Novel method for the producing area identification of Zhongning Goji berries by electronic nose.

Abstract

High-quality Zhongning Goji berries (ZNG) are illegally adulterated in the market by adding non-ZNG (NZNG). An accurate, rapid, and effective approach for the producing area identification of ZNG is needed to protect the geographical indications of Goji berry products and to ensure fair trade. Samples from different regions were collected and their odors were detected by an electronic nose (E-nose). Principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) were employed to build identification models. The E-nose models were further verified by gas chromatography-mass spectrometry (GC-MS). The identification rates of the PCA, CA, and LDA models were 91.0%, 98.9%, and 100%, respectively. The PCA and CA models presented good results, and the LDA model showed optimum performance. These conditions indicate the feasibility of using the E-nose technique for ZNG identification. GC-MS analysis revealed differences and similarities in total ion current chromatograms between ZNG and NZNG.