Journal
FOODS
Volume 9, Issue 12, Pages -Publisher
MDPI
DOI: 10.3390/foods9121860
Keywords
walnut; FT-NIR; geographical origin; data pre-processing; Juglans regia L
Categories
Funding
- Federal Ministry of Food and Agriculture (German: Bundesministerium fur Ernahrung und Landwirtschaft, BMEL) by a decision of the German parliament (German: Bundestag) [2816500914]
- Federal Institute for Agriculture and Food (German: Bundesanstalt fur Landwirtschaft und Ernahrung, BLE)
Ask authors/readers for more resources
The prices of walnuts vary according to their geographical origin and, therefore, offer a financial incentive for adulteration. A reliable analysis method is required to quickly detect possible misdeclarations and thus prevent food fraud. In this study, a method to distinguish between seven geographical origins of walnuts using Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics as a fast, versatile, and easy to handle analytical tool was developed. NIR spectra of 212 ground and afterwards freeze-dried walnut samples, harvested in three consecutive years (2017-2019), were collected. We optimized the data pre-processing by applying and evaluating 50,545 different pre-processing combinations, followed by linear discriminant analysis (LDA) which was confirmed by nested cross-validation. The results show that in the scope of our research minimal pre-processing led to the best results: By applying just multiplicative scatter correction (MSC) and median centering, a classification accuracy of 77.00% +/- 1.60% was achieved. Consequently, this complex model can be used to answer economically relevant questions e.g., to distinguish between European and Chinese walnuts. Furthermore, the great influence of the applied pre-processing methods, e.g., the selected wavenumber range, on the achieved classification accuracy is shown which underlines the importance of optimization of the pre-processing strategy.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available