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. 2020 Mar 13;25(6):1309.
doi: 10.3390/molecules25061309.

Ionic Liquid-Based Ultrasonic-Assisted Extraction Coupled with HPLC and Artificial Neural Network Analysis for Ganoderma lucidum

Changqin Li  1   2 , Yiping Cui  1   2 , Jie Lu  1   3 , Cunyu Liu  1   3 , Sitan Chen  1   3 , Changyang Ma  1   3 , Zhenhua Liu  1   3 , Jinmei Wang  1   2 , Wenyi Kang  1   3
Affiliations

Ionic Liquid-Based Ultrasonic-Assisted Extraction Coupled with HPLC and Artificial Neural Network Analysis for Ganoderma lucidum

Changqin Li et al. Molecules. .

Abstract

Ganoderma lucidum is widely used in traditional Chinese medicine (TCM). Ganoderic acid A and D are the main bioactive components with anticancer effects in G. lucidum. To obtain the maximum content of two compounds from G. lucidum, a novel extraction method, an ionic liquid-based ultrasonic-assisted method (ILUAE) was established. Ionic liquids (ILs) of different types and parameters, including the concentration of ILs, ultrasonic power, ultrasonic time, rotational speed, solid-liquid ratio, were optimized by the orthogonal experiment and variance analysis. Under these optimal conditions, the total extraction yield of the two compounds in G. lucidum was 3.31 mg/g, which is 36.21% higher than that of the traditional solvent extraction method. Subsequently, an artificial neural network (ANN) was developed to model the performance of the total extraction yield. The Levenberg-Marquardt back propagation algorithm with the sigmoid transfer function (logsig) at the hidden layer and a linear transfer function (purelin) at the output layer were used. Results showed that single hidden layer with 9 neurons presented the best values for the mean squared error (MSE) and the correlation coefficient (R), with respectively corresponding values of 0.09622 and 0.93332.

Keywords: Ganoderma lucidum; HPLC; artificial neural network; ionic liquid (ILs); ultrasonic-assisted method.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Influence of different extraction solvents. Compared with methanol group: * p < 0.05. Compared with [HMIM] Br/methanol group: ## p < 0.01.
Figure 2
Figure 2
Influence of different types of anions on the extraction yield. Compared with [HMIM] Br/methanol group: ## p < 0.01.
Figure 3
Figure 3
Influence of different types of cations on the extraction yield. Compared with [HMIM] Br/methanol group: # p < 0.05.
Figure 4
Figure 4
Effect of concentration of ionic liquids (ILs) on the extraction yield. Compared with 1.2M group: ** p < 0.01; * p < 0.05.
Figure 5
Figure 5
Effect of ultrasonic power on the extraction yield. Compared with 350 W group: * p < 0.05.
Figure 6
Figure 6
Effect of ultrasonic time on the extraction yield. Compared with 20 min group: *** p < 0.001; ** p < 0.01; * p < 0.05.
Figure 7
Figure 7
Effect of rotational speed on the extraction yield. Compared with 4000 r/min group: * p < 0.05.
Figure 8
Figure 8
Effect of solid–liquid ratio on the extraction yield. Compared with 1:20 g/mL group: * p < 0.05.
Figure 9
Figure 9
Mean squared error (MSE) versus the number of epochs.
Figure 10
Figure 10
Experimental values versus artificial neural network (ANN) predicted values.
Figure 11
Figure 11
Chemical structures of Ganoderic acid A and D.
Figure 12
Figure 12
HPLC chromatograms of the standard solution (1) and the test sample solution (2): (a) Ganoderic acid A, (b) Ganoderic acid D.
Figure 13
Figure 13
Structure of the developed ANN with five inputs and one output.
See this image and copyright information in PMC

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