Artificial Intelligence in Food Processing

The post-harvest food processing requires wide range of novel emerging techniques for efficient production and handling of food. Among these, Artificial intelligence (AI) is catching the attention of businesses across many disciplines and sectors directly and indirectly. AI driven food processing using mechanized inspection and learning methods for improving the food generation model. It is not only analyzes the data digitally, but also accurately replaces most of the human interventions. The complex assessment and management of food quality and quantity can be easily controlled and assured by using predictable models in AI. In global perspective, this chapter highlights the various scenarios and relationships of AI with dairy processing (identify adulteration, standardization and monitoring cleaning in place systems), cereal processing (sorting and grading), meat and poultry product processing (behaviour of carcass and egg quality), beverage processing (simulation of pulping process, detection of polyphenol contents, permeate flux, viscosity and discrimination of brands), fruits and vegetable processing (prediction of physical properties, internal defects, total soluble solids, pH and texture quality of processed fruits and vegetables), tea processing (assessing quality using E-nose), bakery and confectionary (surface color changes for chocolate). It elucidates requirements, demands and safety towards the food processing industries by means of AI. Also, this chapter explains challenges and recommendations in the setup of AI technologies in real-time post-harvest processing. Finally, the chapter notifies the future possibilities of AI revolution in food processing industries as a key to provide quality food.