Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods.
Molecules
; 28(4)2023 Feb 09.
Article
in En
| MEDLINE
| ID: mdl-36838644
ABSTRACT
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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Honey
Type of study:
Prognostic_studies
Country/Region as subject:
America do norte
Language:
En
Journal:
Molecules
Journal subject:
BIOLOGIA
Year:
2023
Document type:
Article
Affiliation country:
Canadá