JOURNAL ARTICLE
Phytochemical Screening and Spectroscopic Characterization of Parkia biglobosa Stem Bark: A Potential Source of Medicinal Compounds.
Published In: Bima Journal of Science & Technology, 2026, v. 9, n. 4B. P. 54 1 of 3
Database: Africa Studies Source 2 of 3
Authored By: Auwal, Auwal R.; Maikifi, Adamu S.; Gololo, Ahmed A.; Abubakar, Junaidu; Alhassan, Adamu J.; Musa, Abbas; Hassan, Muhammad K. 3 of 3
Abstract
This article focuses on the phytochemical screening and spectroscopic characterization of Parkia biglobosa stem bark to evaluate its potential as a source of medicinal compounds. The study employed qualitative and quantitative phytochemical analyses, Fourier-transform infrared (FT-IR) spectroscopy, and Gas Chromatography-Mass Spectrometry (GC-MS) on methanol extracts of the bark collected in Kano State, Nigeria. Results revealed the presence of bioactive compounds including alkaloids, flavonoids, tannins, phenolics, saponins, terpenoids, and cardiac glycosides, with tannins being the most abundant. FT-IR identified functional groups consistent with phenols and terpenoids, while GC-MS detected compounds such as 5-chlorovaleric acid and propenamide, supporting the plant’s traditional use for treating oxidative stress, inflammation, and cardiovascular diseases. The findings validate the therapeutic potential of P. biglobosa stem bark and suggest further pharmacological studies to isolate and evaluate its bioactive constituents.
Additional Information
- Source:Bima Journal of Science & Technology. 2026/01, Vol. 9, Issue 4B, p54
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2026
- ISSN:2536-6041
- DOI:10.64290/bima.v9i4B.1445
- Accession Number:192421606
- Copyright Statement:Copyright of Bima Journal of Science & Technology is the property of Gombe State University, Faculty of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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