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Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry
Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry
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Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry
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Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry
Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry

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Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry
Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry
Journal Article

Identification and Detection of Adulterations of Salmon Caviar by PCR, IR Spectrometry, and Digital Coloriometry

2025
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Overview
A possibility of identifying and establishing adulterations of salmon caviar by a simple and an available method using PCR, Fourier transform IR spectrometry, digital colorimetry with the chemometric processing of the analysis results is shown. The PCR method is used to determine the species of salmon caviar. No salmon DNA in the studied caviar samples, as well as the presence of DNA of other fish, indicates the adulteration of the caviar products. Near- and mid-region Fourier transform infrared spectroscopy makes it possible to distinguish between the natural and imitation caviar after processing diffuse reflectance spectra by principal component analysis and hierarchical cluster analysis. The above methods are combined with a simpler and a cheaper colorimetric analysis method. Hand-made devices with LEDs emitting in the UV and IR regions are used. The analytical signal is recorded using smartphones with specialized applications. Chemometric processing of the spectral characteristics of the samples makes it possible to distinguish natural caviar from imitation and structured caviar: in the principal component analysis and hierarchical cluster analysis, points of the analyzed samples are located in different quadrants and clusters.