Enhancing the performance of lotus seed kernel and shell sorting after dehulling: A real-time approach based on deep learning and image processing (YOLOv8)

Nguyen Dinh-Tu, Huu-Phat Tran, Le Duc-Tin, Nguyen Hoai-Tan and Thanh-Thuong Huynh
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Nguyen Dinh-Tu: Faculty of Mechanical Engineering, Can Tho University of Technology, Can Tho, Vietnam
Huu-Phat Tran: Department of Mechanical Engineering, College of Engineering, National Central University, Tao Yuan, Taiwan
Le Duc-Tin: Faculty of Mechanical Engineering, Can Tho University of Technology, Can Tho, Vietnam
Nguyen Hoai-Tan: Faculty of Mechanical Engineering, College of Engineering, Can Tho University, Can Tho, Vietnam
Thanh-Thuong Huynh: Faculty of Mechanical Engineering, College of Engineering, Can Tho University, Can Tho, Vietnam

Research in Agricultural Engineering, vol. preprint

Abstract: Lotus seeds represent a high-value agricultural commodity, widely utilised in the food and pharmaceutical industries for their nutritional and medicinal benefits. However, post-harvest processing, specifically the removal of shells, often relies on manual labour or rudimentary equipment that results in low productivity. This study proposes a computer vision system based on the YOLOv8 deep learning framework to automate and enhance the efficiency of post-decortication sorting. The model is designed to detect and classify three distinct components: unshelled seeds, kernels, and shell fragments. Based on these predictions, the system controls pneumatic actuators to perform precise, real-time separation. Trained on a dataset of more than 30 000 images, the model achieved a mean average precision (mAP@0.5) of 92.6%. These results validate the model's capability to accurately identify lotus seed components under high-speed processing conditions. Consequently, this research presents a feasible technological solution to mitigate the labour dependence and optimise the shell residue removal stage in industrial lotus seed processing.

Keywords: computer vision; deep learning; fresh lotus seed shelling; post-harvest automation; shell-kernel lotus seed separation; smart and precision agriculture; YOLOv8n (search for similar items in EconPapers)
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DOI: 10.17221/29/2026-RAE

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