Supercritical fluid extraction and solubilization of Carica papaya linn. leaves in ternary system with CO2 + ethanol solvents

• Published in: Chemical engineering research & design Vol. 156; pp. 31 - 42
• Main Authors: Chai, Yee Ho, Yusup, Suzana, Ruslan, Muhammad Syafiq Hazwan, Chin, Bridgid Lai Fui
• Format: Journal Article
• Language: English
• Published: Rugby Elsevier B.V 01-04-2020; Elsevier Science Ltd
• Subjects: Carbon dioxide; Carica papaya linn; Ethanol; Extraction processes; Flow velocity; Fruits; Linearity; Mathematical models; Papayas; Parameter modification; Response surface methodology; Solubility; Solubility modeling; Solubilization; Solvents; Supercritical fluid extraction; Supercritical fluids; Supercritical processes; Ternary systems; Response surface methodology; Supercritical fluid extraction; Carica papaya linn; Solubility modeling
• ISSN: 0263-8762; 1744-3563
• DOI: 10.1016/j.cherd.2020.01.025

[Display omitted]
•Supercritical fluid extraction of papaya leaves with CO2 + ethanol solvents.•Optimisation of papaya leaves extract yield by response surface methodology.•Solubility of papaya leaves are modelled by density-based solubility models.•Méndez-Santiago and Teja model gave the best prediction with AARD of 1.36%.
The supercritical fluid extraction of Carica papaya linn. leaves in the presence of CO2 solvent and ethanol modifier was carried out with respect to four operating parameters, namely temperature (40–60 °C), pressure (18–30 MPa), solvent flow rate (3–6 mL/min) and co-solvent ratio (3 – 5 vol%), for the maximization of global extract yield of Carica papaya linn. leaves. The optimized parameters obtained are as follows: temperature of 57.47 °C, pressure of 26.62 MPa, solvent flow rate of 5.43 mL/min and co-solvent ratio of 4.98% with a predicted global extract yield of 0.0806 g. Five density-based solubility models, namely Chrastil, Bian et al., Bartle et al., Sparks et al. and Méndez-Santiago and Teja models were correlated against experimental solubility data. The Méndez-Santiago and Teja model were found to be more accurate with AARD of 1.36% and R2 value of 0.873 due to the non-linearity extraction profiles of papaya leaves.