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Discrimination of adulterated milk using temperature-perturbed two-dimensional infrared correlation spectroscopy and multivariate analysis
[Display omitted] •The discrimination method for adulterated milk was proposed using temperature-perturbed 2D IR correlation spectroscopy.•The discrimination accuracy of two brands of pure and adulterated milk was 100% by temperature-perturbed 2D IR correlation spectroscopy.•The discrimination accur...
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Published in: | Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Molecular and biomolecular spectroscopy, 2022-10, Vol.278, p.121342, Article 121342 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | [Display omitted]
•The discrimination method for adulterated milk was proposed using temperature-perturbed 2D IR correlation spectroscopy.•The discrimination accuracy of two brands of pure and adulterated milk was 100% by temperature-perturbed 2D IR correlation spectroscopy.•The discrimination accuracy of two brands of pure and adulterated milk was 77.8 % by conventional 3D stacked map.•Temperature-perturbed 2D correlation spectra showed better performance thanconventional 3D stacked map.
The discrimination method for adulterated milk is proposed based on temperature-perturbed two-dimensional (2D) infrared correlation spectroscopy and N-way partial least squares discriminant analysis (NPLS-DA). Two brands of pure and adulterated milk samples were prepared. The mid-infrared spectra of all samples were obtained from 30 ℃ to 55 ℃ with an interval of 5 ℃. Under the perturbation of temperature, synchronous 2D correlation spectra were calculated to build discrimination models of pure milk and adulterated milk. In comparison, the NPLS-DA models were built based on three-dimensional (3D) stacked map (sample × temperature × wavenumber variable). For the NPLS-DA models of two brands of milk, the discrimination accuracy of unknown samples in the prediction set is 100% using temperature-perturbed 2D infrared correlation spectra, versus 77.8% using conventional 3D stacked map. The proposed method can be used as an alternative way for classifying pure and adulterated milk. |
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ISSN: | 1386-1425 |
DOI: | 10.1016/j.saa.2022.121342 |