| Literature DB >> 32387877 |
Lijuan Cheng1, Guishan Liu2, Jianguo He3, Guoling Wan1, Chao Ma4, Jingjing Ban1, Limin Ma1.
Abstract
This study aimed to develop simplified models for rapid and nondestructive monitoring myoglobin contents (DeoMb, MbO2 and MetMb) during refrigerated storage of Tan sheep based on a hyperspectral imaging (HSI) system in the spectral range of 400-1000 nm. Partial least squares regression (PLSR) and least-squares support vector machines (LSSVM) were applied to correlate the spectral data with the reference values of myoglobin contents measured by a traditional method. In order to simplify the LSSVM models, competitive adaptive reweighted sampling (CARS) and Interval variable iterative space shrinkage approach (iVISSA) were used to select key wavelengths. The new CARS-LSSVM models of DeoMb and MbO2 yielded good results, with R2p of 0.810 and 0.914, RMSEP of 1.127 and 2.598, respectively. The best model of MetMb was new iVISSA-CARS-LSSVM, with an R2p of 0.915 and RMSEP of 2.777. The overall results from this study indicated that it was feasible to predict myoglobin contents in Tan sheep using HSI.Entities:
Keywords: Hyperspectral imaging; Least-squares support vector machines (LSSVM); Myoglobin content; Tan sheep; Wavelengths selection
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Year: 2019 PMID: 32387877 DOI: 10.1016/j.meatsci.2019.107988
Source DB: PubMed Journal: Meat Sci ISSN: 0309-1740 Impact factor: 5.209