Fungal fermentation of Fuzhuan brick tea: A comprehensive evaluation of sensory properties using chemometrics, visible near-infrared spectroscopy, and electronic nose

被引：8

作者：

Hu, Yan ^{[1
]}

Chen, Wei ^{[2
]}

Gouda, Mostafa ^{[1
,4
]}

Yao, Huan ^{[3
]}

Zuo, Xinxin ^{[2
]}

Yu, Huahao ^{[1
]}

Zhang, Yuying ^{[1
]}

Ding, Lejia ^{[2
]}

Zhu, Fengle ^{[3
]}

Wang, Yuefei ^{[2
]}

Li, Xiaoli ^{[1
]}

Zhou, Jihong ^{[2
]}

He, Yong ^{[1
]}

机构：

[1] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Peoples R China

[2] Zhejiang Univ, Tea Res Inst, Hangzhou 310058, Peoples R China

[3] Zhejiang Univ Technol, Coll Mech Engn, Hangzhou 310023, Peoples R China

[4] Natl Res Ctr, Dept Nutr & Food Sci, Dokki 12622, Egypt

来源：

FOOD RESEARCH INTERNATIONAL | 2024年 / 186卷

基金：

中国国家自然科学基金;

关键词：

Fermented dark tea; Multiple sensor technologies; Spectroscopy; Data fusion; Tea quality assessment; QUALITY;

D O I：

10.1016/j.foodres.2024.114401

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

Fuzhuan brick tea (FBT) fungal fermentation is a key factor in achieving its unique dark color, aroma, and taste. Therefore, it is essential to develop a rapid and reliable method that could assess its quality during FBT fermentation process. This study focused on using electronic nose (e-nose) and spectroscopy combination with sensory evaluations and physicochemical measurements for building machine learning (ML) models of FBT. The results showed that the fused data achieved 100 % accuracy in classifying the FBT fermentation process. The SPA-MLR method was the best prediction model for FBT quality (R2 = 0.95, RMSEP = 0.07, RPD = 4.23), and the fermentation process was visualized. Where, it was effectively detecting the degree of fermentation relationship with the quality characteristics. In conclusion, the current study's novelty comes from the established real-time method that could sensitively detect the unique post-fermentation quality components based on the integration of spectral, and e-nose and ML approaches.

引用

页数：11