| Literature DB >> 27979067 |
Qi Li1, Xiuzhu Yu2, Lirong Xu1, Jin-Ming Gao3.
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.Entities:
Keywords: 1-Hydroxy-2-propanone (PubChem CID: 8299); 1-Octen-3-ol (PubChem CID 18827); 2,5-Octanedione (PubChem CID: 6420399); 2-Ethylcyclohexanol (PubChem CID: 19576); 6-Methyl-6-nitroheptan-2-one (PubChem CID: 537587); Anethole (PubChem CID: 637563); Copaene (PubChem CID: 70678558); Cysteine sulfinic acid (PubChem CID: 109); E-nose; Identification; Methylhydrazine (PubChem CID: 6061); Pentadecane (PubChem CID: 12391); Producing area; Zhongning Goji berry
Mesh:
Year: 2016 PMID: 27979067 DOI: 10.1016/j.foodchem.2016.11.049
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514