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  1. Alara OR, Abdurahman NH, Ukaegbu CI
    Curr Res Food Sci, 2021;4:200-214.
    PMID: 33899007 DOI: 10.1016/j.crfs.2021.03.011
    Phenolic compounds are parts of secondary metabolites mostly found in plant species with enormous structural diversities. They can exist as glycosides or aglycones; matrix or free-bound compounds; and comprising mostly polymerized or monomer structures. Additionally, these compounds are not universally dispensed within plants with varied stability. This has contributed to challenging extraction processes; implying that employing a single step or inappropriate extraction technique might change the recovery of phenolic components from the plant samples. Hence, it is important to select an appropriate extraction method so as to recover the targeted phenolic compounds. This is will helps to recover substantial yields from the sample matrix. Therefore, this review mainly focuses on the phenolic compounds and several methods of extraction that are used to obtaining them from plant materials. These extraction methods includes both conventional and unconventional techniques.
  2. Alara OR, Abdurahman NH, Ukaegbu CI, Hassan Z, Kabbashi NA
    Data Brief, 2018 Dec;21:1686-1689.
    PMID: 30505901 DOI: 10.1016/j.dib.2018.10.159
    The tentative identification of bioactive compounds in the extract of Vernonia amygdalina leaf was carried out using positive ionization of Liquid chromatography-mass spectrometry quadrupole time of flight (LC-Q-TOF/MS). The positive ionization is associated with the presence of saponins, flavonoids, alkaloids, terpenoids, and glycosides. Tentative assignments of the secondary metabolites were performed by comparing the MS fragmentation patterns with Waters® UNIFY library which allows positive identification of the compounds based on the spectral match. All the metabolites compounds were estimated and presented in a BPI (Base peak intensity) plot. These data are the unpublished supplementary materials related to "Ethanolic extraction of bioactive compounds from V. amygdalina leaf using response surface methodology as an optimization tool" (Alara et al., 2018).
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