High-Resolution Mass Spectrometry Associated with Data Mining Tools for the Detection of Pollutants and Chemical Characterization of Honey Samples

Abstract

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.

Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study

“…Metabolomics-based approaches have emerged as important tools in assessing large chemical and biological data sets, including those related to disease pathology, 20 drug response, 21 environmental toxicity, 22 and natural products discovery. 23,24 The primary goal of metabolomics is to correlate changes in the chemical profile of a sample with a corresponding shift in macroscopic phenotype due to a perturbation.…”

Multi-class analysis for simultaneous determination of pesticides, mycotoxins, process-induced toxicants and packaging contaminants in tea

“…In addition, considering the low sensitivity and high matrix effects for some compounds, changes were required. In particular, an evaporation step was needed and acidified ACN was selected to recover the dry residue as inspired by Cotton et al (2014). Since this solvent was unable to recover fumonisins B1 and B2, two more options were further investigated to improve the efficiency of the extraction: 1) increasing the percentage of FA or 2) adding MeOH to the mixture (Hans G. J.…”

Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry

“…Similarly, a 26 contaminant standard mixture was spiked at different levels into orange juice to determine the practicality of a statistical approach using a nested analysis of variance (ANOVA) and PCA to identify contaminants in food samples [73]. A similar workflow was also demonstrated in honey where a banned pesticide was detected and identified in one of the samples by mining the data for chlorine-containing molecular species using partial least squares discriminant analysis (PLS-DA) and PCA [74]. Most instrument vendors offer chemometric software tools to analyze their own data formats, although vendor neutral software packages are also available, such as XCMS [75].…”