Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy
ABSTRACTThis study aimed to determine the integrated freshness index (IFI) of eggs using Vis-NIR spectroscopy and optimized support vector regression, which gave the first insight into the freshness quality of eggs from the biochemical essence of quality changes. In this work, Vis-NIR transmission s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-09-01
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| Series: | International Journal of Food Properties |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10942912.2022.2158866 |
| _version_ | 1797202467494035456 |
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| author | Dandan Fu Qingyan Li Yan Chen Ming Ma Wenquan Tang |
| author_facet | Dandan Fu Qingyan Li Yan Chen Ming Ma Wenquan Tang |
| author_sort | Dandan Fu |
| collection | DOAJ |
| description | ABSTRACTThis study aimed to determine the integrated freshness index (IFI) of eggs using Vis-NIR spectroscopy and optimized support vector regression, which gave the first insight into the freshness quality of eggs from the biochemical essence of quality changes. In this work, Vis-NIR transmission spectra of brown-shell and pink-shell egg samples were analyzed between 500 nm and 900 nm. Standard normal variables (SNV) were used to normalize the spectral data, and the Shuffled Frog Leaping Algorithm (SFLA) and Competitive Adaptive Reweighted Sampling (CARS) were used to choose the optimal wavelengths. The quantitative analysis model of IFI was developed using a support vector regression (SVR) that was optimized using Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). After conducting a comparative analysis, it was determined that the GA-SVR model based on 63 wavelengths screened by the SFLA best predicted IFI with a training set coefficient of determination (Rc2) of 0.900, root means square error (RMSEC) of 0.005, a prediction set coefficient of determination (Rp2) of 0.816, root mean square error (RMSEP) of 0.012 and relative analysis error (RPD) of 2.077. The results demonstrate that the model can be used to simultaneously perform nondestructive detection of two distinct egg IFI variants, suggesting broader applicability and enhanced model reliability. |
| first_indexed | 2024-03-11T18:20:11Z |
| format | Article |
| id | doaj.art-795343bcc25a4f3d87e87573a78b6886 |
| institution | Directory Open Access Journal |
| issn | 1094-2912 1532-2386 |
| language | English |
| last_indexed | 2024-04-24T08:03:54Z |
| publishDate | 2023-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Food Properties |
| spelling | doaj.art-795343bcc25a4f3d87e87573a78b68862024-04-17T13:20:13ZengTaylor & Francis GroupInternational Journal of Food Properties1094-29121532-23862023-09-0126115516610.1080/10942912.2022.2158866Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopyDandan Fu0Qingyan Li1Yan Chen2Ming Ma3Wenquan Tang4College of Mechanical Engineering, Wuhan Polytechnic University, Wuhan, ChinaCollege of Mechanical Engineering, Wuhan Polytechnic University, Wuhan, ChinaCollege of Mechanical Engineering, Wuhan Polytechnic University, Wuhan, ChinaCollege of Mechanical Engineering, Wuhan Polytechnic University, Wuhan, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan, ChinaABSTRACTThis study aimed to determine the integrated freshness index (IFI) of eggs using Vis-NIR spectroscopy and optimized support vector regression, which gave the first insight into the freshness quality of eggs from the biochemical essence of quality changes. In this work, Vis-NIR transmission spectra of brown-shell and pink-shell egg samples were analyzed between 500 nm and 900 nm. Standard normal variables (SNV) were used to normalize the spectral data, and the Shuffled Frog Leaping Algorithm (SFLA) and Competitive Adaptive Reweighted Sampling (CARS) were used to choose the optimal wavelengths. The quantitative analysis model of IFI was developed using a support vector regression (SVR) that was optimized using Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). After conducting a comparative analysis, it was determined that the GA-SVR model based on 63 wavelengths screened by the SFLA best predicted IFI with a training set coefficient of determination (Rc2) of 0.900, root means square error (RMSEC) of 0.005, a prediction set coefficient of determination (Rp2) of 0.816, root mean square error (RMSEP) of 0.012 and relative analysis error (RPD) of 2.077. The results demonstrate that the model can be used to simultaneously perform nondestructive detection of two distinct egg IFI variants, suggesting broader applicability and enhanced model reliability.https://www.tandfonline.com/doi/10.1080/10942912.2022.2158866Integration freshness indexVis-NIR spectroscopySFLAGA-SVR |
| spellingShingle | Dandan Fu Qingyan Li Yan Chen Ming Ma Wenquan Tang Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy International Journal of Food Properties Integration freshness index Vis-NIR spectroscopy SFLA GA-SVR |
| title | Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy |
| title_full | Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy |
| title_fullStr | Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy |
| title_full_unstemmed | Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy |
| title_short | Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy |
| title_sort | assessment of integrated freshness index of different varieties of eggs using the visible and near infrared spectroscopy |
| topic | Integration freshness index Vis-NIR spectroscopy SFLA GA-SVR |
| url | https://www.tandfonline.com/doi/10.1080/10942912.2022.2158866 |
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