FT-IR data discrimination using principal component analysis toward the green extraction of avocado oil: A study comprehending electrostatic misfits of polar solvents

Abstract

Avocado oil is renowned for its nutritional and health benefits. This study examines the avocado oil extraction process using ethanol and acetone as green solvents to evaluate yield, kinetics, mass transfer, thermodynamics, and oil quality, compared to hexane nonrenewable solvent. Fourier transform infrared spectroscopy combined with principal component analysis (PCA) is used to evaluate the oil composition. UNIFAC and COSMO-SAC models are used to understand the solubility of avocado oil in ethanol and acetone at infinite dilution. In addition, density functional theory is applied to explain the extraction mechanisms. PCA identified key wavelengths in the lipid fingerprint region, while the dry avocado pulp exhibited critical features at around 2924, 2367, 3755, and 2754 cm-1, avocado oil demonstrated crucial signals at 1746, 3746, 3690, and 3801 cm-1. This study found that the oil extracted with acetone and hexane had comparable compositions. The UNIFAC and COSMO-SAC models estimated ΔH∞ values between -8.156 to -47.889 kJ.mol-1 and ΔS∞ between -0.201 to 0.008 kJ.mol-1.K-1. The chemical hardness was calculated to be about 40% higher for ethanol than acetone, while molecular entropy was 10% lower. The results indicate that acetone has the potential to be a greener solvent for avocado oil extraction.