Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton
To study the texture, microstructural changes, and classification of cold-fresh (C-F), freeze-thawed once (F-T0), and freeze-thawed twice Tan mutton (F-Tt), the aforementioned three types of Tan mutton were subjected to near-infrared hyperspectrum scanning, scanning electron microscopy, and TPA test...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/2019/1957486 |
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| author | Dongdong Li Yaling Peng Haihong Zhang |
| author_facet | Dongdong Li Yaling Peng Haihong Zhang |
| author_sort | Dongdong Li |
| collection | DOAJ |
| description | To study the texture, microstructural changes, and classification of cold-fresh (C-F), freeze-thawed once (F-T0), and freeze-thawed twice Tan mutton (F-Tt), the aforementioned three types of Tan mutton were subjected to near-infrared hyperspectrum scanning, scanning electron microscopy, and TPA testing. The original spectrum of Tan mutton was obtained at a wavelength range of 900∼1,700 nm after hyperspectrum scanning; a spectrum fragment ranging from 918 nm to 1,008 nm was intercepted, and the remaining original spectrum was used as a studied spectrum (“full spectrum” hereafter). The full spectrum was pretreated by SNV (standard normal variate), MSC (multiple scattering correction), and SNV + MSC and then extracted feature wavelengths by SPA (successive projections algorithm) and CARS (competitive adaptive reweighted sampling) algorithm, and 25 feature wavelengths were obtained. By combining these feature wavelengths with classified variables, the SNV + MSC−CARS−PLS-DA (partial least squares-discriminate analysis, PLS-DA) and SNV + MSC−SPA−PLS-DA models for classification of C-F and F-T Tan mutton were established. In contrast, SNV + MSC−CARS−PLS-DA yielded the highest classification rate of 98% and 100% for calibration set and validation set, respectively. The results indicated that the texture and surface microstructure of F-T Tan mutton deteriorated, and more worsely with F-T time. SNV+MSC-CARS-PLS-DA could be well used to classify C-F, F-T0, and F-Tt Tan mutton. |
| format | Article |
| id | doaj-art-444504cf12104178b5b6022011c1e327 |
| institution | Kabale University |
| issn | 0146-9428 1745-4557 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
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| series | Journal of Food Quality |
| spelling | doaj-art-444504cf12104178b5b6022011c1e3272025-02-03T06:01:32ZengWileyJournal of Food Quality0146-94281745-45572019-01-01201910.1155/2019/19574861957486Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan MuttonDongdong Li0Yaling Peng1Haihong Zhang2School of Agriculture, Ningxia University, Yinchuan 750021, ChinaSchool of Agriculture, Ningxia University, Yinchuan 750021, ChinaSchool of Agriculture, Ningxia University, Yinchuan 750021, ChinaTo study the texture, microstructural changes, and classification of cold-fresh (C-F), freeze-thawed once (F-T0), and freeze-thawed twice Tan mutton (F-Tt), the aforementioned three types of Tan mutton were subjected to near-infrared hyperspectrum scanning, scanning electron microscopy, and TPA testing. The original spectrum of Tan mutton was obtained at a wavelength range of 900∼1,700 nm after hyperspectrum scanning; a spectrum fragment ranging from 918 nm to 1,008 nm was intercepted, and the remaining original spectrum was used as a studied spectrum (“full spectrum” hereafter). The full spectrum was pretreated by SNV (standard normal variate), MSC (multiple scattering correction), and SNV + MSC and then extracted feature wavelengths by SPA (successive projections algorithm) and CARS (competitive adaptive reweighted sampling) algorithm, and 25 feature wavelengths were obtained. By combining these feature wavelengths with classified variables, the SNV + MSC−CARS−PLS-DA (partial least squares-discriminate analysis, PLS-DA) and SNV + MSC−SPA−PLS-DA models for classification of C-F and F-T Tan mutton were established. In contrast, SNV + MSC−CARS−PLS-DA yielded the highest classification rate of 98% and 100% for calibration set and validation set, respectively. The results indicated that the texture and surface microstructure of F-T Tan mutton deteriorated, and more worsely with F-T time. SNV+MSC-CARS-PLS-DA could be well used to classify C-F, F-T0, and F-Tt Tan mutton.http://dx.doi.org/10.1155/2019/1957486 |
| spellingShingle | Dongdong Li Yaling Peng Haihong Zhang Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton Journal of Food Quality |
| title | Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton |
| title_full | Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton |
| title_fullStr | Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton |
| title_full_unstemmed | Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton |
| title_short | Investigation on Texture Changes and Classification between Cold-Fresh and Freeze-Thawed Tan Mutton |
| title_sort | investigation on texture changes and classification between cold fresh and freeze thawed tan mutton |
| url | http://dx.doi.org/10.1155/2019/1957486 |
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