Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods
To address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/28/4/1656 |
| _version_ | 1797618998483877888 |
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| author | Ian W. Burton Mohsen Kompany-Zareh Sophie Haverstock Jonathan Haché Camilo F. Martinez-Farina Peter D. Wentzell Fabrice Berrué |
| author_facet | Ian W. Burton Mohsen Kompany-Zareh Sophie Haverstock Jonathan Haché Camilo F. Martinez-Farina Peter D. Wentzell Fabrice Berrué |
| author_sort | Ian W. Burton |
| collection | DOAJ |
| description | To address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology, NMR data were recorded in triplicate on a 700 MHz NMR spectrometer equipped with a cryoprobe, and the data analysis led to the identification and quantification of 33 compounds characteristic of the chemical composition of honey. The high proportion of Canadian honey in the library provided a unique opportunity to apply multivariate statistical methods including PCA, PLS-DA, and SIMCA in order to differentiate Canadian samples from the rest of the world. Through satisfactory model validation, both PLS-DA as a discriminant modeling technique and SIMCA as a class modeling method proved to be reliable at differentiating Canadian honey from a diverse set of honeys with various countries of origins and floral types. The replacement method of optimization was successfully applied for variable selection, and trigonelline, proline, and ethanol at a lower extent were identified as potential chemical markers for the discrimination of Canadian and non-Canadian honeys. |
| first_indexed | 2024-03-11T08:21:49Z |
| format | Article |
| id | doaj.art-1b36068f47ca42ab868f4fcb5777746a |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-11T08:21:49Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-1b36068f47ca42ab868f4fcb5777746a2023-11-16T22:21:28ZengMDPI AGMolecules1420-30492023-02-01284165610.3390/molecules28041656Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical MethodsIan W. Burton0Mohsen Kompany-Zareh1Sophie Haverstock2Jonathan Haché3Camilo F. Martinez-Farina4Peter D. Wentzell5Fabrice Berrué6Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, CanadaTrace Analysis Research Centre, Department of Chemistry, Dalhousie University, P.O. Box 15000, Halifax, NS B3H 4R2, CanadaAquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, CanadaCanadian Food Inspection Agency, 1400 Merivale Rd, Ottawa, ON K1A 0Y9, CanadaAquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, CanadaTrace Analysis Research Centre, Department of Chemistry, Dalhousie University, P.O. Box 15000, Halifax, NS B3H 4R2, CanadaAquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, CanadaTo address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology, NMR data were recorded in triplicate on a 700 MHz NMR spectrometer equipped with a cryoprobe, and the data analysis led to the identification and quantification of 33 compounds characteristic of the chemical composition of honey. The high proportion of Canadian honey in the library provided a unique opportunity to apply multivariate statistical methods including PCA, PLS-DA, and SIMCA in order to differentiate Canadian samples from the rest of the world. Through satisfactory model validation, both PLS-DA as a discriminant modeling technique and SIMCA as a class modeling method proved to be reliable at differentiating Canadian honey from a diverse set of honeys with various countries of origins and floral types. The replacement method of optimization was successfully applied for variable selection, and trigonelline, proline, and ethanol at a lower extent were identified as potential chemical markers for the discrimination of Canadian and non-Canadian honeys.https://www.mdpi.com/1420-3049/28/4/1656nuclear magnetic resonance (NMR)honeyquantitationmultivariate statistical analysesfood adulteration |
| spellingShingle | Ian W. Burton Mohsen Kompany-Zareh Sophie Haverstock Jonathan Haché Camilo F. Martinez-Farina Peter D. Wentzell Fabrice Berrué Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods Molecules nuclear magnetic resonance (NMR) honey quantitation multivariate statistical analyses food adulteration |
| title | Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods |
| title_full | Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods |
| title_fullStr | Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods |
| title_full_unstemmed | Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods |
| title_short | Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods |
| title_sort | analysis and discrimination of canadian honey using quantitative nmr and multivariate statistical methods |
| topic | nuclear magnetic resonance (NMR) honey quantitation multivariate statistical analyses food adulteration |
| url | https://www.mdpi.com/1420-3049/28/4/1656 |
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