, improve harvest planning, and significantly cut tomato waste at the production stage.

Food Loss in Greenhouse Tomato Production is a Challenge

Tomatoes are one of the most consumed vegetables in Europe and globally - but also one of the most wasted. In the EU alone, around 3 million tons of tomatoes are lost annually, resulting in wasted resources, financial loss, and inefficiency across the food chain. Within the ZeroW project’s Systemic Innovation Living Lab 3 (SILL 3), an innovative data-driven solution is being developed to address this challenge directly at the production stage. 

Greenhouses often struggle with overproduction, harvest timing issues, and mismatches between supply and fluctuating market demand. Diseases and mechanical damage also contribute to food loss by lowering the quality of produce. The absence of accurate, real-time monitoring makes it difficult for growers to adjust plans in time, leading to unnecessary waste.

AI-Driven Monitoring for Smarter Harvests

To tackle this, SILL 3 is developing an advanced computer vision-based monitoring system to help farmers optimize harvest planning and production workflows. The system uses multiple cameras mounted on a 100-metre rail track to capture images of tomato plants. In just three minutes per trip, the system can scan an entire hectare of greenhouse crops within a single day. 

These images are processed by custom AI-powered software, featuring machine-learning models that can identify and count tomatoes, assess ripeness levels, and estimate weight, all based on images alone. The processed data is uploaded in real time, supporting precise yield forecasting and enabling farmers to regulate supply in line with market demand. 

Through an interactive online dashboard, farmers gain access to these forecasts and actionable insights, allowing for better decision-making, improved harvest management, and significantly reduced food loss. 

This system marks a groundbreaking advancement for greenhouse management. By combining AI, computer vision, and data-driven decision-making, SILL 3 offers producers a scalable, practical tool to prevent overproduction, reduce waste, and align harvests with real-time market needs. 

ZeroW’s SILL 3 is setting a new standard for efficient, sustainable greenhouse operations - and it is just one of many innovations we are developing to help build a zero food waste future.  

Watch video Learn more about SILL 3

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