Abstract:To solve the problems in sale and identification of Lycium barbarum L, a quantitative anlysis method was developed based on near infrared spectrum for quantitative analysis of chemical composition of Lycium barbarum L Partial least-squares regression (PLS) was introduced for estabulishment of model calibration, in which thirty samples were used for the calibration set and ten samples were used for the prediction set. Then the chemical values of Lycium barbarum L. were calculated. The result showed that using this prediction model of Lycium barbarum L. composition, the calibrating correlation coefficient RC were above 0.93 and cross-check correlation coefficients RCV were above 0.83. The mean square error correction RMSEC values of each component were smaller than those of the cross check all variance RMSEP values. The predicted values had a good correlation with the chemistry values. Both of chemical value and predictive value of Lycium barbarum L reached quantitative standard, indicating that this method can be used for quantitative analysis of chemical composition of Lycium barbarum L .
