UPSI Digital Repository (UDRep)
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UPSI Digital Repository (UDRep)
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| Abstract : Universiti Pendidikan Sultan Idris |
| Background: Eurycoma longifolia (E. longifolia), Labisia pumila (L. pumila), and Orthosiphon stamineus (O. stamineus) are popular species known for their therapeutic properties. An increase in local demand for herbal products makes them susceptible to adulteration, which poses a risk to their safety and efficacy. Current identification methods, such as organoleptic, microscopic, and macroscopic analysis, need to be revised to identify plant species in highly processed herbal products due to their limited ability to detect morphological features and provide comprehensive plant taxonomy information. Methods: This research objective was to develop a simple, reliable, and accurate DNA molecular identification method based on polymerase chain reaction_restriction fragment length polymorphism (PCR_RFLP) for E. longifolia, L. pumila, and O. stamineus, used to validate the species identification for herbal products. PCR_RFLP was developed for rapid identification using restriction enzymes TaqI, BamH I, HinfI, EcoRI, EcoRV, Mbol, and Mspl. Results: The nuclear DNA internal transcribed spacer 2 (ITS2) sequences were identified and compared between plant specimens of E. longifolia, L. pumila, and O. stamineus and 101 samples of commercial herbal products. Plant specimens of E. longifolia, L. pumila, and O. stamineus were successfully identified with high similarity of 100%, 100%, and 99.33%, respectively, based on National Center for Biotechnology Information (NCBI) GenBank. The recovery of DNA sequences from the herbal products was 60.4%, of which 81.97% were identified, and 18.03% showed no sequence through Basic Local Alignment Search Tool (BLAST) identification. Conclusion: A reliable approach for identifying and validating plant species in herbal products has been created using restriction enzymes. This simple and accurate PCR_RFLP approach efficiently identifies E. longifolia, L. pumila, and O. stamineus by analysing ITS2 sequences, assuring consumer health and safety. _ The Author(s) 2024. |
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