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基于可见/近红外高光谱成像技术的牛肉品种鉴别
引用本文:王彩霞,王松磊,贺晓光,董欢.基于可见/近红外高光谱成像技术的牛肉品种鉴别[J].食品工业科技,2019(12):241-247.
作者姓名:王彩霞  王松磊  贺晓光  董欢
作者单位:宁夏大学农学院
基金项目:红外与热风协同新型烘烤技术及装备研发(021704000107)
摘    要:利用可见/近红外高光谱成像技术实现荷斯坦奶牛、秦川牛、西门塔尔牛三个品种牛肉的快速无损鉴别。首先,对原始光谱进行预处理并对样本集进行划分;应用竞争性自适应重加权算法(CARS)、连续投影算法(SPA)和无信息变量消除算法(UVE)对预处理后的光谱数据提取特征波长;结合偏最小二乘判别模型(PLS-DA)、K最近邻(KNN)模型及支持向量机(SVM)模型进行全波段及特征波段鉴别分析。结果表明,一阶导数(FD)法为最优预处理方法,利用光谱-理化值共生距离法(SPXY)法划分后的样本模型预测性能最好;利用CARS、SPA和UVE分别选出24、17和19个特征波长;基于CARS法提取的特征波长所建的RBF-SVM模型的校正集与预测集正确率分别为100%、98.82%。由此可见,基于高光谱成像技术能够获得较好的牛肉品种鉴别效果。该研究可为牛肉品种的快速无损鉴别提供参考。

关 键 词:可见/近红外  高光谱成像技术  牛肉品种  无损鉴别  支持向量机

Identification of Beef Breeds Based on the Vis/NIR Hyperspectral Imaging Technique
WANG Cai-xia,WANG Song-lei,HE Xiao-guang,DONG Huan.Identification of Beef Breeds Based on the Vis/NIR Hyperspectral Imaging Technique[J].Science and Technology of Food Industry,2019(12):241-247.
Authors:WANG Cai-xia  WANG Song-lei  HE Xiao-guang  DONG Huan
Affiliation:(School of Agriculture,Ningxia University,Yinchuan 750021,China)
Abstract:Rapid and non-destructive identification of three varieties of beef(Holstein cow,Qinchuan cattle and Simmental cattle)was realized by visible/near-infrared hyperspectral imaging technology. Firstly,the original spectral date was pretreated and the sample set was divided.Then,the characteristic wavelengths were selected from the pretreatment spectral data by competitive adaptive reweighed sampling(CARS),successive projections algorithm(SPA)and uniformative variable elimination(UVE). K-nearest neighbor(KNN)and partial least squares discrimination analysis(PLS-DA)and support vector machine(SVM)discriminant models of beef were established,basing on full spectrum and characteristic wavelengths respectively. The results showed that the first derivative(FD)method was the optimal pretreatment method. The sample model divided by spectrum-physicochemical value symbiosis distance method(SPXY)had the best prediction performance. The number of the characteristic wavelengths selected by competitive adaptive reweighed sampling(CARS),successive projections algorithm(SPA)and uniformative variable elimination(UVE)were 24,17 and 19. The accuracy of the correction set and prediction set of the RBF-SVM model based on the characteristic wavelength,extracted by the CARS method were 100% and 98.82%,respectively. It was confirmed that using hyperspectral imaging technologies could obtain a better recognition effect of beef varieties. The study provided meaningful references for a rapid and non-destructive detection of the beef breeds.
Keywords:visible/near infrared  hyperspectral imaging technology  beef breeds  non-destructive identification  SVM
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