NMR based metabolomic approach for evaluation of Vietnamese honey

Abstract

Honey represents a natural, agricultural product endowed with valuable nutritional and pharmacological functions. Therefore, the classification and evaluation of honey has always been a challenge for chemical analysis, especially when honey adulteration is increasing. The traditional methods for quality control of honey is currently based on physicochemical methods, which is often relatively high cost and time‐consuming. NMR based metabolomics is a metabolomic fingerprinting approach for NMR data using chemometric tools. This combined approach can be apply in food analysis for origin discrimination, biomarker discovery and authenticity screening. The present study demonstrated the capability of the 1H NMR based metabolomics for evaluation of 27 NMR spectra of 09 selected honey samples from Viet Nam. 1H NMR analysis was conducted immediately on collected honey samples, without extraction. Unsupervised PCA multivariate data analysis, applied on 1H NMR experimental data, used to characterize and classify honey samples according to their origin and quality. Different metabolites specific for each botanical origins of honey samples also determined. The obtained results of the demonstration suggests that this combined approach could be useful to develop generally applicable metabolomic approaches to valuate honey products as well as other agricultural products.

NMR-Based Approaches in the Study of Foods

“…Multivariate statistics (PCA) of NMR spectrum-derived variables enabled authors to clearly distinguish the three fractions and the whole-grain flour samples. The NMR profiling approach has been largely used to study the same food aspects described for the untargeted NMR analysis: pedoclimatic factors (olive oil [99,100]), geographical origin (wines [101,102], olive oils [103][104][105], cocoa beans [106], coffee [41], saffron [107], asparagus [108], walnuts [109], hazelnut [110], honey [111]), botanical origin (honey [112]), ripening (tomatoes (64), passion fruit ( 69)), post-harvesting (peaches, tomatoes, and plums [113]), and the manufacturer (beer [114], coffee [44]). Food authenticity (seeds [115], olive oil [116], beer [117], honey [118], avocado oil [119]) has been also studied with the described untargeted approach.…”

Identifying type of sugar adulterants in honey: Combined application of NMR spectroscopy and supervised machine learning classification

“…The inherent strength of NMR (target and non-target based) permits identification and quantification of all possible monosaccharides, disaccharides, oligosaccharides, acids, HMF, and amino-acids, separately from different well-resolved chemical shifts. These features can be easily exploited to discriminate geographical and botanical origins of honey since each honey variety has its unique NMR spectral features/signatures ( Girelli et al, 2020 ; Spiteri et al, 2020 ; Boffo et al, 2012 ; Ribeiro et al, 2014 ; Nguyen et al, 2017 ; Luong et al, 2019 ; Pu'scion-Jakubik et al, 2020 ). Thus, to detect the authenticity of honey under testing, a specific honey NMR database with the respective authentic honey samples is required.…”

LC-HRMS-Based Non-Targeted Metabolomics for the Assessment of Honey Adulteration with Sugar Syrups: A Preliminary Study

“…As far as we know, few metabolomic studies have been carried out on honey to date. Most of them were aimed at determining the botanical origin of honey in terms of product authenticity [ 28 , 29 , 30 ]. However, Bachmann et al (2022) [ 31 ] analyzed the metabolic profiles of syrups of different botanical origins with the NMR technique, identifying a marker for the detection of food fraud in each.…”