Xinjiang Laboratory of Native Medicinal and Edible Plant Resources Chemistry，College of Chemistry and Environmental Science，Kashgar University，Kashgar ，China
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Abstract:
The near-infrared spectra of a certain water content and different mass concentrations of luteolin solutions were collected，and the spectral peak changes were studied by means of a multivariate analysis method．A model for luteolin detection was established based on the disturbance of the water spectra．By comparing different spectral preprocessing methods，it was finally determined that the standard normal transformation（SNV） method was used for spectral preprocessing，and the partial least squares（PLS） method was used to establish a quantitative prediction model for luteolin．The results showed that the correlation coefficient R of the model selected by Kennard－Stone（KS） was 0.994 7，and the root mean square error of cross validation（RMSECV） was 1.947 8，ratio of performance to deviation（RPD） was 4.292 7，it indicated that the model was robust and the error was small．Meanwhile，the predicted root mean square error（RMSEP） of the prediction set samples was 2.077 7，and the recovery ranged from 98.0% to 105%．The results showed that the luteolin content could be determined based on the perturbation of the near-infrared spectra of water．The method is simple，rapid and accurate，and it provides a new method for the determination of bio-active ingredients．