Contemporary Food Science Automation for Food Engineering

Electronics and computer technologies have significantly pushed forward the progress of automation in the food industry. The application of these technologies to automation for food engineering should produce more nutritious, better quality, and safer items for consumers. This text explores the usage of advanced methods, such as wavelet analysis and artificial neural networks, to automated food quality evaluation and process control. It introduces novel system prototypes, such as machine vision, elastography, and the electronic nose, for food quality measurement, analysis, and prediction. The book discusses advanced techniques, such as medical imaging, mathematical analysis, and statistical modelling, which have proven successful in food engineering. The authors use the characteristics of food processes to describe concepts, and they employ data from food engineering applications to explain the methods. To aid in the comprehension of technical information, they provide real-world examples and case studies from food engineering projects. The material covers the frameworks, techniques, designs, algorithms, tests and implementation in data acquisition, analysis, modelling, prediction, and control in automation for food engineering. It demonstrates the techniques for automation of food engineering, and helps you in the development of techniques for your own applications.