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Chemophenetic Approach to Selected Senecioneae Species, Combining Morphometric and UHPLC-HRMS Analyses.

Yulian VoynikovVessela BalabanovaReneta GevrenovaDimitrina Zheleva-Dimitrova
Published in: Plants (Basel, Switzerland) (2023)
Herein, a chemophenetic significance, based on the phenolic metabolite profiling of three Senecio ( S. hercynicus, S. ovatus , and S. rupestris ) and two Jacobaea species ( J. pancicii and J. maritima ), coupled to morphometric data, is presented. A set of twelve morphometric characters were recorded from each plant species and used as predictor variables in a linear discriminant analysis (LDA) model. From a total 75 observations (15 from each of the five species), the model correctly assumed their species' membership, except for 2 observations. Among the studied species, S. hercynicus and S. ovatus presented the greatest morphological similarity. A phytochemical profiling of phenolic specialized metabolites by UHPLC-Orbitrap-MS revealed 46 hydroxybenzoic, hydroxycinnamic, and acylquinic acids and their derivatives, 1 coumarin and 21 flavonoids. Hierarchical and PCA clustering applied to the phytochemical data corroborated the similarity of S. hercynicus and S. ovatus , observed in the morphometric analysis. This study contributes to the phylogenetic relationships between the tribe Senecioneae taxa and highlights the chemophenetic similarity/dissimilarity of the studied species belonging to Senecio and Jacobaea genera.
Keyphrases
  • ms ms
  • single cell
  • mass spectrometry
  • genetic diversity
  • high resolution mass spectrometry
  • palliative care
  • machine learning
  • deep learning
  • neural network