Development, optimization, and characterization of vitamin C-fortified oleogel-based chewable gels and a novel nondestructive analysis method for the vitamin C assay Article Swipe
Reyhaneh Sabourian
,
Farid Abedin Dorkoosh
,
Mohammad Reza Khoshayand
,
Mohsen Amini
,
Zahra Tamiji
,
Jahan B. Ghasemi
,
Naficeh Sadeghi
,
Mannan Hajimahmoodi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1186/s43014-024-00255-3
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1186/s43014-024-00255-3
Chewable gels represent an excellent alternative to oral dosage forms, such as tablets and capsules, owing to their appealing appearance, easy swallowing, and attractive colors. Given the inherent instability of vitamin C, particularly within chewable gels, it is imperative to enhance its stability and mitigate its degradation during processing and storage. Oleogel, systems prepared through an environmentally friendly and pollution-free method, exhibit a three-dimensional network structure that eliminates oxygen, alleviates oxidation, and enhances vitamin C stability. This study focused on optimizing vitamin C-fortified oleogel-based chewable gels using Plackett–Burman and D-Optimal design methodologies to maximize vitamin C stability while maintaining favorable mechanical properties. The optimal formulation, Opt-C, was achieved by crystallizing the gel at -18 °C, incorporating 2.5 g of distilled monoglyceride (DMG), and maintaining an oleogel-to-chewable gel ratio of 10%. Opt-C was comprehensively characterized using differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FT-IR), and its stability was rigorously assessed. Furthermore, a nondestructive assay method for vitamin C determination in chewable gels was developed employing near-infrared spectroscopy (NIR) and chemometric techniques. Storage studies demonstrated that Opt-C retained 85% of its vitamin C content during accelerated tests over ten weeks, surpassing the 69% retention observed in the control chewable gel. Opt-C exhibited a slower release of vitamin C in simulated digestive fluids; however, this release profile did not adversely impact the overall availability of vitamin C. Ultimately, the developed multivariate model successfully predicts vitamin C concentration: root mean square error of calibration (RMSEC): 0.284, $${\text{R}}_{\text{cal}}^{2}$$ : 0.9906; RMSE cross-validation (RMSECV): 0.501, $${\text{R}}_{\text{val}}^{2}$$ : 0.9722; RMSE prediction (RMSEP): 0.670, $${\text{R}}_{\text{pred}}^{2}$$ : 0.9154. This innovative approach enhances the stability of water-soluble vitamins in chewable gels. Graphical Abstract
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s43014-024-00255-3
- OA Status
- diamond
- Cited By
- 4
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401446870
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401446870Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1186/s43014-024-00255-3Digital Object Identifier
- Title
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Development, optimization, and characterization of vitamin C-fortified oleogel-based chewable gels and a novel nondestructive analysis method for the vitamin C assayWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-09Full publication date if available
- Authors
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Reyhaneh Sabourian, Farid Abedin Dorkoosh, Mohammad Reza Khoshayand, Mohsen Amini, Zahra Tamiji, Jahan B. Ghasemi, Naficeh Sadeghi, Mannan HajimahmoodiList of authors in order
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https://doi.org/10.1186/s43014-024-00255-3Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1186/s43014-024-00255-3Direct OA link when available
- Concepts
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Characterization (materials science), Vitamin, Vitamin C, Fortified Food, Chemistry, Nondestructive testing, Food science, Materials science, Chromatography, Biochemistry, Medicine, Nanotechnology, RadiologyTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
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2025: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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