Investigation of Flavor Molecules from a Machine Learning Perspective and Its Application in Jasmine Tea

Abstract

The pupose of this review was to explore the application of machine learning in the realm of flavor molecule research, particularly in the analysis of the flavor of Jasmine tea. The study of flavor molecules is fundamental to understand and optimize the taste and quality of food, especially tea. The introduction of machine learning technology has opened new horizons for the identification and analysis of flavor molecules. This paper firstly outlined the basic concepts and research methods of flavor molecules, and a detailed discussion on the application of machine learning in deciphering the relationships between molecular structures and flavor characteristics, as well as in the analysis, prediction and optimization of the flavor and intelligent processing of Jasmine tea and other applications, put forward the research prospect. Thereby, this review could enhance the quality of Jasmine tea and provide technical support for the further development of the tea industry.

Keywords

• flavor molecules
• machine learning
• jasmine tea
• quality prediction and control
• flavor optimization
• intelligent processing
• research prospect