Background: Food adulteration is a global concern, whether it takes place intentionally or incidentally. In Canada, maple syrup is susceptible to being adulterated with cheaper syrups such as corn, beet, cane syrups, and many more due to its high price and economic importance.

Results: In this study, the use of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy was investigated to detect maple syrups adulterated with 15 different sugar syrups at different concentration levels. The spectra were collected in the range of 4000-650 cm in the absorbance unit. These spectra were used to build six libraries and three models. A method that is capable of performing a qualitative library search using a similarity search, which is based on the first derivative correlation search algorithm, was developed. This method was further evaluated and proved to be able to capture adulterated and reject non-adulterated maple syrups, belonging to the color grades golden and amber maple syrups, with an accuracy of 93.9% and 92.3%, respectively. However, for the maple syrup belonging to the dark color grade, this method demonstrated low specificity of 33.3%, and for this reason it was only able to adequately detect adulterated samples from the non-adulterated ones with an accuracy of 81.4%.

Conclusion: This simple and rapid method has strong potential for implementation in different stages of the maple syrup supply chain for early adulteration detection, particularly for golden and amber samples. Further evaluation and improvements are required for the dark color grade. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Download full-text PDF

Source
http://dx.doi.org/10.1002/jsfa.13073DOI Listing

Publication Analysis

Top Keywords

maple syrup
16
maple syrups
12
atr-ftir spectroscopy
8
detect maple
8
golden amber
8
dark color
8
color grade
8
maple
7
syrups
7
adulterated
5

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!