A new method has been proposed for enhancing extraction yield of rutin from Sophora japonica, in which a novel ultrasonic extraction system has been developed to perform the determination of optimum ultrasonic frequency by a two-step procedure. This study has systematically investigated the influence of a continuous frequency range of 20-92 kHz on rutin yields. The effects of different operating conditions on rutin yields have also been studied in detail such as solvent concentration, solvent to solid ratio, ultrasound power, temperature and particle size. A higher extraction yield was obtained at the ultrasonic frequency of 60-62 kHz which was little affected under other extraction conditions. Comparative studies between existing methods and the present method were done to verify the effectiveness of this method. Results indicated that the new extraction method gave a higher extraction yield compared with existing ultrasound-assisted extraction (UAE) and soxhlet extraction (SE). Thus, the potential use of this method may be promising for extraction of natural materials on an industrial scale in the future.

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The novel extraction system was developed to efficiently extract plant material by determining optimum extraction frequency via two steps. Extraction experiments show that this extraction system gave a higher extraction yield compared to existing ultrasonic extraction method.

Ultrasonic-assisted extraction (UAE) of quercetin and rutin from the stalks of Euonymus alatus (Thunb.) Sieb in our laboratory, which aimed at evaluating and optimizing the process parameters, was investigated in this work. In addition, process parameters such as ethanol solution concentration, solvent volume/sample ratio, ultrasound power and extraction time, ultrasound frequency and extraction temperature were also first applied for evaluating the influence of extraction of quercetin and rutin. Optimum process parameters obtained were: ethanol solution 60%, extraction time 30 min, solvent volume/sample ratio 40 mL/g, ultrasound power 200 W, extraction temperature 30 • C and ultrasound frequency 80 kHz. Further a hybrid predictive model, which is based on least squares support vector machine (LS-SVM) in combination with improved fruit fly optimization algorithm (IFOA), was first used to predict the UAE process. The established IFOA-LS-SVM model, in which six process parameters and extraction yields of quercetin and rutin were used as input variables and output variables, respectively, successfully predicted the extraction yields of quercetin and rutin with a low error. Moreover, by comparison with SVM, LS-SVM and multiple regression models, IFOA-LS-SVM model has higher accuracy and faster convergence. Results proved that the proposed model is capable of predicting extraction yields of quercetin and rutin in UAE process.