STATISTICAL OPTIMIZATION OF ANTIOXIDANT AND EXTRACTION YIELD FROM CENTELLA ASIATICA LEAVES

Abstract

This study focuses on the statistical optimization of antioxidant and extraction yield from Centella asiatica leaves using Central Composite Designs (CCD) and response surface methodology. The primary objective was to identify influential variables affecting the extraction process, such as extraction time and temperature, using ultrasonic-assisted extraction. The optimized extraction conditions yielded an antioxidant activity of 52.4420%, Total Phenolic Content (TPC) of 0.5000 mg/g, and Total Flavonoid Content (TFC) of 15.3125 mg/g. Statistical analysis revealed significant model terms with an R² value of 0.930, indicating that 93% of the variability in antioxidant yield could be explained by the model. The 'Adeq Precision' ratio of 15.479 confirmed an adequate signal, and the Model F-value of 15.16 (p = 0.0043) highlighted the significance of the model. The findings demonstrate a viable and efficient technique for maximizing the extraction yield of bioactive components from C. asiatica, providing a robust framework for enhancing the efficiency of extracting valuable antioxidants from medicinal plants, which is crucial for natural product research and herbal medicine.