Dynamic risk assessment of food safety based on an improved hidden Markov model integrating cuckoo search algorithm: A sterilized milk study

Abstract

With the growth in the living standard of people, food safety and quality risk assessment has gradually become the focus. Therefore, this article realizes the dynamic risk assessment of food safety based on an improved hidden Markov model (HMM) integrating the cuckoo search algorithm (CS) (CS‐HMM). The CS is used to conduct global search to obtain the initial value of HMM, and then the Baum–Welch algorithm is used for modifying the initial value to obtain a trained risk assessment model. Finally, in terms of several benchmark functions, the accuracy of the CS algorithm is better than the PSO and the GA algorithms for seeking global optimal solution. Moreover, the presented method is applied to evaluate the safety risk of the sterilized milk production. Combined with the characteristics of time and temperature, the deterioration reasons of sterilized milk are analyzed. Moreover, the proposed method has certain theoretical significance and practical value for improving the ability of food quality risk assessment and formulating control measures in advance. Practical applications The presented method is applied to evaluate the safety risk of the sterilized milk production, which are supplied by the food inspection agency of Guizhou province in China. Combined with the characteristics of time and temperature, the deterioration reasons of sterilized milk are analyzed. Furthermore, the improved model breaks out of the local optimal limit, so as to better realize the risk prediction of food and obtain better evaluation results. Based on the analysis of dynamic risk assessment result with the temperature characteristics, the future risk trend can be predicted. Meanwhile, the causes affecting the deterioration of the sterilized milk and the direction to improve the quality of the sterilized milk can be obtained. In this way, risk control measures can be taken more precisely and risks can be reduced more effectively, which is helpful to the production and storage of food products.

Risk early warning of food safety using novel long short-term memory neural network integrating sum product based analytic hierarchy process

“…Finally, the risk value is obtained by multiplying and adding the detection data after data fuzzification and transformation with the corresponding weight of risk evaluation index (Lin et al , 2021).…”

Discussion on emergency management of food safety from the perspective of foodborne diseases caused by mycotoxins

“…In addition, some scholars proposed a cuckoo search algorithm based on the improved Hidden Markov model. Dynamic risk assessment of food safety --disinfection milk study (Lin et al, 2021). Risk assessment is of great significance to the proposal of food safety emergency management measures, but the application of the risk assessment model still needs sufficient research data to be brought into the model, to intuitively compare which model has greater research value.…”

Data-Driven Analysis of Risk-Assessment Methods for Cold Food Chains

“…In addition, the HMM model was used to conduct probability analysis of the possible future safety levels of the system, and early warning risk analysis was conducted based on high indicator values, making up for the shortcomings of traditional static risk assessment. Aiming at the disadvantage that the Baum Welch algorithm in traditional HMM models can fall into local optimization, Lin et al [ 71 ] proposed a hidden Markov model method based on the optimization of the cuckoo search algorithm. The initial HMM value is obtained through the global search function in the cuckoo search algorithm, and then the Baum Welch algorithm is used to modify the initial value, train the risk assessment model, and improve the accuracy of sterilized milk risk assessment results.…”