Quality Assessment and Classification of Goji Berry by an HPLC-based Analytical Platform Coupled with Multivariate Statistical Analysis

Abstract

Here, a comprehensive approach, based on chromatographic profiles and chemometric methods, was developed for the simultaneous qualitative and quantitative determinations of goji berry. High-performance liquid chromatography with diode-array detection (HPLC-DAD) was employed to acquire the fingerprints of 67 water extracts of goji berries of different varieties and growing years. The results indicated that the correlation coefficients among the samples of the same varieties and growing years were ˃ 0.900, although they varied from 0.726 to 0.986 among samples of different varieties and growing years. Based on these data, the chemometric analysis was applied. Further, principal component analysis (PCA), hierarchical clustering analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied for the discrimination of the varieties and the growing years. Moreover, nine marker compounds were obtained as potential references for goji berries of different growing years and 10 other marker components contributed significantly to the varieties differentiation. Precisely, the goji berries of Ningqi No. 7 (N7) and Ningqi No. 9 (N9) were of higher contents than the other three varieties (Ningqi No. 1 (N1), Ningqi No. 5 (N5), and Zhongke Luchuan (ZKLC)), indicating that N7 and N9 were of higher qualities than the others. Conclusively, the chromatographic fingerprint, combined with chemometric methods, could be employed to differentiate the raw materials of different varieties and growing years. Additionally, it could be employed as a rapid and reliable tool for the quality control (QC) of goji berries.