Characterization and exploration of dynamic variation of volatile compounds in vine tea during processing by GC-IMS and HS-SPME/GC-MS combined with machine learning algorithm.

Journal: Food chemistry
PMID: 39142197

Abstract

It is imperative to unravel the dynamic variation of volatile components of vine tea during processing to provide guidance for tea quality evaluation. In this study, the dynamic changes of volatile compounds of vine tea during processing were characterized by GC-IMS and HS-SPME/GC-MS. As a result, 103 volatile compounds were characterized by the two technologies with three overlapped ones. The random forest approach was employed to develop the models and explore key volatile compounds. 23 key compounds were explored, among which 13 were derived from GC-IMS and ten were from HS-SPME/GC-MS. Moreover, the area under the receiver operating characteristics curve with 100 cross validations by the pair-wised models were all 1 for the established models. Furthermore, the primary aroma formation mechanism for the key volatile compounds were mainly involved in fatty acid and amino acid metabolism. Besides, this study provides a theoretical support for directed processing and quality control of vine tea.

Authors

  • Qianqian Li
    Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, 710072, China.
  • Chaoyang Zhang
    a School of Computing Sciences and Computer Engineering , University of Southern Mississippi , Hattiesburg , Mississippi , USA.
  • Wei Liu
    Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • Bei Li
    State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China. Electronic address: beili@ciomp.ac.cn.
  • Shengfan Chen
    Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture and Rural Affairs, Beijing 100093, PR China.
  • Huawei Wang
    Guangdong Provincial Key Laboratory of Optical Information Materials and Technology & Institute of Electronic Paper Displays, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China.
  • Yi Li
    Wuhan Zoncare Bio-Medical Electronics Co., Ltd, Wuhan, China.
  • Jianxun Li
    School of Information Science and Engineering, Baoding University of Technology, Baoding 071000, Hebei, China.

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