Study on Multi-Bands Recognition for Varieties of Mutton by Using Hyperspectral Technologies
WANG Song-lei1，2, WU Long-guo1, MA Tian-lan2, CHEN Ya-bin2, HE Jian-guo1，2*, HE Xiao-guang2, KANG Ning-bo1
1. School of Construction and Hydraulic Engineering, Ningxia University, Yinchuan 750021, China 2. School of Agriculture, Ningxia University, Yinchuan 750021, China
Abstract：This paper focused on the research on identifying and classifying for mutton varieties of Tan-han hybrid sheep,Yanchi Tan-sheep and small-tailed sheep in Ningxia by using visible/ near-infrared (400~1 000 nm). Near infrared (900~1 700 nm) hyperspectral technologies, baseline and SG convolution smoothing spectra pretreatment methods were applied respectively according to the characteristics of different spectrum bands; the characteristic wavelengths were extracted by using successive projection algorithm (SPA);then combined with linear discriminant analysis (LDA) and radial basis kernel function of support vector machine (RBFSVM) model were applied to identify the different mutton varieties under characteristic wavelengths and full-wave bands. Results showed that there were good effects for mutton varieties identification in different hyperspectral bands, among which Baseline-Fullwave-RBFSVM and the same models under 12 characteristic wavelengths obtained accuracy of 100% and 98.75% in 400~1 000 nm respectively, and Baseline-Fullwave-RBFSVM and the same models under 7 characteristic wavelengths obtained accuracy of 96.25% and 87.80% in 900~1 700 nm respectively.The identification accuracy of RBFSVM nonlinear classification was higher than the LDA linear discriminant result, meanwhile the identification accuracy in 400~1 000 nm bands was better than in 1 000~1 700 nm bands, which explained that the differences of color and texture were more significant than the component contents among the 3 varieties mutton. Combined hyperspectral technologies with RBFSVM models can obtain a better recognition effect of mutton varieties.
Key words：Hyperspectral imaging technology;Varieties of mutton;Multichannel recognition;Characteristic wavelengths;SVM(support vector machine)
王松磊1，2，吴龙国1 ，马天兰2，陈亚斌2，何建国1, 2*，贺晓光2，康宁波1 . 高光谱技术的羊肉品种多波段识别研究 [J]. 光谱学与光谱分析, 2016, 36(09): 2937-2945.
WANG Song-lei1，2, WU Long-guo1, MA Tian-lan2, CHEN Ya-bin2, HE Jian-guo1，2*, HE Xiao-guang2, KANG Ning-bo1. Study on Multi-Bands Recognition for Varieties of Mutton by Using Hyperspectral Technologies. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(09): 2937-2945.
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