Hiranpradith Vimolpa, Therdthai Nantawan, Soontrunnarudrungsri Aussama, Rungsuriyawiboon Oumaporn
Department of Product Development, Faculty of Agro-Industry, Kasetsart University, Bangkok 10900, Thailand.
Department of Veterinary Technology, Faculty of Veterinary Technology, Kasetsart University, Bangkok 10900, Thailand.
Foods. 2025 Jan 17;14(2):291. doi: 10.3390/foods14020291.
(CA), known for its health-promoting properties, is rich in bioactive compounds. This study optimised ultrasound-assisted extraction (UAE) parameters to maximise total phenolic content (TPC) and total flavonoid content (TFC) using the response surface methodology (RSM). Ethanol concentration and solvent volume significantly influenced TPC and TFC yields ( < 0.0001), while ultrasonic power had nonsignificant effects ( < 0.05). Time showed no significant effect on TPC ( > 0.05) but influenced TFC due to flavonoids' sensitivity to degradation ( < 0.05). Variable interactions were negligible ( > 0.05). The relationship between responses (TPC and TFC) and independent parameters could be expressed as the quadratic models fitted with a Predicted R of 0.8263 for TPC and 0.9006 for TFC. Based on RSM, the optimal conditions-75% ethanol concentration, 87.5 W ultrasonic power, 30 min extraction time, and 20 mL solvent volume-yielded TPC and TFC values of 52.29 ± 1.65 mg/g and 43.71 ± 1.92 mg/g, closely aligning with model predictions at 95% confidence. Additionally, the optimal UAE condition provided asiaticoside of 37.56 ± 4.25 mg/g and madecassoside of 16.91 ± 1.28 mg/g. This study offers valuable insights into the factors influencing UAE efficiency, sustainability, and scalability for recovering bioactive compounds, underscoring its potential as a sustainable method for developing functional food ingredients from CA.
以其促进健康特性而闻名的积雪草富含生物活性化合物。本研究采用响应面法(RSM)优化超声辅助提取(UAE)参数,以最大化总酚含量(TPC)和总黄酮含量(TFC)。乙醇浓度和溶剂量对TPC和TFC产量有显著影响(P < 0.0001),而超声功率的影响不显著(P < 0.05)。时间对TPC无显著影响(P > 0.05),但由于黄酮类化合物对降解敏感,时间对TFC有影响(P < 0.05)。变量间的相互作用可忽略不计(P > 0.05)。响应值(TPC和TFC)与独立参数之间的关系可以用二次模型表示,TPC的预测决定系数R为0.8263,TFC为0.9006。基于RSM,最佳条件为:乙醇浓度75%、超声功率87.5 W、提取时间30分钟和溶剂量20 mL,此时TPC和TFC值分别为52.29±1.65 mg/g和43.71±1.92 mg/g,在95%置信度下与模型预测值紧密吻合。此外,最佳UAE条件下积雪草苷含量为37.56±4.25 mg/g,羟基积雪草苷含量为16.91±1.28 mg/g。本研究为影响UAE效率、可持续性和可扩展性以回收生物活性化合物的因素提供了有价值的见解,强调了其作为从积雪草中开发功能性食品成分的可持续方法的潜力。