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Foods

Title:		Digital Evaluation of Aroma Intensity and Odor Characteristics of Tea with Different Types-Based on OAV-Splitting Method
Author(s):		Hu W; Wang G; Lin S; Liu Z; Wang P; Li J; Zhang Q; He H;
Address:		"Key Laboratory of Agroecological Processing and Safety Monitoring of Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, China. College of Tea and Food Science, Wuyi University, Wuyishan 353400, China"
Journal Title:		Foods
Year:		2022
Volume:		20220725
Issue:		15
Page Number:		-
DOI:		10.3390/foods11152204
ISSN/ISBN:		2304-8158 (Print) 2304-8158 (Electronic) 2304-8158 (Linking)
Abstract:		"Aroma is one of the most important quality indicators of tea. However, this evaluation method is a subjective one. In this study, the volatiles of tea with 5 types were determined by headspace solid-phase micro-extraction (HS-SPME) combined with gas chromatography mass spectrometry (GC-MS). The aroma intensity and odor characteristics of teas were comparatively analyzed based on the OAV-splitting method. The results showed that OAV were green tea (492.02), red tea (471.88), oolong tea (302.74), white tea (68.10), and dark tea (55.98). The odor index I(o) indicated that green tea was strong-flavor tea with highlight green accompanied by fruity, woody and fatty odors; oolong tea was strong-flavor tea with fruity and fatty accompanied by woody, floral and green odors; red tea was strong-flavor tea with highlight fruity accompanied by woody, green and floral odors; white tea was a light-flavor tea with floral, woody and green odors; and dark tea was light-flavor tea with woody and floral notes accompanied by fatty and green odors. These results fitted perfectly with the people's consensus on these teas, and proved that the OAV-splitting method is feasible to evaluate the aroma intensity and odor characteristics of tea aroma. We suggest that the digital evaluation of tea aroma can facilitate people's communication"
Keywords:		OAV-splitting method odor activity value (OAV) odor characteristic odor index I(o) tea;
Notes:		"PubMed-not-MEDLINEHu, Wenwen Wang, Gege Lin, Shunxian Liu, Zhijun Wang, Peng Li, Jiayu Zhang, Qi He, Haibin eng 2014-Z36/National 948 Project/ 2020J01408/Natural Science Foundation of Fujian Province/ No. 2015-75/Project of China Oolong Tea Industry Collaborative Innovation Center/ Switzerland 2022/07/28 Foods. 2022 Jul 25; 11(15):2204. doi: 10.3390/foods11152204"