A Liquid Chromatography Time-of-Flight Mass Spectrometry-Based Metabolomics Approach for the Discrimination of Cocoa Beans from Different Growing Regions

Abstract

Accurate and reliable techniques for the discrimination of cocoa beans according to their geographical origin are essential for quality control and traceability management. In the present study, we demonstrate a metabolomics approach for the discrimination of cocoa beans using liquid chromatography time-of-flight mass spectrometry (LC-TOF MS) and multivariate analysis. Cocoa bean samples from six growing regions were used to prove the effectiveness of the developed technique. The critical markers, such as polyphenols, responsible for such variations were identified through the corresponding loading weights, and the tentative identification of biomarkers was completed by the accurate mass from the TOF MS. The results revealed that the LC-TOF MS coupled with a partial least squares discriminant analysis model can be successfully applied for the discrimination of cocoa beans based on their geographic origins for effective quality assurance.