Issue 10, 2018, Issue in Progress

Correlating supercritical fluid extraction parameters with volatile compounds from Finnish wild mushrooms (Craterellus tubaeformis) and yield prediction by partial least squares regression analysis

Abstract

Supercritical fluid was applied to extract volatile compounds from Finnish wild mushrooms (Craterellus tubaeformis). The effects of extraction pressure, temperature and supercritical carbon dioxide volume on extraction yield and the content of mushroom alcohols in the extracts were investigated in the range from 80 to 95 bar, 35 to 55 °C and 30 to 70 mL, respectively. The correlation between extracted volatile compounds and supercritical fluid extraction parameters was studied and prediction models of ten extracted aroma compounds were established by partial least squares regression (PLSR). The calibrated and validated models of 2-octen-1-ol (R_cal = 0.96, R_cal2 = 0.91, R_val = 0.94, R_val2 = 0.88) and geranyl acetone (R_cal = 0.96, R_cal2 = 0.92, R_val = 0.95, R_val2 = 0.90) were satisfactory, and had the predictive capability of 88% and 92%, respectively. Moreover, the predictive equations for other extracted aroma compounds were also proved to be sufficiently accurate. Hence, the present study provides useful reference for extraction of volatile compounds from mushrooms using supercritical fluid for further industrial applications.

Graphical abstract: Correlating supercritical fluid extraction parameters with volatile compounds from Finnish wild mushrooms (Craterellus tubaeformis) and yield prediction by partial least squares regression analysis

Supplementary files

Article information

Article type
Paper
Submitted
15 Nov 2017
Accepted
24 Jan 2018
First published
31 Jan 2018
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2018,8, 5233-5242

Correlating supercritical fluid extraction parameters with volatile compounds from Finnish wild mushrooms (Craterellus tubaeformis) and yield prediction by partial least squares regression analysis

X. Chen, N. Huynh, H. Cui, P. Zhou, X. Zhang and B. Yang, RSC Adv., 2018, 8, 5233 DOI: 10.1039/C7RA12472D

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