Visual inspection of cocoa beans is vital for quality control in the agri-food industry, yet traditional methods such as the cut test remain subjective and labor-intensive. Conventional Machine Learning (ML) and Deep Learning (DL) models show good performance in binary classification but often struggle with multi-class tasks and non-standard image conditions.This study introduces a Quaternion Convolutional Neural Network (QCNN) designed to capture inter-channel correlations in color images within both RGB and CIE XYZ spaces. The model was trained and validated on 1,788 cocoa bean images divided into six quality classes, collected under […] Read more at https://mjcellpress.com/article/mjes07/