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Prediction of porosity of food materials during drying: Current challenges and directions

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Joardder, M. U. H., Kumar, C. and Karim, M. A. (2018) Prediction of porosity of food materials during drying: Current challenges and directions. Critical Reviews in Food Science and Nutrition, 58 (17). pp. 2896-2907. ISSN 10408398 (ISSN)

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Article Link: https://doi.org/10.1080/10408398.2017.1345852

Publisher URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061283342&doi=10.1080%2f10408398.2017.1345852&partnerID=40&md5=d16549b8976521793a1526541f7c530c

Abstract

Pore formation in food samples is a common physical phenomenon observed during dehydration processes. The pore evolution during drying significantly affects the physical properties and quality of dried foods. Therefore, it should be taken into consideration when predicting transport processes in the drying sample. Characteristics of pore formation depend on the drying process parameters, product properties and processing time. Understanding the physics of pore formation and evolution during drying will assist in accurately predicting the drying kinetics and quality of food materials. Researchers have been trying to develop mathematical models to describe the pore formation and evolution during drying. In this study, existing porosity models are critically analysed and limitations are identified. Better insight into the factors affecting porosity is provided, and suggestions are proposed to overcome the limitations. These include considerations of process parameters such as glass transition temperature, sample temperature, and variable material properties in the porosity models. Several researchers have proposed models for porosity prediction of food materials during drying. However, these models are either very simplistic or empirical in nature and failed to consider relevant significant factors that influence porosity. In-depth understanding of characteristics of the pore is required for developing a generic model of porosity. A micro-level analysis of pore formation is presented for better understanding, which will help in developing an accurate and generic porosity model. © 2017, © 2017 Taylor & Francis Group, LLC.

Item Type:Article
Corporate Creators:Department of Primary Industries, Queensland
Business groups:Horticulture and Forestry Science
Keywords:drying conditions food properties microstructure Pore formation porosity prediction models Desiccation Food Analysis Food Handling Food, Preserved Porosity Dehydration Forecasting Glass transition Pore size Thermal processing (foods) Dehydration process Drying condition In-depth understanding Porosity predictions Sample temperature Variable material property preserved food procedures Drying
Subjects:Science > Science (General)
Live Archive:12 Jun 2025 00:27
Last Modified:12 Jun 2025 00:27

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