Advancements in Food and Meat Freshness Monitoring: Integrating Machine Learning and Advanced Technologies

This study includes a comprehensive review of the literature on food and meat freshness control. These reviews discuss various approaches, challenges and opportunities, with a primary focus on the integration of advanced technologies and machine learning. The following review discusses the barriers to food freshness monitoring related to data management, physical analysis and sensory evaluation. It also includes meat freshness monitoring using both traditional and advanced approaches with a focus on integration and standardization. It also highlights the need for integration and the difficulties in accurately identifying meat types using sensory evaluation and DNA (Deoxyribonucleic acid) -based techniques. The application explores how machine learning (ML) is used for meat freshness, which requires interdisciplinary collaboration, and how it is used in food freshness, which also involves data collection and collaboration. The article also includes relevant case studies on fresh fruit, fish and poultry. Overall, this study highlights the critical role of ML and in improving food quality, safety and sustainability through freshness monitoring.