Exploration of metabolite profiles of cassava (Manihot esculenta Crantz) genotypes using an LC-MS approach

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• Untargeted metabolomic analysis of four cassava genotypes revealed 3 372 metabolite features, highlighting significant metabolic diversity. • PCA and PLS-DA revealed distinct metabolic patterns, with the genotype P4/10 showing the most pronounced separation. • Phenylpropanoid biosynthesis, fatty acid degradation, and flavonoid biosynthesis played significant roles in shaping metabolic profiles. • Metabolites including lipids, polyphenols, organic acids and flavonoids were identified as primary contributors to genotype differentiation. Cassava serves as a crucial crop for food security, particularly in regions where agriculture is integral to local livelihoods, owing to its resilience and adaptability to challenging environmental conditions. Understanding the metabolic diversity in cassava germplasm is essential for improving farmers’ and customers’ preferred traits. This work employed liquid chromatography–quadrupole time-of-flight tandem mass spectrometer (LC-MS qTOF) to analyse the metabolic profiles of four cassava genotypes under controlled environments, resulting in 3372 metabolite characteristics from the leaf samples. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) demonstrated clear distinctions in metabolic patterns across the genotypes. Genotype P4/10 demonstrated the most significant separation, whilst UKF4 displayed modest divergence. Moreover, the findings suggested that lipids, polyphenols, organic acids, and flavonoids were the primary metabolites that contributed to genotype separation. A pathway study revealed significant influences from the phenylpropanoid biosynthesis, fatty acid degradation, and flavonoid biosynthesis pathways, emphasizing the role of genotype-specific metabolic profiles in shaping cassava’s biochemical diversity. These findings highlight the importance of metabolic blueprints in determining unique traits among genotypes. Furthermore, future research can look into the genetic basis of metabolic diversity and the potential of metabolomics as a selection tool in breeding programs targeting improved cassava genotypes with higher nutritional content and stress tolerance.