Systemization of requirements for operational quality control systems of meat products

Abstract

This paper presents a study on organizing requirements for automated meat quality control systems. It identifies key quality indicators – color, texture, marbling, and gloss and analyzes the technical and functional parameters essential for practical assessment. The research highlights integrating computer vision, image processing, and machine learning algorithms to enhance objectivity, accuracy, and evaluation speed. The proposed approach aims to reduce human influence, enable real-time monitoring, and offer scalable solutions suitable for large-scale producers and small enterprises.