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All Journal Biodiversitas Journal of Biological Diversity
NUR AINI FADHILAH
Department of Pharmaceutical Biology, Faculty of Pharmacy, Universitas Surabaya. Jl. Tenggilis Mejoyo Blok AM 12, Surabaya 60293, East Java, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology

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Molecular characterization of red ginger varieties (Zingiber officinale Roxb. var. rubrum) by DNA markers OEKE YUNITA; NUR AINI FADHILAH; SARI PRAMADIYANTI; SIMON JONATAN
Biodiversitas Journal of Biological Diversity Vol. 24 No. 12 (2023)
Publisher : Society for Indonesian Biodiversity

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/biodiv/d241252

Abstract

Abstract. Yunita O, Fadhilah NA, Pramadiyanti S, Jonatan S. 2023. Molecular characterization of red ginger varieties (Zingiber officinale Roxb. var. rubrum) by DNA markers. Biodiversitas 24: 6905-6913. Red ginger (Zingiber officinale Roxb. var. rubrum) rhizomes have been traditionally used in Indonesia to increase human health. Therefore, the assurance of raw material quality holds significant importance in the industrial application of red ginger. The primary step in ensuring the quality, safety, and effectiveness of the final product in the industrial environment is the identification of plants used as raw materials for supplements and herbal medications. DNA-based molecular characterization approaches have been specifically developed to aid in the identification of herbal raw materials prior to their application in production processes. Based on the findings derived from the conducted research, the Random Amplified Polymorphic DNA (RAPD) technique can be employed to amplify the DNA isolates of red ginger rhizome samples. The results obtained from the PCR-RAPD amplification of DNA samples extracted from red ginger plants indicated that 90.48% of the total 147 bands seen exhibited polymorphism. The findings suggest a tendency for DNA banding patterns derived from red ginger samples planted in the same geographic area to display clustering tendencies.
Co-Authors OEKE YUNITA SARI PRAMADIYANTI SIMON JONATAN