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Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies
被引:38
|作者:
Tan, Jin
[1
]
Li, Rong
[1
]
Jiang, Zi-Tao
[1
]
机构:
[1] Tianjin Univ Commerce, Coll Biotechnol & Food Sci, Tianjin Key Lab Food Biotechnol, Tianjin 300134, Peoples R China
来源:
基金:
中国国家自然科学基金;
关键词:
Beers;
Manufacturer;
Data fusion;
Synchronous fluorescence;
UV and visible;
Principal component analysis (PCA);
Linear discriminant analysis (LDA);
MULTIVARIATE-ANALYSIS;
PATTERN-RECOGNITION;
DIFFERENTIATION;
DISCRIMINATION;
CONFIRMATION;
ADULTERATION;
IDENTITY;
PROFILE;
SAMPLES;
WINES;
D O I:
10.1016/j.foodchem.2015.03.085
中图分类号:
O69 [应用化学];
学科分类号:
081704 ;
摘要:
We report an application of data fusion for chemometric classification of 135 canned samples of Chinese lager beers by manufacturer based on the combination of fluorescence, UV and visible spectroscopies. Right-angle synchronous fluorescence spectra (SFS) at three wavelength difference Delta lambda = 30, 60 and 80 nm and visible spectra in the range 380-700 nm of undiluted beers were recorded. UV spectra in the range 240-400 nm of diluted beers were measured. A classification model was built using principal component analysis (PCA) and linear discriminant analysis (LDA). LDA with cross-validation showed that the data fusion could achieve 78.5-86.7% correct classification (sensitivity), while those rates using individual spectroscopies ranged from 42.2% to 70.4%. The results demonstrated that the fluorescence, UV and visible spectroscopies complemented each other, yielding higher synergic effect. (C) 2015 Elsevier Ltd. All rights reserved.
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页码:30 / 36
页数:7
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