NATURAL PRODUCT RESEARCH AND DEVELOPMENT ›› 2025, Vol. 37 ›› Issue (增刊1): 99-106.

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Study on browning marker of tobacco leaf based on HPLC fingerprint and antioxidant spectrum-effect relationship

LI Yong-dong1,HUO Qin-jian2,YANG Ming-hua1,LI Yun-qiang1,JIN Hui1,YANG Min-min1,LIAN Yun1,LIU Jin-liang1*   

  1. 1Guizhou Provincial Key Laboratory for Tabacco Quality Improvement and Efficiency Enhancement,College of Tobacco Science,Guizhou University,Guiyang 550025,China;2Guizhou Tobacco Science Institute,Guiyang 550081,China
  • Online:2025-09-25 Published:2025-09-22

Abstract:

To investigate the browning mechanism of tobacco leaves,this study established a method for identifying browning markers by integrating high-performance liquid chromatography (HPLC) fingerprint profiles with antioxidant activity correlations.HPLC fingerprint chromatograms of 24 batches of tobacco leaf samples were developed,and nine common peaks were identified.Cluster analysis (CA) and principal component analysis (PCA) were employed to evaluate browning levels based on the peak areas of these common peaks.The antioxidant capacity and browning degree of the samples were assessed using DPPH radical scavenging activity and browning index measurements.Bivariate correlation analysis and grey relational analysis (GRA) were applied to explore the spectrum-effect relationships between the common peaks and browning characteristics,revealing that peaks 3,4,5,6,7,8,and 9 were critical markers influencing browning.Through HPLC-MS/MS identification and reference standard validation,peaks 4,5,6,7,and 8 were confirmed as neochlorogenic acid,chlorogenic acid,cryptochlorogenic acid,caffeic acid,and rutin,respectively.The results elucidate the material basis of antioxidant activity in tobacco leaves and provide a theoretical foundation for regulating and evaluating browning processes.The identified markers offer practical insights for quality control and preservation strategies in tobacco production.

Key words: tobacco leaves, fingerprint spectrum, browning marker, bivariate correlation analysis, grey correlation analysis

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