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In situ measurement of deposit layer formation during skim milk filtration by MRI
Author(s) -
Schork Nicolas,
Schuhmann Sebastian,
Nirschl Hermann,
Guthausen Gisela
Publication year - 2019
Publication title -
magnetic resonance in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 72
eISSN - 1097-458X
pISSN - 0749-1581
DOI - 10.1002/mrc.4826
Subject(s) - microfiltration , chemistry , skimmed milk , filtration (mathematics) , membrane , chromatography , fouling , casein , whey protein , fractionation , cross flow filtration , ultrafiltration (renal) , size exclusion chromatography , membrane fouling , globules of fat , food science , biochemistry , milk fat , statistics , mathematics , linseed oil , enzyme
Filtration and separation via membranes are key processes in food processing. One major application of membrane filtration is in the dairy industry, aiming for the separation of different milk proteins. The various chemical components of milk possess different physiochemical properties and can be used most effectively in food processing if they are separately available and remain in their native state. Microfiltration of skim milk allows a fractionation of the milk proteins casein and whey by size. A deposit is formed on the membrane surface mainly but not exclusively by micellar casein proteins during filtration. Membrane pore blockage by whey proteins and fouling occur during membrane filtration, negatively affecting the yield of the whey protein fraction. Skim milk filtration and the deposit layer formation were measured time and spatially resolved by in situ magnetic resonance imaging (MRI). The nature of the fouling layer was investigated during dead‐end filtration in ceramic hollow fiber membranes. MRI was used to further clarify the influence of operating conditions on separation and filtration mechanisms that are responsible for growth of the fouling layer and its reversibility. The MRI measurements were analyzed for a detailed description of skim milk filtration by modeling the signal intensity distribution.