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Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification
Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification
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Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification
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Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification
Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification

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Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification
Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification
Journal Article

Integrating untargeted volatile metabolomics and molecular evidence supporting chemotaxonomy in Kaempferia species for more effective identification

2025
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Overview
Kaempferia L., a medicinal genus of Zingiberaceae family, is widely distributed from India to Southeast Asia and is rich in terpenoids, flavonoids, phenolics, and volatile oils. Recently, it has gained attention for its diverse biological activities, including antioxidant, anticancer, analgesic, anti-inflammatory, and anti-tuberculosis effects. However, several Kaempferia species complexes exhibit similar morphological characteristics, making identification and classification challenging. This study integrates morphology, molecular phylogeny, and phytochemistry to identify and distinguish Kaempferia species. Phylogenetic relationships were reconstructed using four DNA barcoding markers: one nuclear region (ITS) and three chloroplast markers ( mat K, rbc L, and psb A- trn H). Untargeted metabolomic analysis using SPME-GC-MS, combined with multivariate statistical analyses, was employed to resolve species relationships and display volatile profiles among 15 Kaempferia species from two subgenera. A total of 217 metabolites were identified by the SPME-GC-MS technique. Variable Importance in Projection (VIP ≥ 1.5) analysis indicated 30 key metabolites, primarily sesquiterpenes, as specific chemotaxonomic markers. This study provides a comprehensive chemical profile of Kaempferia species and highlights metabolomic differences among them. Our findings emphasize the importance of integrating morphological, molecular, and phytochemical approaches for precise identification of closely related species, particularly within Kaempferia . This chemotaxonomic research also provides further applications for species authentication in pharmaceuticals and medicine.