Multi-Response Modeling for Bio-Compound Ultrasound-Assisted Extraction (UAE) from Matico (Piper aduncum L.) and...

Medicinal plants play an essential role in the food, pharmaceutical, and cosmetic industries due to their ability to prevent and treat diseases. In this study, a three-factor, three-level Box-Behnken experimental design (BBD) with response surface methodology (RSM) was used to maximize the conditions of ultrasound-assisted extraction (UAE) of bioactive compounds from matico and chacruna leaves in terms of total extraction yield (TEY), total phenolic content (TPC) and antioxidant activity (AA) using ABTS and DPPH assays. The effect of methanol concentration (X1: 25%, 50%, and 75%), time (X2: 3, 6, and 9 min), and power (X3: 90, 270, and 450 W) was evaluated as independent variables. The experimental results were fitted to second-order polynomial models, and multiple regression analysis and analysis of variance were used to determine the suitability of the models, using which 3D response surface plots were generated. Considering the multivariable optimization, the best extraction conditions were 73.68% v/v methanol, 9 min, 269.32 W for matico, and 64.84% v/v methanol, 3 min, 344.44 W for chacruna. Under these conditions, the maximum value of 18.33 and 20.83% for TEY, 7.16 and 40.86 mg GAE/g dm for TPC, 56.88 and 526.38 µmol TE/g dm for DPPH were predicted for matico and chacruna, respectively. Practical Applications: This research focused on the modeling by response surface methodology (RSM) of Ultrasound-Assisted Extraction of bioactive compounds from matico and chacruna, Peruvian plants used in traditional medicine. The methodologies used allow the maximization of bioactive extraction, which presented a high recovery of phenolics with high antioxidant activity. These results highlight the use of Amazon plants in traditional medicine and their possible use in other industries such as cosmetic or food safety.