Identification of volatile components and analysis of aroma characteristics of Jiangxi Congou black tea-Reference-Cited by-同舟云学术

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Identification of volatile components and analysis of aroma characteristics of Jiangxi Congou black tea

Published:2020-01-01 Issue:1 Volume:23 Page:2160-2173
ISSN:1094-2912
Container-title:International Journal of Food Properties
language:en
Short-container-title:International Journal of Food Properties

Author:

Yue Cuinan¹²^ORCID,Yang Puxiang¹²,Qin Dandan³,Cai Hailan¹²,Wang Zhihui¹²,Li Chen¹²,Wu Hualing³

Affiliation:

1. Tea Research Institute, Jiangxi Sericulture and Tea Research Institute, Nanchang, China

2. Tea Research Institute, Jiangxi Key Laboratory of Tea Quality and Safety Control, Nanchang, China

3. Tea Research Institute, Guangdong Academy of Agricultural Science, Guangzhou, China

Funder

China Agricultures Research System

Jiangxi Key Laboratory of Tea Quality and Safety Control

Agricultures Research System of Jiangxi Province

Publisher

Informa UK Limited

Subject

Food Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/10942912.2020.1844747

Reference40 articles.

1. Understanding the biosyntheses and stress response mechanisms of aroma compounds in tea (Camellia sinensis) to safely and effectively improve tea aroma

2. Antioxidant, antihypertensive, and anticancer activities of the flavonoid fractions from green, oolong, and black tea infusion waste

3. Prediction of Congou Black Tea Fermentation Quality Indices from Color Features Using Non-Linear Regression Methods

4. Foodomics: MS-based strategies in modern food science and nutrition

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1. Comparative study of volatile compounds and metabolic pathways of Congou black tea from four regions based on sensory evaluation and HS-SPME/GC–MS;Microchemical Journal;2024-10

2. The Chemistry, Sensory Properties and Health Benefits of Aroma Compounds of Black Tea Produced by Camellia sinensis and Camellia assamica;Horticulturae;2023-11-22

3. Classification of oolong tea varieties based on computer vision and convolutional neural networks;Journal of the Science of Food and Agriculture;2023-10-30

4. UPLC–QTOF/MS-based non-targeted metabolomics coupled with the quality component, QDA, to reveal the taste and metabolite characteristics of six types of Congou black tea;LWT;2023-08

5. Molecular markers and phenotypic identification reveal the genetic diversity and structure of four local tea plant populations in China;Genetic Resources and Crop Evolution;2023-07-14

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