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Near-infrared Spectroscopy for Rapid Classification of Fruit Spirits

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Date 2016 Aug 2
PMID 27478236
Citations 2
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Abstract

Multivariate analysis combined with near-infrared (NIR) spectral analysis was evaluated to classify fruit spirits. A total of 67 fruit spirits (12 apple, 18 apricot, 19 pear and 18 plum spirits) were analyzed. NIR spectra were collected in the wavenumber range of 4000-10,000 cm(-1). Linear discriminant analysis based on principal component analysis (PCA-LDA) and general discriminant analysis (GDA) based directly on NIR spectral data were used to classify the samples. The prediction performance of models in different wavenumber ranges was also investigated. The best PCA-LDA and GDA models gave a 100 % classification of spirits of the four fruit kinds in the wavenumber range from 5500 to 6050 cm(-1) corresponding to either the C-H stretch of the first overtones of CH3 and CH2 groups, or to compounds containing O-H aromatic groups. The results demonstrated that NIR spectroscopy could be used as a rapid method for classification of fruit spirits.

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