Sustainable extraction of phytochemicals from Mentha arvensis using supramolecular eutectic solvent via microwave Irradiation: Unveiling insights with CatBoost-Driven feature analysis.

Journal: Ultrasonics sonochemistry
PMID:

Abstract

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.

Authors

  • Zubera Naseem
    Department of Textile Engineering, National Textile University, Faisalabad 37610, Pakistan; Department of Chemistry, University of Agriculture Faisalabad 38040, Pakistan.
  • Muhammad Bilal Qadir
    Department of Textile Engineering, National Textile University, Faisalabad 37610, Pakistan.
  • Abdulaziz Bentalib
    Department of Chemical Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia.
  • Zubair Khaliq
    Department of Materials, National Textile University, Faisalabad 37610, Pakistan.
  • Muhammad Zahid
    College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China.
  • Fayyaz Ahmad
    Department of Applied Sciences, National Textile University, Faisalabad 37610, Pakistan.
  • Nimra Nadeem
    Department of Textile Engineering, National Textile University, Faisalabad 37610, Pakistan; Department of Chemistry, University of Agriculture Faisalabad 38040, Pakistan.
  • Anum Javaid
    Shanghai Jiao Tong University Minhang Campus School of Materials Science and Engineering, China.