Chen Xiao, Huynh Nghia, Cui Heping, Zhou Peng, Zhang Xiaoming, Yang Baoru
State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University Lihu Road 1800 Wuxi Jiangsu 214122 China
Food Chemistry and Food Development, Department of Biochemistry, University of Turku FIN-20014 Turku Finland
RSC Adv. 2018 Jan 31;8(10):5233-5242. doi: 10.1039/c7ra12472d. eCollection 2018 Jan 29.
Supercritical fluid was applied to extract volatile compounds from Finnish wild mushrooms (). 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 ( = 0.96, = 0.91, = 0.94, = 0.88) and geranyl acetone ( = 0.96, = 0.92, = 0.95, = 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.
采用超临界流体从芬兰野生蘑菇中提取挥发性化合物。分别在80至95巴、35至55℃和30至70毫升的范围内，研究了萃取压力、温度和超临界二氧化碳体积对萃取产率和提取物中蘑菇醇含量的影响。研究了提取的挥发性化合物与超临界流体萃取参数之间的相关性，并通过偏最小二乘回归（PLSR）建立了十种提取的香气化合物的预测模型。2-辛烯-1-醇（校准模型R² = 0.96，验证模型R² = 0.91，RMSEP = 0.94，Q² = 0.88）和香叶基丙酮（校准模型R² = 0.96，验证模型R² = 0.92，RMSEP = 0.95，Q² = 0.90）的校准和验证模型令人满意，预测能力分别为88%和92%。此外，其他提取的香气化合物的预测方程也被证明足够准确。因此，本研究为利用超临界流体从蘑菇中提取挥发性化合物以供进一步工业应用提供了有用的参考。
