High-Resolution Mass Spectrometry Associated with Data Mining Tools for the Detection of Pollutants and Chemical Characterization of Honey Samples
| Autor: | Christophe Junot, Mylène Marie, Fanny Leroux, Jérôme Cotton, Céline Ducruix, Jean-Claude Tabet, Bruno Corman, Simon Broudin |
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| Přispěvatelé: | Profilomic [Boulogne-Billancourt], Profilomic, Chimie Structurale Organique et Biologique (CSOB), Institut Parisien de Chimie Moléculaire (IPCM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut de Biologie et de Technologies de Saclay (IBITECS), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay |
| Rok vydání: | 2014 |
| Předmět: |
Metabolite
Food Contamination Mass spectrometry computer.software_genre 01 natural sciences Mass Spectrometry 03 medical and health sciences chemistry.chemical_compound Metabolomics Data Mining [CHIM]Chemical Sciences ComputingMilieux_MISCELLANEOUS 030304 developmental biology Pollutant 0303 health sciences Chromatography 010401 analytical chemistry food and beverages Honey General Chemistry Pesticide Honey samples Food Analysis 0104 chemical sciences chemistry 13. Climate action Environmental chemistry Data mining General Agricultural and Biological Sciences Xenobiotic computer Chromatography Liquid |
| Zdroj: | Journal of Agricultural and Food Chemistry Journal of Agricultural and Food Chemistry, American Chemical Society, 2014, 62 (46), pp.11335--11345. ⟨10.1021/jf504400c⟩ Journal of Agricultural and Food Chemistry, 2014, 62 (46), pp.11335--11345. ⟨10.1021/jf504400c⟩ |
| ISSN: | 1520-5118 0021-8561 |
| DOI: | 10.1021/jf504400c |
| Popis: | Analytical methods for food control are mainly focused on restricted lists of well-known contaminants. This paper shows that liquid chromatography-high-resolution mass spectrometry (LC/ESI-HRMS) associated with the data mining tools developed for metabolomics can address this issue by enabling (i) targeted analyses of pollutants, (ii) detection of untargeted and unknown xenobiotics, and (iii) detection of metabolites useful for the characterization of food matrices. A proof-of-concept study was performed on 76 honey samples. Targeted analysis indicated that 35 of 83 targeted molecules were detected in the 76 honey samples at concentrations below regulatory limits. Furthermore, untargeted metabolomic-like analyses highlighted 12 chlorinated xenobiotics, 1 of which was detected in lavender honey samples and identified as 2,6-dichlorobenzamide, a metabolite of dichlobenil, a pesticide banned in France since 2010. Lastly, multivariate statistical analyses discriminated honey samples according to their floral origin, and six discriminating metabolites were characterized thanks to the MS/MS experiments. |
| Databáze: | OpenAIRE |
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