Comprehensive study of different grades of Lonicerae japonicae flos: GC-IMS, UPLC-HRMS, and machine learning

作者：Shuang Liu, Hongjing Dong, Heng Lu, Meng Li, Xiao Wang · 发表于：Applied Food Research · 年份：2025 · DOI：10.1016/j.afres.2025.100760 · 被引用次数：9 · 研究领域：Metabolomics and Mass Spectrometry Studies、Traditional Chinese Medicine Analysis、Advanced Chemical Sensor Technologies

• Twelve key volatile compounds in different grades of LJF were selected. • Fifteen key non-volatile compounds in different grades of LJF were screened. • As LJF grades increased, the content of polyphenols and flavonoids increased. • Higher grades of LJF had stronger antioxidant activity. • SVM-P, LDA, and SVM-L could accurately identify the LJF grades. Lonicerae japonicae flos (LJF), a traditional Chinese medicine with the homology characteristics of food and medicine, is commonly classified into three grades by sensory evaluation. Currently, few studies focus on the difference in their chemical compositions. This study aims to analyze total polyphenols and flavonoids in different grades of LJF, and determine their antioxidant activity. It can be observed that higher grades of LJF have higher content of main components and stronger antioxidant activity. The volatile and non-volatile compounds are detected using HS-GC-IMS and UPLC HRMS, a total of 12 differential volatile compounds and 15 differential non-volatile compounds are screened. Finally, eleven machine learning models are established to quickly identify LJF grades, and the results show that SVM-P, LDA, and SVM-L have potential applications for the identification of LJF grades. This study provides a detailed metabolite profile of LJF grades and establishes an identification method for grade classification.