UV-Visible Spectroscopic Technique-Data Mining Tool as a Reliable, Fast, and Cost-Effective Method for the Prediction of Total Polyphenol Contents: Validation in a Bunch of Medicinal Plant Extracts

Abstract

Medicinal plants extracts are a rich natural source of bioactive phytochemicals (mainly polyphenols). This study aims at determining the total polyphenols content (TPC) of nine medicinal plants extracted using the UV-visible (UV-Vis) spectroscopic method, along with the Orange Data Mining Tool (ODMT). The TPC for the selected medicinal plant extracts (i.e., Daucus carota L. root, Ruta Chalepensis L. Leaves, Anisosciadium DC. Leaves, Thymus vulgaris L. Leaves, Senna alexandrina leaves, Myrtus communis L. leaves, Silybum Marianum L. Flower, Silybum marianum L. Leaves, and Rosa moschata Flower) was measured using gallic acid (GA) as a standard. The intended method requires a maximum of 1 mg of GA and only 1 mg of the plant extract. The wavelength range of the maximum absorption in the UV-vis spectrum was about 270 nm. For polyphenols, the purposed method linear dynamic concertation range (44.67 to 334.7 mg GA equivalent (GAE)/g dry weight (DW)) with a recovery percentage range of 95.3% to 104.3%, and the good regression value, was found to be R2 = 0.999. This method was easy, fast, accurate, and less expensive than the conventional Folin–Ciocalteu method.