野薄荷
薄荷醇
共晶体系
超分子化学
深共晶溶剂
化学
萃取(化学)
微波辐射
微波食品加热
有机化学
材料科学
色谱法
计算机科学
精油
晶体结构
催化作用
电信
合金
作者
Zubera Naseem,Muhammad Bilal Qadir,Abdulaziz Bentalib,Zubair Khaliq,Muhammad Zahid,Fayyaz Ahmad,Nimra Nadeem,Anum Javaid
标识
DOI:10.1016/j.ultsonch.2025.107300
摘要
The present study revealed the higher extraction potential of sustainable choline chloride (ChCl) and ethylene glycol (EG) based deep eutectic solvent (DES) from Mentha arvensis via microwave irradiation. The categorical boosting (CatBoost) machine learning model was applied to optimize the extraction process against time (4-8 min), microwave power (160-320 W), and biomass quantity (1-2.0 g/10 mL) with DES. The experimentally optimized TPC 124 ± 4.0 mg GAE/g, TFC 79 ± 3.0 mg QE/g, and DPPH radical inhibition 90 ± 4.0 % evaluated in 6 min at 240 W with 1.0 g biomass. The lowest average relative errors of 0.402 % (TPC), 0.863 % (TFC), and 0.597 % (DPPH) for train and 0.679 % (TPC), 0.685 % (TFC) and 0.480 % (DPPH) for test data showed the consistency with the predicted values. The partial dependence and feature importance revealed the contributing impact of parameters for optimizing the extraction. The average contribution percentage of each predictor to the responses revealed that time contributed 32.5 % (TPC), 35.9 % (TFC), and 18.6 % (DPPH); microwave power contributed 26.7 % (TPC), 25.5 % (TFC), and 44.2 % (DPPH); while biomass contributed 40.8 % (TPC), 38.6 % (TFC), and 37.2 % (DPPH). The significant antibacterial (S. aureus = 25.5 ± 1.4 mm and E. coli = 23.5 ± 1.4 mm) with MICs (S. aureus = 50 ± 2.5 µg/mL and E. coli = 100 ± 1.5 µg/mL) and antifungal potential (F. solani = 22.5 ± 1.4 mm, A. niger = 23.5 ± 0.8 mm), with MIC (F. solani = 100 ± 0.4 µg/mL and A. niger = 50 ± 0.5 µg/mL) of optimized extracts recorded by DES. The DES would be the best alternative to traditional organic solvents based on higher extraction efficiency and sustainability.
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