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Advisor(s)
Abstract(s)
Drying of foods has been used to preserve food and agricultural products since immemorial times. However, still nowadays it assumes a prominent place among food processing technologies applied industrially
to extend shelf life of foods. Although having some important advantages, like the reduction in water activity and subsequent minimization of degradation reactions of biological, chemical or enzymatic nature,
reduction in size for transportation and storage or avoidance of refrigeration systems during transportation and storage, it is also true that drying brings high energy costs and some possible undesirable changes in quality parameters. Hence, the optimization of drying processes is of the utmost importance to minimize energy costs and maximize quality. Mathematical modelling in food process engineering allows important savings, while also guaranteeing the safety of industrial plants and workers, and finally achieving ultimate quality of the dried foods. Because artificial neural networks (ANNs) have been gaining importance in the context of many problems in the fields of engineering, among others, this chapter
aims to do a review of scientific literature about the use of artificial neural networks to modelling and optimization of food drying processes. Finally, opportunities and restrictions of the ANNs technique for drying process simulation, optimization, and control are achieved to guide future R&D in this area.
Description
Keywords
drying technology process control and modelling
Pedagogical Context
Citation
Guiné R, Golpour I, Barroca MJ and Kaveh M (2020) Application of Artificial Neural Networks (ANNS) Modelling in Drying Technology of Food Products: A Comprehensive Survey. In Skaar S (Ed.) A Comprehensive Guide to Neural Network Modeling. Chapter 1, pp. 1-56, Nova Science Publishers, Inc., USA.
Publisher
Nova Science Publishers, Inc., USA