鉴定(生物学)
生化工程
生物技术
功能性食品
计算机科学
计算生物学
数据科学
化学
生物
工程类
食品科学
植物
作者
Bo‐Dou Zhang,Sheng Li,Zhenzhen Liang,Yinling Wei,Jing Dong,Hao Wen,Ling‐Li Guo,Xiao‐Jiang Hao,Yu Zhang
标识
DOI:10.26599/fshw.2024.9250003
摘要
Medicinal and dietary plants provide numerous nutritional and functional compounds and also have various potential health benefits to humanity. The specific and efficient techniques for accurate identification of nutritional compounds and functional metabolites is crucial for the development of functional foods from medicinal and dietary plants. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are indispensable and essential technologies that provide an unsurpassed wealth of untargeted identification, quantitative and qualitative analysis, and structural information in the study of food and plant products. In the past decade, the rapid development of modern analytical technology has led to the emergence of new approaches and strategies for natural products discovery. Especially the application of novel NMR- and MS-based identification and dereplication strategies aided by artificial intelligence and machine learning algorithms have brought about a significant shift in the natural products discovery process. These developments and changes in the natural products filed have given us insights into how to accurately target and mining nutritional, functional, and bioactive compounds. Thus, we have summarized recent research on novel NMR and MS based strategies and methods focusing on functional compounds, accurate identification and efficient discovery mainly in medicinal and dietary plants. This review could provide a comprehensive perspective for a better understanding of novel strategies and methods based on NMR and MS technologies, which could provide valuable insights and ideas for functional compounds mining.
科研通智能强力驱动
Strongly Powered by AbleSci AI