Prototyping and evaluation of a novel machine vision system for real-time, automated quality grading of sweetpotatoes

Abstract

Rapid advances in machine vision and artificial intelligence (AI) technologies have generated high interest in developing automated grading and sorting solutions for fresh produce of specialty crops. Sweetpotatoes are an economically important crop in the United States and beyond, but grading and sorting the commodity, especially for surface defects, remains a labor-intensive operation at commercial packing facilities. In addition to incurring high labor costs, manual grading is subjective and prone to human assessment error. This study was therefore aimed to develop automated grading technology based on machine vision and state-of-the-art AI to reduce labor dependence and improve quality assessment for sweetpotato packing lines. The developed grading system prototype consisted of a custom-designed roller conveyor to transport and rotate sweetpotatoes and an overhead color camera to perform full-surface quality assessment for size and surface defects. A YOLOv8-based computer vision pipeline was developed to segment and track each sweetpotato traveling on the conveyor and analyze sample quality conditions in real-time. The YOLOv8l model coupled with the BoT-SORT tracker achieved the overall Higher Order Tracking Accuracy (HOTA) score of 0.952. Based on the instance segmentation by YOLOv8l, the length and width of sweetpotatoes were estimated with percentage accuracies of 96.7 % and 90.3 %, respectively, while the instance segmentation for three classes of sweetpotatoes according to surface defect conditions yielded an overall accuracy of 82.6 %, regardless of samples. The final sample grading, which was realized by taking into account the quality information recorded from a sequence of multi-view images for each sample, achieved an overall accuracy of 91.7 % in grading four classes of sweetpotatoes. The developed prototype holds promise for next-stage integration with sorting mechanisms into a full-fledged sorting system and will be eventually beneficial for sweetpotatoes packers.