A Comprehensive Review of Artificial Intelligence (AI)-Driven Approaches to Meat Quality and Safety

Abstract

Assessment of meat quality is a fundamental aspect as it is the backbone of the meat industry. The quality of meat influences consumer satisfaction and safety, and is also necessary for competitiveness in the market. Nowadays, consumers know much more about food quality and safety. Moreover, quality and safety are major concerns for consumers. The meat industry is looking for alternatives to evaluate meat quality rather than traditional methods, as conventional methods are less efficient and time-consuming for evaluating the quality. The development of artificial intelligence (AI) technologies provides promising solutions to transform current techniques in quality evaluation. Currently, several sophisticated AI technologies are being developed for quality analysis, improving the precision and efficiency of meat quality examination. The AI systems are being used to examine color attributes as well as textures and microbial load to generate precise information that will assist producers in achieving ideal freshness and safety standards. AI-based technologies support predictive models that help stakeholders recognize supply chain issues in meat science while they remain easier to manage. This review conducts a comprehensive examination of AI systems used for meat quality evaluation. Furthermore, this review investigates the essential contribution of AI toward food safety improvements while explaining multiple techniques that can be utilized to determine expiration time. Multiple real-world scenarios demonstrate field implementations, and the advantages and disadvantages of AI-driven approaches in the meat science sector are discussed in this paper. Furthermore, this review also incorporates future predictions.