Abstract

EL HAWARY, Seham S. et al. Biodiversity Assessment in Tecoma Species Using Micro-morphometric, Phytochemical and Molecular Descriptors Aided by Multivariate Analysis. J. Mex. Chem. Soc [online]. 2022, vol.66, n.4, pp.455-467.  Epub Apr 10, 2023. ISSN 1870-249X.  https://doi.org/10.29356/jmcs.v66i4.1702.

Tecoma genus is a medicinally-valuable member in Bignoniaceae family comprising fourteen defectively-demarcated species with overlapping vegetative characters. Our study aimed to explore the micro-morphometric, phytochemical and genetic diversity among eight cultivated Tecoma plants. The variabilities existing in three data matrices derived from micro-morphometric features of powdered leaves, high performance liquid chromatographic fingerprints and Random Amplified Polymorphic DNA (RAPD) fingerprints were explored by multivariate analysis. The microscopical measurements of non-glandular trichomes, i.e. collapsed multicellular and branched, and glandular trichomes were revealed to be the significant botanical discriminatory features of the powdered plant specimens, however species-specific phytochemical markers were identified to be gallic acid, catechin and chlorogenic acid for T. radicans, T. grandiflora, T. capensis var. yellow, respectively. Sinapic acid was enriched in T capensis and its varieties i.e. pink, red and harmony. RAPD primers i.e. OP-B02, OP-C04 and OP-K2 served as molecular descriptors producing the highest polymorphism among the plants. The variabilities within two trumpet creeper plants “T. radicans and T. grandiflora” were unveiled via their micro-morphometric features as well as genetic fingerprints. Tecoma hybrid “Tecoma ×smithii” was more micro-morphometrically similar to the Chinese “T. grandiflora.” than T. capensis which is one of its parents plants, and proved to be more genetically related to it. This is the report for biodiversity in botanical, chemical and genetic aspects of Tecoma plants which are essential for the comprehensive authentication and differentiation among the studied plants assisted by multivariate analysis. The presented approach provides a competent and time-saving tool for simultaneously-discriminating among closely-related species.

Keywords : Cluster analysis; micro-morphometric features; OPLS-DA; PCA; Tecoma.