Advances in Foodomics Based on Liquid Chromatography High Resolution Mass Spectrometry and Machine Learning

With the improvement of living standards, people’s demands for food quality and safety have increased, driving the urgent need for cutting-edge analytical methodologies in food science research. In this context, the integration of liquid chromatography high resolution mass spectrometry (LC-HRMS) with machine learning (ML) has established a sophisticated framework for foodomics. This powerful technological combination is gradually becoming a new direction for food science research and is widely being applied in food authenticity identification, safety assessment, and quality control. This review provides a critical overview of recent advances in the application of LC-HRMS combined with ML in food metabolomics, proteomics, lipidomics, and multi-omics approaches. Furthermore, we discuss the future development of the combination of LC-HRMS and ML, aiming to provide a theoretical basis and technical guidance for the intelligent development of rapid and comprehensive food testing.