{"title":"Brazilian honey: Metabolomic analysis and characterization by 1D- and 2D-nuclear magnetic resonance (NMR) spectroscopy and chemometrics","authors":"Aline Nunes , Mauricio Luis Sforça , Silvana Aparecida Rocco , Caroline Schmitz , Gadiel Zilto Azevedo , Beatriz Rocha dos Santos , Sidnei Moura , Marcelo Maraschin","doi":"10.1016/j.foodres.2025.116104","DOIUrl":null,"url":null,"abstract":"<div><div>Honey is a complex matrix that contains a wide range of compounds. This rich composition is influenced by diverse environmental factors, including geographic and botanical origin. Honey has been among the most commonly tampered foods worldwide, with improvements in techniques to do it. Accordingly, there is a recurring need for new techniques and methods to assess the honey's metabolic profiles to distinguish adulterated from non-tampered samples. In this sense, this study aimed to determine the chemical profiles of honey samples from the eleven agroecological zones of the Santa Catarina State (southern Brazil), collected in the 2019–2020 and 2020–2021 harvest seasons through 1D- and 2D-NMR. As a result, a series of metabolites was identified and their concentrations measured in samples. Further, the metabolomic dataset was used for building descriptive models through chemometric techniques, in order to discriminate honey samples according to their geographic and botanical origins and harvest season effect. Twenty-one metabolites were identified, with predominance of glucose and fructose in all samples. Two other carbohydrates (sucrose and maltose) were identified in lower concentrations, in addition to amino acids, organic acids, ketone, alcohol, ester, and alkaloids. No discrepant <sup>1</sup>H NMR resonances that could indicate fraud were detected in the spectra. By PCA, it was possible to find clusters with similar geographic origins, i.e., agroecological zones, and botanical origins. In this regard, patterns of composition were detected for honey samples of <em>Eucalyptus</em> spp. and <em>Hovenia dulcis</em> species, which presented acetoin and kynurenate, respectively, in higher concentrations. Taking together, the results allowed demonstrating that NMR spectroscopy coupled to chemometrics is an effective experimental approach to characterize Brazilian honey regarding their geographic origin and season of collection, despite the huge floral diversity available in that country for bee forage.</div></div>","PeriodicalId":323,"journal":{"name":"Food Research International","volume":"207 ","pages":"Article 116104"},"PeriodicalIF":7.0000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Research International","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0963996925004417","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Honey is a complex matrix that contains a wide range of compounds. This rich composition is influenced by diverse environmental factors, including geographic and botanical origin. Honey has been among the most commonly tampered foods worldwide, with improvements in techniques to do it. Accordingly, there is a recurring need for new techniques and methods to assess the honey's metabolic profiles to distinguish adulterated from non-tampered samples. In this sense, this study aimed to determine the chemical profiles of honey samples from the eleven agroecological zones of the Santa Catarina State (southern Brazil), collected in the 2019–2020 and 2020–2021 harvest seasons through 1D- and 2D-NMR. As a result, a series of metabolites was identified and their concentrations measured in samples. Further, the metabolomic dataset was used for building descriptive models through chemometric techniques, in order to discriminate honey samples according to their geographic and botanical origins and harvest season effect. Twenty-one metabolites were identified, with predominance of glucose and fructose in all samples. Two other carbohydrates (sucrose and maltose) were identified in lower concentrations, in addition to amino acids, organic acids, ketone, alcohol, ester, and alkaloids. No discrepant 1H NMR resonances that could indicate fraud were detected in the spectra. By PCA, it was possible to find clusters with similar geographic origins, i.e., agroecological zones, and botanical origins. In this regard, patterns of composition were detected for honey samples of Eucalyptus spp. and Hovenia dulcis species, which presented acetoin and kynurenate, respectively, in higher concentrations. Taking together, the results allowed demonstrating that NMR spectroscopy coupled to chemometrics is an effective experimental approach to characterize Brazilian honey regarding their geographic origin and season of collection, despite the huge floral diversity available in that country for bee forage.
期刊介绍:
Food Research International serves as a rapid dissemination platform for significant and impactful research in food science, technology, engineering, and nutrition. The journal focuses on publishing novel, high-quality, and high-impact review papers, original research papers, and letters to the editors across various disciplines in the science and technology of food. Additionally, it follows a policy of publishing special issues on topical and emergent subjects in food research or related areas. Selected, peer-reviewed papers from scientific meetings, workshops, and conferences on the science, technology, and engineering of foods are also featured in special issues.