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Determination of organic acids for predicting sourness intensity of tea beverage by liquid chromatography-tandem mass spectrometry and chemometrics methods.
Liu, Meiyan; Shi, Lijuan; Guo, Jie; Gu, Ying; Li, Siyu; Yi, Lunzhao; Ren, Dabing; Li, Boyan.
Afiliación
  • Liu M; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Shi L; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Guo J; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Gu Y; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Li S; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Yi L; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Ren D; Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China.
  • Li B; School of Public Health, Guizhou Medical University, Guiyang, China.
J Sep Sci ; 47(9-10): e2300628, 2024 May.
Article en En | MEDLINE | ID: mdl-38801755
ABSTRACT
The contents of organic acids (OAs) in tea beverage and their relationship with taste intensity have not been fully understood. In this work, a rapid (10 min for a single run) and sensitive (limits of quantification 0.0044-0.4486 µg/mL) method was developed and validated for the simultaneous determination of 17 OAs in four types of tea, based on liquid chromatography-tandem mass spectrometry with multiple reaction monitoring mode. The contents of 17 OAs in 96 tea samples were measured at levels between 0.01 and 11.80 g/kg (dried weight). Quinic acid, citric acid, and malic acid were determined as the major OAs in green, black, and raw pu-erh teas, while oxalic acid and tartaric acid exhibited the highest contents in ripe pu-erh tea. Taking the OAs composition as input features, a partial least squares regression model was proposed to predict the sourness intensity of tea beverages. The model achieved a root-mean-square error of 0.58 and a coefficient of determination of 0.84 for the testing set. The proposed model provides a theoretical way to evaluate the sensory quality of tea infusion based on its chemical composition.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Té / Espectrometría de Masas en Tándem Idioma: En Revista: J Sep Sci Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Té / Espectrometría de Masas en Tándem Idioma: En Revista: J Sep Sci Año: 2024 Tipo del documento: Article País de afiliación: China