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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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| Published in: | European food research & technology 2023-09, Vol.249 (9), p.2287-2297 |
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| container_title | European food research & technology |
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| creator | El Orche, Aimen Johnson, Joel B. |
| description | 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. |
| doi_str_mv | 10.1007/s00217-023-04300-2 |
| format | article |
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| 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 |
| title | Investigation of pre-processing NIR spectroscopic data and classification algorithms for the fast identification of chocolate-coated peanuts and sultanas |
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