NSGA-II Genetic Algorithm Combined with Response Surface Methodology to Optimize the Extraction Process of Active Ingredients of Inonotus obliquus
2022
Haocheng YUN | Fanhua YU | Du CHENG | Zhen LIU | Huazhou NIU | Wanchao HOU | Sainan LI | Chunming LIU | Yuchi ZHANG
This paper aimed to investigate the extraction process of total flavonoids and triterpenes in Inonotus obliquus by ultrasound-assisted enzymatic extraction. The UV spectrophotometric method was used as the detection method, the extraction rate of total triterpenes and flavonoids was used as the evaluation index, the effects of enzyme addition, enzymatic digestion time, liquid to material ratio and ethanol concentration on the extraction rate were investigated, and the best extraction process was obtained by NSGA-II genetic algorithm combined with response surface analysis. Finally, the main chemical components in Inonotus obliquus were analyzed and identified using ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The optimal extraction process for simultaneous extraction of total triterpenes and flavonoids from Inonotus obliquus was obtained by the Pareto front surface B region scheme, and the optimal extraction conditions were determined as enzyme addition of 1.9%, enzymatic digestion time of 45 min, liquid to material ratio of 20 mL/g, and ethanol concentration of 64%. The average extraction rates of total triterpenes and flavonoids were 2.670%±0.05% and 5.356%±0.09%, and the relative errors were 0.75% and 0.70% with the predicted average extraction rates. It was identified that Inonotus obliquus contained four active ingredients: Betulin, lanosterol, osmundacetone and quercetin. The above proved that the test indexes of NSGA-II genetic algorithm combined with response surface optimization of Inonotus obliquus fungus extraction process fitted well with the predicted results.
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