Food quality and safety risk assessment using a novel HMM method based on GRA

Food quality and safety are closely related to peoples health and living standard, and the risk assessment of food quality and safety has great social significance. Therefore, a novel hidden Markov model (HMM) based on gray relational analysis (GRA) (GRA-HMM), in terms of the high complexity and temporal characteristics of food detection data, is proposed to dynamically assess the food quality and safety risk. The weight of food detection indicators is calculated based on the GRA method to obtain risk indexes. Then risk indexes are used as the input data of the HMM to build the risk assessment model of food quality and safety. Moreover, the accuracy and reliability of the risk assessment model is proved based on the fuzzy matrix. Finally, the risk grading results of sterilized milk quality and safety are obtained using the proposed method. The results show that the GRA-HMM method has high accuracy in risk assessment. Meanwhile, risk control measures can be formulated or adjusted in advance and recommendations can be made for the food production, inspection and management departments.