A predictive model for astringency based on in vitro interactions between salivary proteins and (−)-Epigallocatechin gallate

•Turbidity was used to predict the astringent intensity of EGCG.•Temperature, pH, proteins type and EGCG concentration affected the interactions.•Mucin was more suitable for the prediction of EGCG astringent intensity in vitro.•Fluorescence analysis showed EGCG interacted with mucin and amylase. Ast...

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Published inFood chemistry Vol. 340; p. 127845
Main Authors Ye, Qing-Qing, Chen, Gen-Sheng, Pan, Weichun, Cao, Qing-Qing, Zeng, Liang, Yin, Jun-Feng, Xu, Yong-Quan
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 15.03.2021
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Summary:•Turbidity was used to predict the astringent intensity of EGCG.•Temperature, pH, proteins type and EGCG concentration affected the interactions.•Mucin was more suitable for the prediction of EGCG astringent intensity in vitro.•Fluorescence analysis showed EGCG interacted with mucin and amylase. Astringency is an important quality attribute of green tea infusion, and (−)-Epigallocatechin gallate (EGCG) is the main contributor to astringency. Turbidity was used to predict the intensity of astringency for EGCG. The interactions between the selected proteins and EGCG, and the impacts of temperature, pH, protein structure, and EGCG concentration were studied. Mucin was selected as the protein in study for the prediction of EGCG astringency intensity. A predictive model (R2 = 0.994) was developed based on the relationship between the astringency of EGCG and the turbidity of EGCG/mucin mixtures at pH 5.0 and 37 °C. The fluorescence quenching analyses showed the interactions between EGCG and the selected proteins, which induced the reversible protein molecule conformational changes. The interactions were considered as the main reason that causes the astringency of tea infusions. The results provided a biochemical approach to explore the sensory qualities of green tea.
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ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2020.127845