Estimating Moisture Content of Sausages with Different Types of Casings via Hyperspectral Imaging in Tandem with Multivariate

The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of tr...

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Published inApplied sciences Vol. 13; no. 9; p. 5300
Main Authors Feng, Chao-Hui, Arai, Hirofumi
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 24.04.2023
Subjects
Acids
Calibration
Cancer
Casings
Citrus
Citrus fruits
Coronaviruses
COVID-19
Flavonoids
Hesperidin
High performance liquid chromatography
Hyperspectral imaging
Industrial applications
Lecithin
Liquid chromatography
modified casing
moisture
Moisture content
orange extracts
Polynomials
Pretreatment
Response surface methodology
sausage
Sausages
Severe acute respiratory syndrome coronavirus 2
Soybeans
Surfactants
Water content
Wavelengths
Japan
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Abstract The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of treatment 19. Spectral pre-treatments were employed to enhance the model’s robustness. The raw and pre-processed spectral data, as well as moisture content, were fitted to a regression model. The RSM outcomes showed that the interactive effects of [soy lecithin concentration] × [soy oil concentration] and [soy oil concentration] × [orange extract addition] on moisture were significant (p < 0.05), resulting in an R2 value of 78.28% derived from a second-order polynomial model. Hesperidin was identified as the primary component of the orange extracts using high-performance liquid chromatography (HPLC). The PLSR model developed from reflectance data after normalization and 1st derivation pre-treatment showed a higher coefficient of determination in the calibration set (0.7157) than the untreated data (0.2602). Furthermore, the selection of nine key wavelengths (405, 445, 425, 455, 585, 630, 1000, 1075, and 1095 nm) could render the model simpler and allow for easy industrial applications.
AbstractList The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of treatment 19. Spectral pre-treatments were employed to enhance the model’s robustness. The raw and pre-processed spectral data, as well as moisture content, were fitted to a regression model. The RSM outcomes showed that the interactive effects of [soy lecithin concentration] × [soy oil concentration] and [soy oil concentration] × [orange extract addition] on moisture were significant (p < 0.05), resulting in an R2 value of 78.28% derived from a second-order polynomial model. Hesperidin was identified as the primary component of the orange extracts using high-performance liquid chromatography (HPLC). The PLSR model developed from reflectance data after normalization and 1st derivation pre-treatment showed a higher coefficient of determination in the calibration set (0.7157) than the untreated data (0.2602). Furthermore, the selection of nine key wavelengths (405, 445, 425, 455, 585, 630, 1000, 1075, and 1095 nm) could render the model simpler and allow for easy industrial applications.
The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of treatment 19. Spectral pre-treatments were employed to enhance the model's robustness. The raw and pre-processed spectral data, as well as moisture content, were fitted to a regression model. The RSM outcomes showed that the interactive effects of [soy lecithin concentration] × [soy oil concentration] and [soy oil concentration] × [orange extract addition] on moisture were significant (p < 0.05), resulting in an R[sup.2] value of 78.28% derived from a second-order polynomial model. Hesperidin was identified as the primary component of the orange extracts using high-performance liquid chromatography (HPLC). The PLSR model developed from reflectance data after normalization and 1st derivation pre-treatment showed a higher coefficient of determination in the calibration set (0.7157) than the untreated data (0.2602). Furthermore, the selection of nine key wavelengths (405, 445, 425, 455, 585, 630, 1000, 1075, and 1095 nm) could render the model simpler and allow for easy industrial applications.
Audience Academic
Author Feng, Chao-Hui
Arai, Hirofumi
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Snippet The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were...
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SubjectTerms Acids
Calibration
Cancer
Casings
Citrus
Citrus fruits
Coronaviruses
COVID-19
Flavonoids
Hesperidin
High performance liquid chromatography
Hyperspectral imaging
Industrial applications
Lecithin
Liquid chromatography
modified casing
moisture
Moisture content
orange extracts
Polynomials
Pretreatment
Response surface methodology
sausage
Sausages
Severe acute respiratory syndrome coronavirus 2
Soybeans
Surfactants
Water content
Wavelengths
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Title Estimating Moisture Content of Sausages with Different Types of Casings via Hyperspectral Imaging in Tandem with Multivariate
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https://doaj.org/article/0873a5783fca4f1f8e09c37d647be34f
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