Artificial Intelligence and Experimental Design: The Flywheel of Innovating Food Processing Engineering

Over the past decade, the development and improvement of artificial intelligence (AI) methods have contributed to its intensive application in many scientific disciplines. Thanks to its numerous advantages, AI has enabled the resolution of many problems in food process engineering and provided the opportunity to address various challenges faced by modern food production. In addition to AI methods, including artificial neural networks (ANNs), numerous chemometric methods (multivariate analysis, calibration and validation, experimental design, predictive modeling, signal processing, etc.) are also of great importance for this field. In some specific fields of food processing engineering, AI can be considered to be the flywheel of innovation, considering its contribution to the process optimization, product development and product design. The innovation, optimization and efficiency in food processing can be achieved through the synergy of artificial intelligence and experimental design. The present review focuses on contemporary and cutting-edge AI and experimental design approaches in food processing engineering and points out their main advantages and disadvantages. Recent applications and achievements in these fields are described and systematically discussed.