Investigation of pre-processing NIR spectroscopic data and classification algorithms for the fast identification of chocolate-coated peanuts and sultanas

Chocolate-coated confectionery, including fruits and nuts, is an increasingly popular snack food. Non-destructive discrimination of the core composition could be useful for quality assurance purposes, such as ensuring the absence of peanuts in a batch of chocolate-coated sultanas. This study investi...

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Bibliographic Details
Published in:European food research & technology 2023-09, Vol.249 (9), p.2287-2297
Main Authors: El Orche, Aimen, Johnson, Joel B.
Format: Article
Language:English
Subjects:
Agriculture
Algorithms
Analytical Chemistry
Biotechnology
Chemistry
Chemistry and Materials Science
Chocolate
Classification
Coatings
Confectionery
Data analysis
Discriminant analysis
Food
Food Science
Forestry
Infrared spectra
Infrared spectroscopy
Investigations
Machine learning
Manufacturers
Near infrared radiation
Nuts
Optimization
Original Paper
Peanuts
Principal components analysis
Quality assurance
Quality control
Spectrum analysis
Support vector machines
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Summary:Chocolate-coated confectionery, including fruits and nuts, is an increasingly popular snack food. Non-destructive discrimination of the core composition could be useful for quality assurance purposes, such as ensuring the absence of peanuts in a batch of chocolate-coated sultanas. This study investigated the optimum pre-processing methods and discrimination algorithms for identifying chocolate-coated peanuts and sultanas from their near-infrared (NIR) spectra. The best-performing results were found using partial least squares discriminant analysis (PLS-DA) and principal component analysis with linear discriminant analysis (PCA-LDA), which both demonstrated 100% classification accuracy when applied to the validation set. Principal component analysis with support vector machine (PCA-SVM) showed slightly poorer results, particularly when using non-optimal pre-processing techniques. In general, the most accurate results were found when using either the unprocessed or SNV-processed spectral data. This work supports the prospect of using near-infrared spectroscopy for the quality assurance in the manufacture or wholesale of panned chocolate goods.
ISSN:1438-2377
1438-2385
DOI:10.1007/s00217-023-04300-2