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Application of machine learning (ML)-based algorithms in food drying is an exciting and innovative approach to advance the drying technology. In order to appropriately develop this novel approach in all aspects of food drying field, significant scientific research is required. The main aspects of food drying research are the determination of material properties, microstructural characterization, mathematical modeling, and process optimization. It is essential to express this fundamental information through ML-based algorithms to advance the food drying research. This paper aims to present a comprehensive review of the application of machine learning-based approaches in food drying modeling, property prediction, microstructural characterization, and process parameters optimization. Moreover, this paper discusses the possibilities and challenges to apply ML-based algorithms in multiscale modeling and microwave-based hybrid drying. It is expected that this review paper will be beneficial in advancing the machine learning-based food drying technology. [ABSTRACT FROM AUTHOR]

Food materials, particularly plant-based food materials, are mostly cellular in structure with diverse structural heterogeneities and variable cellular properties. To uncover the fundamental drying process, the cellular-level understanding of simultaneous heat and mass transfer process and associated morphological changes is essential. Consequently, researchers have attempted to investigate microlevel transport and material properties and their spatial and temporal distribution using recent innovative and cutting-edge experimental methods and technologies. The aim of this paper is to review the latest experimental technologies that can be applied to investigate the micro-level features of food material during drying. A comprehensive overview of advanced experimental techniques including X-ray microtomography, nuclear magnetic resonance (NMR), Near Infrared (NIR) Spectroscopy, light microscopy, nanoindentation and atomic force microscopy (AFM) has been presented. Finally, a summary of the current challenges of micro-level investigation for food drying is presented at the end of this paper. [ABSTRACT FROM AUTHOR]

In most drying processes, several physical, chemical and nutritional modifications take place in food products. Innovative drying techniques such as intermittent drying can enhance the quality of dehydrated products effectively and efficiently. Intermittent drying is a technique where drying conditions are changed through varying the drying air temperature, humidity, velocity, pressure, or even mode of heat input. This drying technique has been successfully applied to overcome the problems of conventional drying systems such as longer time consumption, case hardening, lower energy efficiency and poor-quality attributes. However, as the effect of intermittent drying on food quality is not yet well understood, a comprehensive study of quality change during intermittent drying is crucial. The main aim of this paper is to present a thorough review of the potential effect of intermittent drying methods on physical, chemical, nutritional, and stability characteristics of plant-based food material. It is found that application of intermittency using different drying systems has a significant effect on product quality and its stability. In addition, a comprehensive review on existing models of physio/biochemical kinetics for food drying is presented. Finally, the paper is concluded with the discussion of the current challenges and future directions of intermittent drying for producing high-quality dried food products. [ABSTRACT FROM AUTHOR]

The development of a physics-based model of food processing is essential to improve the quality of processed food and optimize energy consumption. Food materials, particularly plant-based food materials, are complex in nature as they are porous and have hygroscopic properties. A multiphase porous media model for simultaneous heat and mass transfer can provide a realistic understanding of transport processes and thus can help to optimize energy consumption and improve food quality. Although the development of a multiphase porous media model for food processing is a challenging task because of its complexity, many researchers have attempted it. The primary aim of this paper is to present a comprehensive review of the multiphase models available in the literature for different methods of food processing, such as drying, frying, cooking, baking, heating, and roasting. A critical review of the parameters that should be considered for multiphase modelling is presented which includes input parameters, material properties, simulation techniques and the hypotheses. A discussion on the general trends in outcomes, such as moisture saturation, temperature profile, pressure variation, and evaporation patterns, is also presented. The paper concludes by considering key issues in the existing multiphase models and future directions for development of multiphase models. [ABSTRACT FROM AUTHOR]