Flikweert Vision Released AI-Powered Optical Produce Sorter
The QualityGrader system automates produce defect identification at throughputs of up to 30 tonnes per hour.
Updated on Oct. 12, 2026 in Artificial Intelligence
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Flikweert Vision has introduced the QualityGrader, an AI-powered optical sorting machine designed for potatoes and onions. The system is currently available as a commercial unit.
Why it matters
The technology addresses industry-wide challenges involving labor shortages, inconsistent defect rates, and strict retail quality specifications. By automating visual inspection, it shifts quality control from manual labor to machine-based consistency.
The system features processing throughput of 30 tonnes per hour and utilizes six or nine cameras across 1.0 or 1.5-metre working widths. An optional RejectSeparator unit is available to extract stones and clods from secondary streams.
The players
Flikweert Vision
A manufacturer specializing in industrial automated sorting and processing hardware for the agricultural sector.
The details
The QualityGrader uses an array of cameras to capture images of produce from multiple angles as they move along a conveyor. These images are fed into an AI system that identifies defects such as rot or physical damage in real time. For more complex sorting, an optional second rejection unit divides produce into three distinct streams rather than just two.
Timeline
October 14-16, 2026: Flikweert Vision will demonstrate the machine at the IFPA Global Produce & Floral Show.
The Tech Race
This development follows a trend of increasing automation in post-harvest processing relative to legacy industrial optical color sorters. It marks a shift from simple color-based rejection toward nuance-aware defect detection in agricultural supply chains.
Commercial agricultural producers can begin implementing these systems to optimize labor costs and consistency in produce grading. Compatibility is limited to large-scale potato and onion operations requiring industrial-grade physical footprints and throughput.
The takeaway
The move toward AI-driven produce sorting signals a transition in agricultural operations toward software-defined quality standards. Observers should track the adoption rates of this unit at the IFPA Global Produce & Floral Show to gauge its market penetration against established mechanical sorters.
Further reading
For broader trends in machine vision, visit Artificial Intelligence.
Source note: This article includes information reported by PotatoPro.
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