Analysis of main aroma components of Zherong white tea and establishment of machine learning model for sensory evaluation
In summary, PTR-TOF-MS combined with PCA and OPLS-DA, among other analytical techniques, enables more effective identification of the 18 key aroma compounds in Zhongrong white tea. The BP model demonstrates high accuracy in predicting aroma sensory scores, as evidenced by a coefficient of determination (R<sup>2</sup>) value approaching 1. © 2025 Society of Chemical Industry.
Authors
- Xinyuan Mo
- Meining Li (ORCID: https://orcid.org/0000-0002-7915-1770)
- Zifeng Huang (ORCID: https://orcid.org/0000-0001-6836-8213)
- Jie Pang (ORCID: https://orcid.org/0000-0002-7061-5233)
- Oujun Dai
- Yilan Sun (ORCID: https://orcid.org/0009-0008-2996-1733)
- Yueguang Wang (ORCID: https://orcid.org/0009-0002-5454-7450)
- Hanlin Zhou (ORCID: https://orcid.org/0009-0008-2611-1557)
- Hong Wang (ORCID: https://orcid.org/0000-0002-6215-6348)
- Chunling Liu (ORCID: https://orcid.org/0000-0003-3410-445X)
- Che Su
Institutions
- Maryland Sea Grant (US)
- Fujian Agriculture and Forestry University (CN)
- University of Maryland, College Park (US)
Publication Details
- Journal
- Journal of the Science of Food and Agriculture
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1002/jsfa.70347
- Primary Topic
- Tea Polyphenols and Effects
- Type
- article
- Field-Weighted Citation Impact
- 0.00