Neural Network Approach for Risk Assessment Along the Food Supply Chain

Neural networks are widely used as a mathematical tool for effective monitoring of robustness in the input data based on the machine learning process. Neural networks have been widely used for food safety, quality analysis, monitoring bacterial growth, and applying controls along the chain. Additionally, a combination of risk assessment processes would develop a smart approach and a model with fast methodology for evaluating risk at all stages of the food chain, thus providing a suitable prediction of risk at a given stage and increasing public health awareness for food processors, food safety managers, and other stakeholders working towards a sustainable food supply chain. This chapter discusses applying neural network approaches for risk assessment along the food supply chain.