State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
Department of Food Science, Rutgers University, New Brunswick, New Jersey, USA.
Compr Rev Food Sci Food Saf. 2023 Nov;22(6):4890-4924. doi: 10.1111/1541-4337.13246. Epub 2023 Oct 2.
With the development of metabolomics analytical techniques, relevant studies have increased in recent decades. The procedures of metabolomics analysis mainly include sample preparation, data acquisition and pre-processing, multivariate statistical analysis, as well as maker compounds' identification. In the present review, we summarized the published articles of tea metabolomics regarding different analytical tools, such as mass spectrometry, nuclear magnetic resonance, ultraviolet-visible spectrometry, and Fourier transform infrared spectrometry. The metabolite variation of fresh tea leaves with different treatments, such as biotic/abiotic stress, horticultural measures, and nutritional supplies was reviewed. Furthermore, the changes of chemical composition of processed tea samples under different processing technologies were also profiled. Since the identification of critical or marker metabolites is a complicated task, we also discussed the procedure of metabolite identification to clarify the importance of omics data analysis. The present review provides a workflow diagram for tea metabolomics research and also the perspectives of related studies in the future.
随着代谢组学分析技术的发展,近几十年来相关研究有所增加。代谢组学分析的步骤主要包括样品制备、数据采集和预处理、多元统计分析以及标志物化合物的鉴定。在本综述中,我们总结了不同分析工具(如质谱、核磁共振、紫外可见光谱和傅里叶变换红外光谱)在茶叶代谢组学方面的已发表文章。综述了不同处理(如生物/非生物胁迫、园艺措施和营养供应)下新鲜茶叶的代谢物变化。此外,还概述了不同加工技术下加工茶样品化学成分的变化。由于关键或标志物代谢物的鉴定是一项复杂的任务,我们还讨论了代谢物鉴定的过程,以阐明组学数据分析的重要性。本综述为茶叶代谢组学研究提供了工作流程图,并对未来相关研究的前景进行了探讨。