Discrimination of Chinese yellow wine from different origins based on flavor fingerprint

• Autorzy: Chen Tong , Qi Xingpu , Chen Mingjie , Lu Daoli , Chen Bin

Identyfikatory

DOI

10.1556/1326.2019.00613

• Języki publikacji: EN

Abstrakty

EN

In this study, discrimination of Chinese yellow wines from Shaoxing, Shandong, and Hubei in China has been carried out according to volatile flavor components. A total of 122 yellow wine samples were characterized by gas chromatography–ion mobility spectrometry (GC–IMS). A simple color mixing method was visually used to select characteristic peaks based on the RGB color model. Then, the volatile organic compounds corresponding to the selected characteristic peaks were identified via library searching, and the height values of those peaks were arranged for further chemometric pretreatment. Principal component analysis was employed to reveal significant differences and potential patterns between samples. Finally, quadratic discriminant analysis was applied to develop a classification model and achieved a correct classified rate of 95.35% for the prediction set. The results prove that the aroma composition combined with chemometric tools can be used as a fingerprinting technique to protect the product of origin and enable the authenticity of Chinese yellow wine.

Słowa kluczowe

EN

GC-IMS; yellow wine; flavor fingerprint; chemometrics

• Wydawca: University of Silesia in Katowice ; Akademiai Kiado
• Czasopismo: Acta Chromatographica
• Rocznik: 2020
• Tom: Vol. 32, no. 2
• Strony: 139--144
• Opis fizyczny: Bibliogr. 25 poz., rys.

Twórcy

autor

Chen Tong

• Jiangsu University, Zhenjiang 212013, P.R. China

autor

Qi Xingpu

• Jiangsu Agri-animal Husbandry Vocational College, Taizhou, 225300, P.R. China

autor

Chen Mingjie

• Jiangsu University, Zhenjiang 212013, P.R. China

autor

Lu Daoli

• Jiangsu University, Zhenjiang 212013, P.R. China

autor

Chen Bin

• Jiangsu University, Zhenjiang 212013, P.R. China

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).