Abstract
Phenolic compounds from a wide collection of mungbean [Vigna radiata (L.) Wilczek] germplasm (56 varieties) were characterised to determine the diversity among these phytochemicals and to analyse the relationships among their contents. The profiles of 25 phenolic compounds identified from the grains were subjected to data-mining processes, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), Pearson’s correlation analysis, and hierarchical clustering analysis (HCA). The IT212105 and IT104818 varieties separated from the others in the first two principal components of PCA. PLS-DA showed significant separation between extracts of mungbean originating from three countries: China, Japan, and Korea. HCA of these phytochemicals resulted in clusters derived from common or closely related biochemical pathways. Significant positive relationships were observed between coumaric acid and resveratrol (r=0.7195, p<0.0001). Catechin content was positively correlated with rutin (r=0.6291, p<0.0001). The IT104818 variety appears to be a good candidate for future breeding programs, as it contains high levels of phenolic compounds. These results demonstrate the use of metabolic profiling combined with chemometrics as a tool for assessing the quality of food.
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