| Literature DB >> 33813204 |
Hongru Zhang1, Wenyuan Liu2, Qingshan Shen1, Laiyu Zhao3, Chunhui Zhang4, Aurore Richel5.
Abstract
Consumers have an increasing concern in the provenance of the foods they consume. Methods for discriminating geographical origins and species of cattle bone product are essential to provide veracious information for consumers and avoid the adulteration and inferior problems. In this study, 50 element contents of a total of 143 cattle bone samples from eight producing regions in China, were determined by inductively coupled plasma mass spectrometry (ICP-MS). Element contents were used as chemical indicators to discriminate species and geographical origins of cattle bone samples by multivariate data analysis, including hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). The K-fold cross validation accuracy for species and geographical origin discrimination was 99.3% and 94.5%, respectively. This study reveals that multi-element analysis accompanied by LDA is an effective technique to ensure the information reliability of cattle bone samples, and this strategy may be a potential tool for standardizing market.Entities:
Keywords: Cattle bone; Discrimination; Geographical origin; ICP-MS; Multi-element; Species
Year: 2021 PMID: 33813204 DOI: 10.1016/j.foodchem.2021.129619
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514