期刊论文

Classification of edible vegetable oil based on laser near - infrared spectroscopy combined with extraction of characteristic wavelength

中文

中国油脂

1003-7969

2017

42

4

72-75

10.3969/j.issn.1003-7969.2017.04.016

国家“十一五”科技支撑计划项目（2009BADB9808） 武汉市科技攻关计划项目（2013010501010147） 武汉工业学院食品营养与安全重大项目培育专项（2011Z06）

本校为第一机构

提出了基于CARS、SPA和CARS - SPA特征波长提取的激光近红外光谱技术快速鉴别食用植物油种类的方法。应用光谱仪采集127个食用植物油样本的光谱数据,采用标准正态变量变换算法(SNV)、标准正态变量变换和去趋势技术联用算法(SNV - DT)对其进行预处理,采用CARS、SPA和CARS - SPA 3种方法对经过预处理的光谱数据进行特征波长提取,应用支持向量机分类方法(SVC)建立食用植物油种类定性分类校正模型,选择网格搜索算法对模型参数组合(C,g)进行寻优,确定最优参数组合。结果表明,CARS - SVC、SPA - SVC和CARS - SPA - SVC模型预测集准确率均达到96.77%,预测效果理想,其中SNV - DT - SPA - SVC模型预测效果...

To classify edible vegetable oil quickly, the method of laser near - infrared(NIR) spectroscopy combined with extration of characteristic wavelength by heavy competitive adaptive weighted sampling (CARS) , successive projections algorithm(SPA) and CARS - SPA was proposed. Spectral data of 127 edible vegetable oil samples were collected by laser NIR spectrometer, and pretreated by standard normal variate transformation (SNV) , standard normal variate transformation and de - trending (SNV - DT),then the characteristic wavelength was extracted using CARS, SPA and CARS - SPA, and the support vecto...