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| Detection of beef TVB-N by visible and near-infrared spectroscopy combined with variable selection method |
| 1.College of Engineering, China Agricultural University, Beijing 100083, China; 2.Nanyang Institute of Technology, Nanyang, Henan 473004, China |
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Abstract To realize rapid and non-destructive detection of total volatile basic nitrogen(TVB-N) content of fresh beef with improved detection accuracy throughout the storage period at 4 ℃, a laboratory visible and near-infrared spectroscopy system was established to collect beef samples reflectance spectra between 400 and 1 700 nm. The beef samples were stored at 4 ℃ for 1 to 17 days. Multiplication scatter correction (MSC), first derivative (FD), Szvitzky-Golay(SG) smoothing method were used as pretreatment method for raw sample spectra. Combined with the effective wavelength variables extracted by uninformative variable elimination(UVE) and successive projections algorithm(SPA)， the least square-support vector machine(LS-SVM) was proposed to predict beef TVB-N content. The results show that the SG is the best pretreatment method with reduced input variables by 99.5% for UVE and SPA, and the proposed LS-SVM has good performance with Rv of 0.925 and Sc of 4.615 mg?(100 g)-1，respectively.
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Received: 05 January 2012
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2013, Vol. 34 
