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Sum-weighted casein micelle AF4-UV-SAXS data disentangled - A new method for characterization and evaluation of widely size distributed samples

Bolinsson, Hans LU orcid ; Pedersen, Martin Cramer ; Glantz, Maria LU ; Herranz-Trillo, Fátima ; Kirkensgaard, Jacob Judas Kain and Nilsson, Lars LU (2025) In Food Hydrocolloids 166.
Abstract

Casein micelles are key structures in milk, influencing stability, nutritional properties, and functionality. Their hierarchical architecture, which is dynamic and responsive to environmental conditions, plays a crucial role in dairy processing. Understanding the structural and dynamic properties of casein micelles is essential for optimizing dairy products and processing techniques. This study presents a novel method for characterizing and evaluating casein micelles using a combination of Asymmetrical Flow Field-Flow Fractionation (AF4) and Small-Angle X-ray Scattering (SAXS) at synchrotron facilities. By coupling AF4 with SAXS, we can fractionate milk samples according to micelle size and gain insights into their structural... (More)

Casein micelles are key structures in milk, influencing stability, nutritional properties, and functionality. Their hierarchical architecture, which is dynamic and responsive to environmental conditions, plays a crucial role in dairy processing. Understanding the structural and dynamic properties of casein micelles is essential for optimizing dairy products and processing techniques. This study presents a novel method for characterizing and evaluating casein micelles using a combination of Asymmetrical Flow Field-Flow Fractionation (AF4) and Small-Angle X-ray Scattering (SAXS) at synchrotron facilities. By coupling AF4 with SAXS, we can fractionate milk samples according to micelle size and gain insights into their structural organization. However, the high-throughput data generated in such experiments pose challenges for traditional data analysis. We introduce an automated data processing pipeline utilizing the McSAS software in combination with Indirect Fourier Transformation, allowing for efficient fitting of SAXS data and extraction of structural parameters such as radius of gyration (Rg) and maximum particle dimension (Dmax). This integrated approach provides a more detailed understanding of the heterogeneity and structural dynamics of casein micelles, revealing distinct features of their size distribution, internal cavities, and overall micelle structure across different fractions. The method offers a powerful tool for future investigations into the behavior of casein micelles under varying environmental conditions, with potential applications in optimizing dairy product formulations and studying casein micelle dynamics.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
AF4, Casein micelles, Evaluation, SAXS, Sum-weighted data, Wide size-distribution
in
Food Hydrocolloids
volume
166
article number
111377
publisher
Elsevier
external identifiers
  • scopus:105001108067
ISSN
0268-005X
DOI
10.1016/j.foodhyd.2025.111377
language
English
LU publication?
yes
id
552a4fa8-bb7a-468d-8f2d-7ab59a679b84
date added to LUP
2025-08-07 12:06:48
date last changed
2025-08-07 12:07:41
@article{552a4fa8-bb7a-468d-8f2d-7ab59a679b84,
  abstract     = {{<p>Casein micelles are key structures in milk, influencing stability, nutritional properties, and functionality. Their hierarchical architecture, which is dynamic and responsive to environmental conditions, plays a crucial role in dairy processing. Understanding the structural and dynamic properties of casein micelles is essential for optimizing dairy products and processing techniques. This study presents a novel method for characterizing and evaluating casein micelles using a combination of Asymmetrical Flow Field-Flow Fractionation (AF4) and Small-Angle X-ray Scattering (SAXS) at synchrotron facilities. By coupling AF4 with SAXS, we can fractionate milk samples according to micelle size and gain insights into their structural organization. However, the high-throughput data generated in such experiments pose challenges for traditional data analysis. We introduce an automated data processing pipeline utilizing the McSAS software in combination with Indirect Fourier Transformation, allowing for efficient fitting of SAXS data and extraction of structural parameters such as radius of gyration (R<sub>g</sub>) and maximum particle dimension (D<sub>max</sub>). This integrated approach provides a more detailed understanding of the heterogeneity and structural dynamics of casein micelles, revealing distinct features of their size distribution, internal cavities, and overall micelle structure across different fractions. The method offers a powerful tool for future investigations into the behavior of casein micelles under varying environmental conditions, with potential applications in optimizing dairy product formulations and studying casein micelle dynamics.</p>}},
  author       = {{Bolinsson, Hans and Pedersen, Martin Cramer and Glantz, Maria and Herranz-Trillo, Fátima and Kirkensgaard, Jacob Judas Kain and Nilsson, Lars}},
  issn         = {{0268-005X}},
  keywords     = {{AF4; Casein micelles; Evaluation; SAXS; Sum-weighted data; Wide size-distribution}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Food Hydrocolloids}},
  title        = {{Sum-weighted casein micelle AF4-UV-SAXS data disentangled - A new method for characterization and evaluation of widely size distributed samples}},
  url          = {{http://dx.doi.org/10.1016/j.foodhyd.2025.111377}},
  doi          = {{10.1016/j.foodhyd.2025.111377}},
  volume       = {{166}},
  year         = {{2025}},
}