Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique
Non-destructive determination of TVB-N content in beef using hyperspectral imaging (HSI) technique was evaluated. In order to create a robust model to predict the TVB-N content in beef, partition of sample set, spectral pretreatment, and the optimum wavelength selection were discussed. After the bee...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2016-01-01
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| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20166106007 |
| _version_ | 1818931723844452352 |
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| author | Liu Shanmei Gan Lu |
| author_facet | Liu Shanmei Gan Lu |
| author_sort | Liu Shanmei |
| collection | DOAJ |
| description | Non-destructive determination of TVB-N content in beef using hyperspectral imaging (HSI) technique was evaluated. In order to create a robust model to predict the TVB-N content in beef, partition of sample set, spectral pretreatment, and the optimum wavelength selection were discussed. After the beef sample set was parted by concentration gradient (CG) algortithm, and the spectra of beef samples were preprocessed by standard normalized variate (SNV) combined with auto scale(AS), the partial least square regression (PLSR) model was established using the full spectral range, which had the best prediction abilities with Rcv2 of 0.9124, Rp2 of 0.8816, RMSECV of 1.5889, and RMSEP of 1.7719, respectively. After the optimum wavelengths which is closely related to the TVB-N content of beef samples was obtained using the competitive adaptive re-weighted (CARS) algorithm, a new PLSR model was established using the optimum wavelengths, which had outstanding prediction abilities with Rcv2 of 0.9235, Rp2 of 0.9241, RMSECV of 1.4881, and RMSEP of 1.4882, respectively.The study showed that HSI is a powerful technique to predict the TVB-N content in beef by a nondestructive way. |
| first_indexed | 2024-12-20T04:21:08Z |
| format | Article |
| id | doaj.art-c2a344d93d4d4d95bd269fead933b033 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-20T04:21:08Z |
| publishDate | 2016-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-c2a344d93d4d4d95bd269fead933b0332022-12-21T19:53:38ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01610600710.1051/matecconf/20166106007matecconf_apop2016_06007Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging TechniqueLiu Shanmei0Gan Lu1College of Informatics, Huazhong Agricultural UniversitySchool of Electric and Electronic Engineering, Wuhan Polytechnic UniversityNon-destructive determination of TVB-N content in beef using hyperspectral imaging (HSI) technique was evaluated. In order to create a robust model to predict the TVB-N content in beef, partition of sample set, spectral pretreatment, and the optimum wavelength selection were discussed. After the beef sample set was parted by concentration gradient (CG) algortithm, and the spectra of beef samples were preprocessed by standard normalized variate (SNV) combined with auto scale(AS), the partial least square regression (PLSR) model was established using the full spectral range, which had the best prediction abilities with Rcv2 of 0.9124, Rp2 of 0.8816, RMSECV of 1.5889, and RMSEP of 1.7719, respectively. After the optimum wavelengths which is closely related to the TVB-N content of beef samples was obtained using the competitive adaptive re-weighted (CARS) algorithm, a new PLSR model was established using the optimum wavelengths, which had outstanding prediction abilities with Rcv2 of 0.9235, Rp2 of 0.9241, RMSECV of 1.4881, and RMSEP of 1.4882, respectively.The study showed that HSI is a powerful technique to predict the TVB-N content in beef by a nondestructive way.http://dx.doi.org/10.1051/matecconf/20166106007beefTVB-N contenthyperspectral imagingdata processing methods |
| spellingShingle | Liu Shanmei Gan Lu Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique MATEC Web of Conferences beef TVB-N content hyperspectral imaging data processing methods |
| title | Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique |
| title_full | Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique |
| title_fullStr | Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique |
| title_full_unstemmed | Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique |
| title_short | Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique |
| title_sort | determination of total volatile basic nitrogen tvb n content in beef by hyperspectral imaging technique |
| topic | beef TVB-N content hyperspectral imaging data processing methods |
| url | http://dx.doi.org/10.1051/matecconf/20166106007 |
| work_keys_str_mv | AT liushanmei determinationoftotalvolatilebasicnitrogentvbncontentinbeefbyhyperspectralimagingtechnique AT ganlu determinationoftotalvolatilebasicnitrogentvbncontentinbeefbyhyperspectralimagingtechnique |