Abstract: Forty Chinese wolfberry samples from 8 different regions of China were scanned with a near infrared (NIR) spectrophotometer. The original spectra were preprocessed by the first derivative (5 point smoothing) and standard normal variate (SNV) and were subjected to principle component analysis over the wavelength range of 950 nm to 1650 nm, in which the number of principal components was selected as 3. A robust model indicating each geographic origin of Chinese wolfberry was achieved using the SIMCA (Simple Modelling of Class Analogy) pattern recognition method and its reliability at the 5% significance level was validated. The results revealed that the model indicating samples from Qinghai exhibited a recognition rate of 80% in the calibration set, the recognition rates for other 7 cultivation regions were all 100%, and the rejection rates were 100%, 100%, 97%, 100%, 91%, 94%, 97% and 100%, respectively. All the recognition rates of the 8 cultivation regions were 100% in the validation set, and the rejection rates were 100%, 100%, 100%, 100%, 75%, 88%, 100% and 100%, respectively. These results support the feasibility of applying NIR to identify the geographic origin of Chinese berry.

Key words: near infrared spectroscopy, identification, Chinese wolfberry, origin traceability