Pure oil-tea camellia seed oil and oil-tea camellia seed oils adulterated with 1%-10% of rapeseed oils were discriminated and classified by visible/near infrared (Vis/NIR) spectra combined with uninformative variable elimination-genetic algorithm (UVE-GA), and classification model was developed by linear discriminant analysis (LDA). The results indicated that UVE-GA was an efficient wave length variable selection method, and the classification model could be simplified and improved by UVE-GA. UVE-GA-LDA classification model was suitable for discriminating oil-tea camellia seed oil adulterated with more than 2% of rapeseed oil, and the correction rate of classification was 100%, while the correction rate of classification for oil-tea camellia seed oil adulterated with 1% of rapeseed oil was only 50%, which need to be improved. |