Guo Lili, Yu Huiwen, Li Yuan, Zhang Chenxi, Kharbach Mourad
Weifang University of Science and Technology, Shouguang, 262700, China.
Shenzhen Hospital, Southern Medical University, Shenzhen, 518005, China.
Plant Methods. 2023 Nov 21;19(1):130. doi: 10.1186/s13007-023-01105-y.
Plant metabolomics is an important research area in plant science. Chemometrics is a useful tool for plant metabolomic data analysis and processing. Among them, high-order chemometrics represented by tensor modeling provides a new and promising technical method for the analysis of complex multi-way plant metabolomics data. This paper systematically reviews different tensor methods widely applied to the analysis of complex plant metabolomic data. The advantages and disadvantages as well as the latest methodological advances of tensor models are reviewed and summarized. At the same time, application of different tensor methods in solving plant science problems are also reviewed and discussed. The reviewed applications of tensor methods in plant metabolomics cover a wide range of important plant science topics including plant gene mutation and phenotype, plant disease and resistance, plant pharmacology and nutrition analysis, and plant products ingredient characterization and quality evaluation. It is evident from the review that tensor methods significantly promote the automated and intelligent process of plant metabolomics analysis and profoundly affect the paradigm of plant science research. To the best of our knowledge, this is the first review to systematically summarize the tensor analysis methods in plant metabolomic data analysis.
植物代谢组学是植物科学中的一个重要研究领域。化学计量学是用于植物代谢组学数据分析和处理的有用工具。其中，以张量建模为代表的高阶化学计量学为复杂的多向植物代谢组学数据分析提供了一种新的且有前景的技术方法。本文系统地综述了广泛应用于复杂植物代谢组学数据分析的不同张量方法。对张量模型的优缺点以及最新方法进展进行了综述和总结。同时，还对不同张量方法在解决植物科学问题中的应用进行了综述和讨论。所综述的张量方法在植物代谢组学中的应用涵盖了广泛的重要植物科学主题，包括植物基因突变与表型、植物病害与抗性、植物药理学与营养分析以及植物产品成分表征与质量评价。从综述中可以明显看出，张量方法显著推动了植物代谢组学分析的自动化和智能化进程，并深刻影响了植物科学研究的范式。据我们所知，这是第一篇系统总结植物代谢组学数据分析中张量分析方法的综述。
