Meat quality grading and contamination identification to avoid foodborne infection and food quality control

Abstract

Ensuring the safety and quality of meat production has a huge impact on preventing foodborne illness, which is also connected to the betterment of public health. Meat being highly decomposable is bound to be contaminated by such bacteria as E. coli, Salmonella and Listeria, which is responsible for serious health hazards. This paper mainly focuses on the development of a system with advanced technology that can provide an accurate meat quality detection. As a result, all this spoilage identification has been integrated by real time monitoring technologies like machine learning, sensors and microcontrollers. Besides, these technologies aim to detect spoilage indicators such as volatile organic compounds (VOCs), harmful bacteria and environmental factors. Furthermore, this can help for more identification, grading and contamination of meat processing. Ultimately, through detecting the spoilage of meat products, this project will not only help to ensure public health but will also have a great impact on the meat supply industry, society and the environment.