摘要
为了实现对山西老陈醋品种的快速鉴别,应用可见/近红外光谱透射技术,结合化学计量学方法,进行了山西老陈醋品种的判别分类试验研究。对4个不同品种共240个山西老陈醋样品采集其光谱数据,结合主成分分析和神经网络技术分别对山西陈醋原始光谱、一阶微分光谱、二阶微分光谱进行了判别分析。结果表明:可见/近红外原始光谱结合主成分分析神经网络判别分析法的分析结果最优,校正集正确分类的百分比达92.1%,预测集达85.0%;二阶微分光谱分析结果最差。
The feasibility of using visible and near infrared（Vis/NIR） transmission spectroscopy for classification of the Shanxi mature vinegars with different varieties,marked as DH,GD,NHF and ST,was analyzed in the present research.A total of 240 Shanxi mature vinegars was tested in the wavelength of range 400~2000 nm and the principal component analysis（PCA） combined with artificial neural network（ANN） was applied to build discrimination model.The results indicated that principal component analysis combined with artificial neural network can be used to discriminate Shanxi mature vinegars varieties to the raw spectra.The percentage of samples correctly classified 92.1% and 85.0% for the calibration and prediction set,respectively.
出处
《山西农业大学学报（自然科学版）》
CAS
2010年第4期309-311,共3页
Journal of Shanxi Agricultural University(Natural Science Edition)
基金
山西省科技攻关项目(20100311066-5)
山西农业大学科技创新基金(2008019)
关键词
近红外透射光谱
主成分分析
神经网络
陈醋
品种鉴别
Vis/NIR transmission spectroscopy
Mature vinegar
Principal component analysis
Artificial neural network
Qualitative analysis
