Abstract
This study aimed to investigate the metabolic differences among six mung bean (Vigna radiata) varieties cultivated in Heilongjiang Province, China, using non-targeted metabolomics based on high-resolution mass spectrometry. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to explore and distinguish the metabolomic profiles across different varieties. A total of 547 metabolites were identified, including fatty acids (9.69%), phenolic acids (7.86%), amino acids and derivatives (5.12%), among others. PCA revealed that the first two principal components (t[1] and t[2]) accounted for 20.1% and 17.0% of the total variance, respectively, indicating significant differentiation among varieties. Differential metabolite analysis demonstrated that GLD07_03 was enriched in defense-related compounds such as lignans, terpenoid lactones, and methyl salicylate, suggesting enhanced antibacterial and antioxidant capacity. BL13_1 showed higher metabolic activity in glycolysis and the mevalonate pathway, with L-lactic acid and mevalonate levels 57.2% and 33.8% higher than those in GLD07_03. NL2_1 and NL4_1 accumulated high levels of amino acids (e.g., L-aspartic acid, increased by 161%), nucleosides, and flavonoids, contributing to superior antioxidant potential. T1114111_1 exhibited higher levels of fatty acids and alkaloids (e.g., trigonelline, increased by 25.2%), associated with improved membrane stability and antibacterial activity. JL13_1 displayed elevated levels of D-proline and (7Z,10Z)-7,10-hexadecadienoic acid (increased by 26.5% and 34.8%, respectively), suggesting advantages in osmotic regulation and membrane homeostasis. These findings reveal distinct metabolite profiles and biochemical traits among mung bean varieties, providing valuable insights for varietal identification, nutritional evaluation, and breeding for enhanced stress tolerance. The study also offers a scientific basis for the development of functional mung bean products and future breeding strategies focused on metabolic traits.