可见/近红外联合UVE-PLS-LDA鉴别压榨和浸出山茶油

山茶油是我国特有的优质食用油，而压榨山茶油营养品质优于浸出山茶油。采用可见/近红外光谱技术对压榨和浸出山茶油进行鉴别研究。在350～1 800 nm波段范围内采集压榨和浸出山茶油样本的透射光谱，利用无信息变量消除(UVE)方法进行波长变量优选，剔除无用波长变量，并应用偏最小二乘-线性判别分析(PLS-LDA)建立鉴别分类模型。最后，利用鉴别分类模型对未参与建模的26个预测集样本进行鉴别。研究结果表明，UVE-PLS-LDA是一种有效的鉴别分类方法，所建立的鉴别分类模型能较好地对压榨和浸出山茶油进行鉴别，校正集和预测集样本的鉴别正确率均为100%。因此，可见/近红外光谱联合UVE-PLS-LDA方法鉴别压榨和浸出山茶油是可行的。

Discrimination of Pressed and Extracted Camellia Oils by Vis/NIR Spectra Combined with UVE-PLS-LDA

Camellia oil is a special and high quality edible oil in China, and quality of pressed camellia oils is superior to extracted camellia oils. The objective of the present research was to discriminate pressed and extracted camellia oils by visible/near infrared (Vis/NIR) spectroscopy. The transmission spectra of pressed and extracted camellia oil samples were acquired using a QualitySpec spectrometer in the wavelength range of 350~1 800 nm. Uninformative variable elimination (UVE) was used to select informative wavelength variables, and eliminate uninformative wavelength variables, then partial least squares combined with linear discriminant analysis (PLS-LDA) was used to develop classification model. At last, the classification model was used to discriminate 26 samples in the prediction set. The results indicate that UVE-PLS-LDA is an efficient discrimination and classification method, pressed and extracted camellia oils can be discriminated well by the classification model developed by UVE-PLS-LDA, the accurate rate is 100% for both samples in the calibration and prediction sets. So, Vis/NIR spectra combined with UVE-PLS-LDA is an effective method for discriminating pressed and extracted camellia oils.