基于可见/近红外高光谱成像技术的牛肉品种鉴别

被引：27

作者：

王彩霞

王松磊

贺晓光

董欢

机构：

[1] 宁夏大学农学院

来源：

食品工业科技 | 2019年 / 40卷 / 12期

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;

D O I：

10.13386/j.issn1002-0306.2019.12.039

中图分类号：

O657.3 [光化学分析法（光谱分析法）]; TS251.52 [];

学科分类号：

070302 [分析化学];

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。

引用

页码：241 / 247

页数：7

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