Chapter 6: Applications of Fuzzy Logic as a Smart Tool for Food Quality Management Check Access

The food sector places major emphasis on food quality. Significant quality assurance and inspection tasks are needed at every stage of the food supply chain. Inadequate quality control assessments can result in a high percentage of damaged products and low customer satisfaction. The procedures that must be completed to ensure safety, however, are intricate and challenging to implement. Currently, human-dependent quality assurance and decision-making processes are generally used to maintain food quality. This implies that errors are likely to occur. However, because subjective human influence is involved in the process, this has occasionally resulted in inflexible, laborious, and inconsistent decisions. Consequently, current procedures are insufficiently effective to promote high-quality management. Thus, there is a dire need for automating human-based decision-making processes in the quality control of food. The food industry can benefit tremendously from novel artificial intelligence techniques namely fuzzy logic and neural networks. Many food applications, particularly in quality control, have made extensive use of fuzzy logic. It can theoretically emulate how people make difficult decisions based on vague and imperfect information by simulating more human behavior in thinking. This chapter delves further into the significance and potential application of fuzzy logic in the realm of food quality management.