Artificial Intelligence (AI) Platform for Improving Food Safety Systems in Frozen and Chilled Food Industries

To create a competitive advantage with other countries, we have to focus on food safety for consumers, especially in the frozen food industry. We need to build confidence in the global market and increase the value of frozen and cold food products. From the research by the Food and Drug Administration (Food and Drug Administration, 2017), 28% of the samples found to be contaminated with microorganisms which did not meet Thai regulations (from all samples 10,547 items sold nationwide) and a research by Kanarat et al (2011) reported Listeria monocytogenes contamination in ready-to-eat chicken products accounted for 2.7 percent (from 2,259 samples). The best prevention of microbial contamination in food is to know the source of contamination (Tracking) together with the use of scientific data to support food safety policies. Consequently, this project focuses on applying Genogate technology from Japan to detect Listeria and detect the species of Listeria by Molecular or DNA Technique and developing an artificial intelligence (AI) platform for improving food safety systems in the frozen food industry. The platform will analyze data to identify the cause and the chance of Literia contamination in the frozen food production process, and the prediction model based on machine learning for Listeria contamination will be developed. The proposed platform will also provide suggestions based on appropriate precautionary principles. Last but not least, the key outcome is to establish a guideline of appropriate environmental monitoring program to reduce of finished product contamination, and also to efficiently improve the quality and safety control in the production of chilled and frozen food products. This results in enhancing the leapfrogging competitiveness of the frozen and cold food industry in the global market.