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Smart machines make fresh produce processing more efficient and sustainable

In the food industry, the focus is rapidly shifting from manual control to systems that monitor and adjust processes automatically. Producers want to reduce waste, prevent downtime, and at the same time deliver consistent quality. This is especially challenging with fresh vegetables, because no head of lettuce, onion, or bell pepper is exactly the same. Variations in origin, season, and growing conditions require production lines that can adapt to the products coming in.

Smart machines make fresh produce processing more efficient and sustainable

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According to Elena Haffmans, Director of Business Innovation at Sormac, a technology supplier for vegetable processing, this is at the heart of current developments. She focuses on process improvement, data development, and IT, and sees artificial intelligence becoming increasingly prominent in vegetable processing. “One of the applications we are focusing on heavily is quality control using camera technology. In this way, you effectively add an artificial eye - like that of a trained specialist - to the process. This allows you to automatically assess whether a product looks as it should and, if necessary, send a follow-up instruction.”

This visual inspection is used to prevent incorrect products from ending up in packaging, or entire batches from being rejected because the product is too wet, cut too large, or too small. According to Haffmans, this is essential because small deviations can have major consequences for shelf life and waste. “Data-driven production makes it possible to work far more precisely than before. You can see exactly where losses occur and respond immediately. As a result, food waste not only becomes visible, but can actually be reduced. It is a shift from reacting to predicting and optimizing.”

Self-learning Systems

In many food-processing factories, operators are still responsible for configuring complex production lines with dozens of sensors and variables. However, the impact of even a small adjustment is almost impossible for people to fully oversee, especially further down the line. Haffmans therefore expects systems to become increasingly self-learning and self-managing. “We are working toward machines that understand the impact of a setting on the rest of the process. This will allow them to make autonomous adjustments to achieve an optimal end product with as little waste as possible.”

This also requires a different approach to maintenance and hygiene. According to her, preventing downtime starts with proactive service: machines that can indicate themselves when parts are wearing out or when intervention is needed. At the same time, every step — from washing and cutting to drying and mixing — must be tailored to the vulnerability of the product. Especially with leafy vegetables, every processing step affects quality and shelf life.

Sustainability

Sustainability also plays an important role, particularly through water consumption. By measuring water levels, turbidity, and temperature, processes can be managed more precisely and water can be reused more frequently. At the same time, new cultivation methods such as vertical farming and controlled environment agriculture are changing the characteristics of vegetables. Products from controlled cultivation are often more uniform and can be produced locally, but they are also more sensitive to processing and spoilage. This requires greater precision in processing and increases the importance of knowledge about product behavior and microbiological processes. “That is why we invested years ago in our own microbiological laboratory. The data we obtain there allows us to continuously improve our technology.”