Literature DB >> 33799063

ICP-MS-based ionomics method for discriminating the geographical origin of honey of Apis cerana Fabricius.

Fanhua Wu1, Haoan Zhao1, Jing Sun1, Jianbo Guo2, Liming Wu3, Xiaofeng Xue3, Wei Cao4.   

Abstract

The identification of geographical origin is an important factor in evaluating the authenticity of honey. However, at present, there are few studies concerning the honey of Apis cerana Fabricius (A. cerana, Asiatic honeybee). To identify geographical origin, we used two common methods (multi-physicochemical parameters and phenolic chromatographic fingerprints) but achieved only poor identification. To compensate for this shortcoming, we established an ICP-MS-based ionomics method using 18 elements in 27 A. cerana honey samples from three different areas in Shaanxi Province, China. Multivariate analysis showed that significant differences in contents can be used to discriminate the geographical origin of A. cerana honey. The method was further validated using an independent test set of 11 samples with 90.91% accuracy, demonstrating its potential for the identification and prediction of the geographical origin of honey.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Apis cerana Fabricius; Geographical origin; Honey; ICP-MS; Ionomics; Mineral element

Year:  2021        PMID: 33799063     DOI: 10.1016/j.foodchem.2021.129568

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  1 in total

1.  Multi-Elemental Composition Data Handled by Chemometrics for the Discrimination of High-Value Italian Pecorino Cheeses.

Authors:  Francesca Di Donato; Martina Foschi; Nadia Vlad; Alessandra Biancolillo; Leucio Rossi; Angelo Antonio D'Archivio
Journal:  Molecules       Date:  2021-11-15       Impact factor: 4.411

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.