LAPSE:2023.2242
Published Article

LAPSE:2023.2242
Application of Computer Microtomography and Hyperspectral Imaging to Assess the Homogeneity of the Distribution of Active Ingredients in Functional Food
February 21, 2023
Abstract
Functional foods represent one of the most intensively investigated and widely promoted areas in the food and nutrition sciences’ market today. The purpose of this work is to determine the possibility of using computed microtomography to assess the homogeneity of distribution of active pharmaceutical ingredients (vitamins K and D and calcium) throughout chocolate. Algorithms for analyzing of microtomographic images were proposed to quantify the distribution of active pharmaceutical ingredients (API) in chocolate: the Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging. The use of the methods of analysis and processing of microtomographic images allows for a quantitative assessment of the homogeneity of the distribution of components throughout the sample, without a 3D reconstruction process. In computer microtomography analysis, it is possible to assess the distribution of those components whose density differs by at least a unit in the accepted scale of gray levels of images and for grain sizes not smaller than the voxel size. The proposed image analysis algorithms, Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging, allow for the assessment of distribution of active ingredients in chocolate.
Functional foods represent one of the most intensively investigated and widely promoted areas in the food and nutrition sciences’ market today. The purpose of this work is to determine the possibility of using computed microtomography to assess the homogeneity of distribution of active pharmaceutical ingredients (vitamins K and D and calcium) throughout chocolate. Algorithms for analyzing of microtomographic images were proposed to quantify the distribution of active pharmaceutical ingredients (API) in chocolate: the Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging. The use of the methods of analysis and processing of microtomographic images allows for a quantitative assessment of the homogeneity of the distribution of components throughout the sample, without a 3D reconstruction process. In computer microtomography analysis, it is possible to assess the distribution of those components whose density differs by at least a unit in the accepted scale of gray levels of images and for grain sizes not smaller than the voxel size. The proposed image analysis algorithms, Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging, allow for the assessment of distribution of active ingredients in chocolate.
Record ID
Keywords
chocolate, distribution homogeneity, image analysis, image processing
Suggested Citation
Błoński B, Wilczyński S, Stolecka-Warzecha A. Application of Computer Microtomography and Hyperspectral Imaging to Assess the Homogeneity of the Distribution of Active Ingredients in Functional Food. (2023). LAPSE:2023.2242
Author Affiliations
Błoński B: Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, Kasztanowa Street 3, 41-200 Sosnowiec, Poland
Wilczyński S: Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, Kasztanowa Street 3, 41-200 Sosnowiec, Poland [ORCID]
Stolecka-Warzecha A: Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, Kasztanowa Street 3, 41-200 Sosnowiec, Poland [ORCID]
Wilczyński S: Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, Kasztanowa Street 3, 41-200 Sosnowiec, Poland [ORCID]
Stolecka-Warzecha A: Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, Kasztanowa Street 3, 41-200 Sosnowiec, Poland [ORCID]
Journal Name
Processes
Volume
10
Issue
6
First Page
1190
Year
2022
Publication Date
2022-06-14
ISSN
2227-9717
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Original Submission
Other Meta
PII: pr10061190, Publication Type: Journal Article
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LAPSE:2023.2242
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https://doi.org/10.3390/pr10061190
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Feb 21, 2023
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