Non-destructive prediction of yak meat freshness indicator by hyperspectral techniques in the oxidation process
文献类型： 外文期刊
作者： Dong, Kai 1 ; Guan, Yufang 3 ; Wang, Qia 1 ; Huang, Yonghui 3 ; An, Fengping 2 ; Zeng, Qibing 1 ; Luo, Zhang 4 ; Huang, Qun 1 ;
作者机构： 1.Guizhou Med Univ, Sch Publ Hlth, Key Lab Environm Pollut Monitoring & Dis Control, Minist Educ, Guiyang 550025, Peoples R China
2.Fujian Agr & Forestry Univ, Coll Food Sci, Engn Res Ctr Fujian Taiwan Special Marine Food Pro, Minist Educ, Fuzhou 350002, Fujian, Peoples R China
3.Guizhou Acad Agr Sci, Food Proc Res Inst Guizhou Prov, Guizhou Key Lab Agr Biotechnol, Potato Engn Res Ctr Guizhou Prov, Guiyang 550006, Guizhou, Peoples R China
4.Tibet Agr & Anim Husb Univ, Coll Food Sci, Linzhi 860000, Tibet Autonomou, Peoples R China
5.Chengdu Univ, Inst Egg Sci & Technol, Sch Food & Biol Engn, Chengdu 610106, Peoples R China
6.Guizhou Med Univ, Key Lab Endem & Ethn Dis, Minist Educ, Guiyang 550004, Guizhou, Peoples R China
7.Guizhou Med Univ, Key Lab Med Mol Biol Guizhou Prov, Guiyang 550004, Guizhou, Peoples R China
8.Guizhou Med Univ, Guiyang 550025, Guizhou, Peoples R China
关键词： Hyperspectral technique; Yak meat; Freshness; PCR; SVR; PLSR
期刊名称：FOOD CHEMISTRY-X （ 影响因子：6.1； 五年影响因子：6.4 ）
ISSN： 2590-1575
年卷期： 2023 年 17 卷
页码：
收录情况： SCI
摘要： This study examined the potential of hyperspectral techniques for the rapid detection of characteristic indicators of yak meat freshness during the oxidation of yak meat. TVB-N values were determined by significance analysis as the characteristic index of yak meat freshness. Reflectance spectral information of yak meat samples (400-1000 nm) was collected by hyperspectral technology. The raw spectral information was processed by 5 methods and then principal component regression (PCR), support vector machine regression (SVR) and partial least squares regression (PLSR) were used to build regression models. The results indicated that the full -wavelength based on PCR, SVR, and PLSR models were shown greater performance in the prediction of TVB-N content. In order to improve the computational efficiency of the model, 9 and 11 characteristic wave-lengths were selected from 128 wavelengths by successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS), respectively. The CARS-PLSR model exhibited excellent predictive power and model stability.
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