Determination of the Geographical Origin of Walnuts (
FT-NIR
Juglans regia L.
data pre-processing
geographical origin
walnut
Journal
Foods (Basel, Switzerland)
ISSN: 2304-8158
Titre abrégé: Foods
Pays: Switzerland
ID NLM: 101670569
Informations de publication
Date de publication:
13 Dec 2020
13 Dec 2020
Historique:
received:
31
10
2020
revised:
10
12
2020
accepted:
11
12
2020
entrez:
16
12
2020
pubmed:
17
12
2020
medline:
17
12
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33322182
pii: foods9121860
doi: 10.3390/foods9121860
pmc: PMC7764259
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Bundesministerium für Ernährung und Landwirtschaft (BMEL)
ID : 2816500914
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