Rapid Classification of Petroleum Waxes: A Vis-NIR Spectroscopy and Machine Learning Approach

Petroleum-derived waxes are used in the food industry as additives to provide texture and as coatings for foodstuffs such as fruits and cheeses. Therefore, food waxes are subject to strict quality controls to comply with regulations. In this research, a combination of visible and near-infrared (Vis-...

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Veröffentlicht in:	Foods Jg. 12; H. 18; S. 3362
Hauptverfasser:	Barea-Sepúlveda, Marta, Calle, José Luis P., Ferreiro-González, Marta, Palma, Miguel
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.09.2023 MDPI
Schlagworte:	Additives Algorithms Analysis Automation Chemical composition Classification Cluster analysis Cost analysis cost effectiveness Data mining Discriminant analysis Food additives Food industry Food science food waxes Fruits Human error Hydrocarbons Industrial applications Infrared spectroscopy Learning algorithms Lubricating oils Machine learning Near infrared radiation Nitrofurantoin Odors paraffins Pattern recognition Petroleum Petroleum industry petroleum-derived products principal component analysis Principal components analysis Quality assessment Quality control spectral analysis Spectroscopy Spectrum analysis Supervised learning support vector machine Support vector machines Test methods texture Unsupervised learning visible–near-infrared spectroscopy Wavelengths Waxes
ISSN:	2304-8158, 2304-8158
Online-Zugang:	Volltext
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