Precise Discrimination Between Rape Honey and Acacia Honey Based on Sugar and Amino Acid Profiles Combined with Machine Learning.

ABSTRACT: Honey variety authentication is critical for ensuring market integrity and protecting consumer rights, especially for high-value unifloral honeys, such as acacia honey, which are frequently adulterated with low-value alternatives such as rape honey due to their similar visual appearance. The aim of this study was to develop a method for precise discrimination between rape honey and acacia honey using their chemical profiles combined with machine learning. A total of 542 honey samples were collected from major beekeeping regions in China. Targeted quantification of 12 sugars and 20 amino acids was performed using UPLC-MS/MS. Multivariate analysis revealed significant differences in sugar and amino acid compositions between the two honey types, though partial samples overlapped due to chemic

SUBMITTER: Sun C 

PROVIDER: S-EPMC12785547 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature