In an industry where margins are tight and sustainability is increasingly mandated, a Belgian startup called Polysense is demonstrating a powerful new application for artificial intelligence. Founded by recent engineering graduates, the company has developed technology that uses cameras and sensors to analyze potatoes in real-time during processing. This allows machinery to automatically adjust to the natural variations in each tuber—size, shape, sugar content, and skin thickness—optimizing the cutting and cooking process for the production of chips and french fries. For processors, this means a direct reduction in waste and an increase in yield, turning what was once an unavoidable cost into a significant opportunity.
The core innovation addresses a fundamental agricultural truth: natural variation in raw materials leads to significant inefficiencies in standardized industrial processes. Polysense’s AI bridges this gap. While specific waste reduction figures for the company are proprietary, the scale of the problem is well-documented. The Food and Agriculture Organization (FAO) estimates that post-harvest losses for roots and tubers can be exceptionally high. In industrial processing, suboptimal tubers can lead to a 5-15% loss in yield due to defects like black spots, improper sizing, or residual peel. By enabling “smarter” machines that adapt to each potato, Polysense’s technology directly attacks this loss, creating both economic and ecological value. This aligns with a major industry trend; a 2023 report by the World Resources Institute highlighted that for every dollar companies invest in reducing food loss, they see a $14 return on average.
The Future is Adaptive and Data-Driven
The success of Polysense signals a critical shift in agricultural technology. It moves the focus from simply growing more to utilizing what we grow more intelligently. For farmers, this evolution means that delivering a high-quality, consistent raw product will remain paramount, but technology now exists to add value even to irregular produce. For agronomists and food engineers, it underscores the immense potential of integrating real-time data analytics directly into processing lines. The story of Polysense proves that the next leap in agricultural efficiency won’t just come from the field, but from the intelligent systems that transform raw commodities into consumer goods, ensuring that less of the harvest ends up as waste and more makes it to the consumer.
