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Estimation of the effective diffusion coefficient of water in skim milk during single-drop drying
RISE, SP – Sveriges Tekniska Forskningsinstitut, SP Food and Bioscience, Processing. Chalmers University of Technology, Sweden.ORCID iD: 0000-0001-6864-6308
RISE, SP – Sveriges Tekniska Forskningsinstitut, SP Food and Bioscience, Processing.
RISE, SP – Sveriges Tekniska Forskningsinstitut, SP Food and Bioscience, Processing.ORCID iD: 0000-0002-1485-8193
Tetra Pak Processing Systems, Sweden.
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2015 (English)In: Journal of Food Engineering, ISSN 0260-8774, E-ISSN 1873-5770, Vol. 147, p. 111-119Article in journal (Refereed) Published
Abstract [en]

This paper presents a new approach combining experimental methodology and modelling, developed to evaluate the effective diffusivity of water in skim milk during drying over a full range of water contents and temperatures. This parameter is important to support modelling of spray-drying processes and designing of equipment. The effective diffusion coefficient is evaluated using a combination of nuclear magnetic resonance (NMR) and parameter estimation. NMR is used to determine the temperature dependence and parameter estimation is used to estimate the water concentration dependence of the effective diffusivity of water in skim milk (0.90 on total weight basis) during drying by comparing the experimental data obtained using a suspended-drop method, which allows the recording of weight and temperature changes during drying, with the results of a distributed heat and mass transport model. The results indicate that the free-volume theory best predicts the dependence of the effective diffusion coefficient of water in skim milk. A mathematical correlation of effective diffusivity over a full range of water contents and temperatures (from 50 to 90°C) was obtained and experimentally successfully validated for concentrated skim milk (0.70 on total weight basis).

Place, publisher, year, edition, pages
2015. Vol. 147, p. 111-119
Keywords [en]
Diffusion coefficient, Skim milk, Spray drying, Single drop, NMR, Parameter estimation
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-6782DOI: 10.1016/j.jfoodeng.2014.09.032Scopus ID: 2-s2.0-84908428586Local ID: 20465OAI: oai:DiVA.org:ri-6782DiVA, id: diva2:964622
Available from: 2016-09-08 Created: 2016-09-08 Last updated: 2023-05-25Bibliographically approved

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Malafronte, LoredanaKaunisto, Erik

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