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- W2912543985 abstract "This work aims to sort cocoa beans according to chocolate sensory quality and phenolic composition. Prior to the study, cocoa samples were processed into chocolate in a standard manner, and then the chocolate was characterized by sensory analysis, allowing sorting of the samples into four sensory groups. Two objectives were set: first to use average mass spectra as quick cocoa-polyphenol-extract fingerprints and second to use those fingerprints and chemometrics to select the molecules that discriminate chocolate sensory groups. Sixteen cocoa polyphenol extracts were analyzed by liquid chromatography–low-resolution mass spectrometry. Averaging each mass spectrum provided polyphenolic fingerprints, which were combined into a matrix and processed with chemometrics to select the most meaningful molecules for discrimination of the chocolate sensory groups. Forty-four additional cocoa samples were used to validate the previous results. The fingerprinting method proved to be quick and efficient, and the chemometrics highlighted 29 m/z signals of known and unknown molecules, mainly flavan-3-ols, enabling sensory-group discrimination." @default.
- W2912543985 created "2019-02-21" @default.
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- W2912543985 date "2019-02-14" @default.
- W2912543985 modified "2023-10-14" @default.
- W2912543985 title "Fast Discrimination of Chocolate Quality Based on Average-Mass-Spectra Fingerprints of Cocoa Polyphenols" @default.
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- W2912543985 doi "https://doi.org/10.1021/acs.jafc.8b06456" @default.
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