Design of Experiments Applications Review: Food Processing Engineering as an Example Field

Abstract

The relationship between food processing engineering and the various properties and qualities of the final product is both evident and significant for industrial companies and customers alike. However, understanding the mechanisms underlying this relationship can be effectively achieved through a powerful and efficient mathematical and statistical methodology known as Design of Experiments (DoE), which aids in optimizing quality while minimizing cost. DoE encompasses various types, each offering distinct advantages. As a versatile tool, it is not only straightforward and practical but also highly insightful. This review begins with an overview of DoE to illustrate its applicability and relevance to the engineering field in general and to food processing engineering in particular. Its crucial roles are also discussed in both process scale-up and ensuring regulatory compliance and standards. Furthermore, this review presents a rundown of published research studies that have employed DoE, highlighting how this methodology has been applied to address various challenges in food processing engineering. These studies-like many others utilizing DoE-focus on investigating the relationship between specific food properties (considered dependent variables or responses) and the independent variables, which represent the tested factors. Finally, the future of DoE in food processing engineering is explored, with particular attention to the new opportunities enabled by emerging technologies such as Artificial Intelligence, Machine Learning, and real-time process monitoring