Optimization of Ultrasonic-assisted Extraction and Fatty Acid Composition of Oil from Paeonia suffruticosa Andr. Seed.

Response surface methodology (RSM) was applied to optimize the effects of extraction parameters including time, power, temperature and liquid-to-solid ratio on peony seed oil yield. Box-Behnken design (BBD) was employed for optimization of extraction parameters in oil yield that extracted assisting by ultrasonic while petroleum ether as solvent. The chemical composition of peony seed oil under optimal condition in ultrasonic-assisted extract method was analyzed by gas chromatography-mass spectrometry (GC-MS). The optimal conditions were that extraction time 45 min, extraction temperature 45°C, extraction power 90 W and liquid-to-solid ratio 7:1, respectively. Under this condition, the extraction yield value was 33.90% which was with 95% confidence level, hence indicated the reliability of RSM in optimizing ultrasonic-assisted extraction of oil from Paeonia suffruticosa Andr. seed. Three unsaturated fatty acid of peony oil such as n-3 α-linolenic acid (39.75%), n-6 linoleic acid (26.32%) and the oleic acid (23.66%), totally more than 89.00% was determined at optimum condition.

are prolific in China and widely applied in biomass fuel, industrial processes, spices, medicine, and food. Camellia oleifera, Vernicia fordii, Juglans, and Sapium sebiferum are the four major woody oil crops in China. Among these species, C. oleifera and Juglans are edible oil plants. Using ultrasonic-assisted extraction, a study confirmed that the common oil yield of C. oleifera is between 16.25 to 35.49 , and the unsaturated fatty acid content of oil from this plant ranges from 83.56 to 91.50 7 . The oil yield of Juglans is 45 -48 , and the unsaturated fatty acid content of its oil exceeds 90 8 . Compared with common oil plant s oil yield rate and unsaturated fatty acid content, it can be deduced that peony can be an eligible woody oil plant.
For the development of green extraction which determines to protect the environment and consumers, the extraction process as a unit operation would more focus on diminishing ecologic damage and material waste 9 . To higher extraction efficiency and lower energy consumption, the conventional extraction process, such as press and Soxhlet extraction, gradually replaced by innovative technologies. Three methods assisted by innovative technologies for oil extraction include ultrasonic-assisted extraction, microwave-assisted extraction, supercritical carbon dioxide fluid extraction. Supercritical carbon dioxide fluid extraction and provide the highest oil yield but limited by equipment 10 . Microwave-assisted and ultrasonic-assisted extraction method are more convenient than supercritical carbon dioxide fluid extraction and show higher oil yield than the conventional processes. Compared with the other two extraction processes, ultrasonic-assisted extraction is the most appropriate method given its faster and more effective energy use, high extraction yield, safety, complexity, and rapidity 11 . With the microscopic observations, the chain detexturation mechanism which ultrasound helps release the deeper substance had clarified in a special order following treating time: local erosion, shear forces, sonoporation, fragmentation, capillary effect, and detexturation is proved 12 . And ultrasound effect not limits to the surface but goes deeper to disruption at the tissue level, which helps release more target content. However, the fatty acid extracted by ultrasound usually shows slightly higher in peroxide value than conventional method 13,14 . It is proved that initiators, oxygen, enzymes, metals, light and temperature lead fatty acid to oxidation 14 . Avoiding reaction system attaching to oxygen and metal may be an effective method to diminish the degradation and enhance the quality of the oil.
Response surface methodology RSM is a collection of mathematical and statistical techniques for modeling and analysis of problems to optimize a response of interest that is influenced by several quantifiable variables factors 15 . There are many RSM methods, and the more commonly used are Box-Behnken Design BBD and Central Compos-ite Design CCD . BBD is suitable for three-level optimization experiments with 2 to 5 experimental factors, while CCD is generally suitable for three-level optimization experiments with three experimental factors. Compared with CCD, BBD is more suitable in employing for optimization of processes that sets 4 variables and gives its rational design and excellent analysis 16 . However, the precision of analysis result is easy affected by the optimal selection of factor s level. It s better to perform single-factor experiment in advance for optimal factor level selection. The single-factor experiment would keep one factor change in wider range while the other factors hold the line. And then finding the relationship between result and the variable for easy narrow the factor level.
In this study, a single-factor experiment was first performed in order to select suitable factor levels. The ultrasonic-assisted extraction method will be used, the seeds of the oil peony variety Fengdan 17 are used as raw materials, and petroleum ether is used as the extractant. Based on the single-factor experiment, BBD will be used in a narrow level 18 . Using multiple quadratic regression equations to fit the relationship between response values and factors, using multiple quadratic equation models to determine the best extraction process for the four factors of time, temperature, power, and liquid-to-solid ratio; finally, GC-MS analyzes the composition of unsaturated fatty acids in crude oil made by optimal technology in order to provide technical support for the development and utilization of peony seed oil.

Plant material
Peony Fengdan , originating from Bozhou, Anhui seeds were oven dried at 60 for 72 h. Cores were separated from seeds by hand. The samples were smashed through a 60-mesh sieve into uniformly sized grains and stored at room temperature 25 .

Chemicals and reagents
Pure water was made by Barnstead in the laboratory. Petroleum ether boiling range, 30-60 , sulfuric acid, methanol, hexane, and anhydrous sodium sulfate were purchased from Sinopharm Chemical Reagent Co., Ltd.

Apparatus
A 200 W 40 kHz SB-5200DTD ultrasonic cleaner Ningbo Scientz Biotechnology Co., Ltd., Ningbo, China was used for oil extraction from peony seeds. The seeds were pulverized using a 14,000 W, 34,000 r/min multifunction pulverizer. GC-MS analysis was performed by gas chromatographytriple quadrupole mass spectrometer purchased from Agilent Technologies Inc. America .

Ultrasound-assisted extraction
Ultrasound-assisted extraction was performed in a temperature-controlled ultrasonic cleaner following single-factor experiment table or BBD factor design table. With a view to actual input power from the device would converted to heat which is dissipated in the medium, the actual absorbing ultrasound power ought to be assessed by calorimetric measurements, calculated as shown in the Eq. 1 below 19 .
where c p is the heat capacity of the solvent at constant pressure J/g/ , m is the mass of solvent g and dT/dt is temperature rise per second.
However, the solvent used in this experiment is petroleum ether which is heterogeneous system that can t determine the heat capacity. Therefore, the output power of the device is still used in the experimental data to represent the actual power.
The liquid-to-solid ratio was monitored under the table and was varied from 3:1 to 9:1. The mixture of peony seed powder and petroleum ether solvent was placed in a beaker and sealed with plastic wrap. The controlled ultrasonic cleaning instrument was set at a constant temperature varying from 30 to 60 and power varying from 60 W to 160 W . The beaker was placed in the ultrasonic cleaner water bath for specific durations varying from 20 min to 70 min 20 . After leaching was completed, the mixture was filtered, distilled, and dried to a constant weight in the oven. Peony oil yield was calculated by using Eq. 2 . oil yield weight of extracted oil, g weight of dry peony seed, g 100 2 2.5 Experimental design 2.5.1 Single-factor experimental design The effect of temperature 30 , 35 , 40 , 45 , 50 , 55 , and 60 on oil yield was determined with petroleum ether as the solvent under the following conditions: liquidto-solid ratio of 1:5, extraction time of 50 min, and power of 80 W. The effect of power 60, 80, 100, 120, 140, and 160 W on oil yield was determined with petroleum ether as the solvent under the following conditions: temperature of 45 , the liquid-to-solid ratio of 1:5, and extraction time of 50 min. The effect of liquid-to-solid ratio 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, and 9:1 on oil yield was determined with petroleum ether as the solvent under the following conditions: temperature of 45 , power of 100 W, and extraction time of 50 min. The effect of time 20, 30, 40, 50, 60, and 70 min on oil yield was determined with petroleum ether as the solvent under the following conditions: temperature of 45 , power of 100 W, and liquid-to-solid ratio of 1:5.

RSM design and data analysis
The extraction temperature, extraction power, liquid-tosolid ratio, and extraction time were selected as the variable factors and were represented as A, B, C, and D, respectively. Oil yield was used as the evaluation index. Based on the single-factor experiment results, three appropriate factor levels were selected and coded as 1, 0, and 1 Table 1 . A three-level, four-variable BBD was employed. A total of 29 experiments Table 2 were required for the optimization of the extraction parameters. An efficient experimental process was used to obtain representative experimental data.
The second-order polynomial Eq. 3 , which includes all interaction terms, was used to calculate predicted response y : where y is the response, b 0 is the offset term, b i is the linear effect, b ii is the squared effect, b ij is the interaction effect, and x i and x j are independent variables. Data were analyzed by Design Expert 10.0.7 , and coefficients were interpreted using F-test. Analysis of variance ANOVA , regression analysis, and plotting of response surface plots were conducted to examine the significance of the data and the quality of model fit.

Pretreatment: methyl esteri cation
Long-chain fatty acids are unstable at high temperatures and are easily lost during the analysis, so they cannot be analyzed directly through GC-MS unless they are derivatized into volatile methyl esters 21 . In order to get stationary phase and clear peak, before analyzing the components  22 , peony seed oil was pretreated through sulfuric acid-methanol esterification. Peony seed oil 1 g was placed in a conical flask and added with 10 mL of sulfuric acid-methanol volume ratio 1:10, v/ v . The mixture rested for 10 min at room temperature. An equivalent volume of hexane was added for extraction. The remainder was extracted with an equivalent volume of hexane. The two extracts were combined and washed with pure water several times to layer the product. The extract was dried with anhydrous sodium sulfate. After filtration and centrifugation 5,000 r/min, 10 min , the supernatant was subjected to GC-MS analysis.

GC-MS analysis
Chromatography was performed with HP-5 capillary column 30 mm 0.25 mm, 0.33 m . The initial temperature was held at 140 for 5 min, then increased at the rate of 4 /min to the final temperature of 240 , and held for 25 min. The carrier gas was high-purity helium, and the Mass spectrometry was performed under the following conditions: ion source for EI source, ion source temperature of 230 , electronic energy of 70 eV, and mass scanning range of 40-450 m/z.
Quantitative analysis was performed by referring to the NIST98 MS library and consulting the relevant literature. The composition and relative percentage content of the fatty acids of peony seed oil were analyzed.

Single-factor experiment
The first single-factor experiment set temperature as the variable that change in the range of 30, 35, 40, 45, 50, 55, 60 when liquid-to-solid ratio was 5:1, time was 50 min, and power was 80 W.
As shown in Fig. 1 A , the oil yield of peony seed first increased from 28.55 to 33.05 when the temperature rose from 30 to 45 , and then decreased from 33.05 to 29.78 when the temperature rose from 45 to 60 . The oil yield peaked at 45 . At 30 -45 , higher temperatures reduced oil viscosity and facilitated the movement of oil molecules from the seeds 23 . Thereby extraction accelerated and oil yield increased. However, high temperatures also promoted solvent volatilization which induced the oil-solvent contact time decrease. Moreover, heat may induce oil denaturation 24 . These all effects eventually led to a decrease in oil yield at 45-60 .
The second single-factor experiment set power as variable that change in the range of 60, 80, 100, 120, 140, 160 W when liquid-to-solid ratio was 5:1, time was 50 min, and the temperature was 45 . Figure 1 B shows that the highest oil yield of 33.39 was obtained when the power was set at 80 W. The oil yield of peony seed first increased at 60-80 W and then decreased at 80-160 W with increasing power. With increasing power, the cavitation effect and mechanical action intensified, which led to the increased frequency of blasting and an increase in oil dissolution. However, when the power exceeded 80 W, the thermal effect promoted the decomposition and degeneration of fatty acids as well as peony seed oil. That would reduce the oil yield 25 .
As shown in Fig. 1 C , the maximum oil yield of 31.09 was obtained when the liquid-to-solid ratio was 7:1. When the liquid-to-solid ratio was 3:1-7:1, the oil yield steadily increased. The increase in the difference in oil concentration between peony grains and solvent increased the diffusion rate, which resulted in the increase in the oil yield. Furthermore, increasing the extraction solvent was conducive to increasing the contact area between the solvent and peony grains. Continue to increase the amount of solvent, the concentration of oil and fat in the solution drops, resulting in excess leaching agents, which goes against the concept of green extraction. And because of the large amount of leaching agent, multiple suction and distillation are required, which is easy to cause oil loss during operation. Thus, the ideal range selected for the liquid-to-solid ratio was 6:1-8:1.
The fourth single-factor experiment set time as variable that change in the range of 20, 30, 40, 50, 60, 70 min when power was 100 W, time was 50 min, and liquid-to-solid ratio was 5:1.
The effect of time on oil yield is shown in Fig. 1 D . The maximum oil yield was 30.62 when the extraction time was 40 min. The oil yield increased gradually as the extraction time was extended from 20 min to 40 min. Under prolonged extraction time, the physicochemical properties of oil changed due to the thermal effects of ultrasonic waves. This effect led to a reduction in the oil content. Hence, appropriately extending the solid-liquid contact time is con-ducive to the full dissolution of fatty acids 26 .

Optimization of ultrasonic-assisted extraction 3.2.1 Model fitting
Among the 29 experiments, including five replicates Table 2 , experiment 7 extraction temperature 42.5 , extraction power 40 W, liquid-to-solid ratio 7:1, extraction time 40 min provided the highest oil yield ranging from 25.58 to 33. 55 . The influence of each parameter and interaction effect was analyzed by Design Expert 10.0.7 . First, the experimental data were fitted with a significant test with models, including linear, 2FI, quadratic, and cubic models. As shown in Table 3, the quadratic polynomial model was highly significant and rigorous for explaining the relationship between the response and each parameter. ANOVA Table 4 showed that the quadratic polynomial model was highly significant with a low p-value 0.0001 . The lack-of-fit test, which was applied to select the model with a nonsignificant lack-of-fit, showed non-significance for a value greater than 0.05. The F-value of 2.06 implied Optimization of Ultrasonic-assisted Extraction of Oil from Paeonia suffruticosa Andr. Seed that the lack of fit was not significant relative to pure error. The low value of the pure error indicated the satisfactory reproducibility of data from ANOVA and the determination coefficient. Furthermore, the high values of adj R 2 indicated a high correlation. The adj R 2 of the quadratic polynomial model was the highest among the models, and pre R 2 was close to adj R 2 adj R 2 -pre R 2 0.2 . Only 8.59 of the total variation was not explained by the model, indicating that most of the process can be explained by the selected regression model 21 . C.V. was 2.32 , which was less than 10 and demonstrated the reliability and accuracy of the experiment. The signal-to-noise ratio was measured with adequate precision 14.932 , and a value greater than 4 was desirable and indicated an adequate signal that the model could be used to navigate the design space.

Response analysis of oil yield
The effects of ultrasonic-assisted extraction parameters such as extraction time, extraction power, extraction tem-perature, and liquid-to-solid ratio on oil yield from peony were investigated. The predicted code equation in terms of coded factors could be employed to predict the response at the coded levels for each factor 27 and identify the relative effect of the factors through comparison of factor coefficients. The significance of each coefficient was determined based on F-values and p-values 28 . Large F-values and small p-values indicate the high significance of the corresponding coefficients 16 . The response surface analysis of data using Eq. 3 fitted with the quadratic model with a good regression coefficient R 2 0.9241 . As shown in Table 4, the p-values of 0.0001 indicated that the model was highly significant, and that D, A 2 , B 2 , C 2 , and D 2 had a highly significant effect p-value less than 0.0001 on oil yield. A, B, C, AD, BC, BD, and CD had a significant effect p-value less than 0.05 on the results. Only AB had a reduced effect p-value more than 0.1 on ultrasonic-assisted oil extraction. The influence of each factor on the yield of peony seed oil conformed to the following order based on F-values: D extraction time C liquid-tosolid ratio A extraction temperature B extraction power .
The relationship between the extraction parameters and oil yield was investigated using response surface plots. Figure 2 shows the mutual interaction among extraction time, extraction power, extraction temperature, and liquidto-solid ratio on oil yield. Figure 2 A presents the mutual interaction between extraction temperature and power when the liquid-to-solid ratio and time were fixed at 7:1 and 40 min, respectively.
When the temperature was fixed, the oil yield increased first but decreased later with increasing power. Temperature also exhibited quadratic effect on the oil yield when the power was fixed. A peak was observed within the middle values of time and power. High temperatures led to the evaporation of the solvent, thereby decreasing the contact time of the oil and consequently the oil yield.
The mutual interaction between extraction time and liquid-to-solid ratio when the power and temperature were fixed at 40 W and 42.5 , respectively, is shown in Fig. 2 B . The extraction time and the liquid-to-solid ratio exhibited a quadratic effect on the oil yield. The peak in the response surface plots of the mutual interaction of time with the liquid-to-solid ratio was found under the condition of extraction time of 40 min and the liquid-to-solid ratio of 7:1. These values are all in the middle of the range. Further increasing or decreasing the extraction time and power reduced the oil yield. Hence, extraction time and ultrasonic Optimization of Ultrasonic-assisted Extraction of Oil from Paeonia suffruticosa Andr. Seed power had a significant effect on the oil extraction yield.
Highly elliptical contour maps are indicative of highly significant interactions between two factors 16 . The interaction of temperature and power had a weak significant effect, whereas the other factors had significant interaction effects, thereby confirming the ANOVA results.

Optimization of extraction parameters and validation
of models The optimum conditions for the ultrasonic-assisted extraction of oil from peony seeds were determined through the steepest ascent search starting at a point within the model concentration range. The optimal conditions were given by Design Expert 10.0.7 as follows: temperature of 45.51 , power of 88.76 W, the liquid-to-solid ratio of 7.36:1, and extraction time of 45.66 min. The predicted oil yield under the above conditions was 34.14 .
Given the restriction of the virtual conditions, the process parameters were adjusted to the temperature of 45 , power of 90 W, the liquid-to-solid ratio of 7:1, and time of 45 min. Under these conditions, the actual oil yield was 33.90 , which is within the 95 confidence interval of the predicted oil yield. Consequently, the conditions reformed from the model were considered to be feasible and proved the reliability and accuracy of the model.

Chemical pro le of the oil
Before detection, the extracted peony seed oil was stabilized through methyl esterification pretreatment. The fatty acid composition of the ultrasonic-assisted extracted oil was detected through GC-MS. The chemical composition of the main fatty acids of the peony seed oil was identified using information retrieved from the NIST 98 Mass Spectral Library and relevant literature. The relative contents of the main fatty acids were detected through the normaliza- tion of the peak area Table 5 . The content of saturated fatty acids was low. The contents of palmitic and stearic acids were 7.73 and 2.54 , respectively. The predominant fatty acids were polyunsaturated fatty acids, including n-3 α-linolenic acid 39.75 , n-6 linoleic acid 26.32 , and oleic acid 23.66 . The ratio of n-6/n-3 of peony seed oil was 0.66 which was between 0.4 and 1.6 3 . These results are in line with the Chinese peony seed industry standards issued in 2014. This standard state that the content of alpha-linolenic acid should not be less than 38 .

Conclusion
RSM was successfully employed to optimize the ultrasonic-assisted extraction of oil from peony seeds. The optimal conditions including extraction power, extraction time, extraction temperature, and liquid-to-solid ratio were determined using the regression equation and a highly significant fitted model that can be used to predict oil yield. Compared with the oil yield of peanuts, olives, and rapeseed, the oil yield of peony resembles reach the standard of the oil yield of conventional edible oil. Otherwise, the output of peony seeds per unit area can also meet the demand for oil. The GC-MS results revealed that the main chemical components of peony seed oil were unsaturated fatty acids, including n-3 α-linolenic acid 39.75 , n-6 linoleic acid 26.32 , and oleic acid 23.66 . The importance of various types of unsaturated fatty acids has been proved via various studies. Therefore, it is undoubtful that peony seed oil with a high content of unsaturated fatty acids has a strongly hygienical effect on the human body and the research provides a green extraction process assisted with ultrasound in determinative devices. The high oil yield and nutrition profile of oil from C. oleifera indicate that it is a potential source of woody edible oil. This study provides strong theoretical support for optimizing the extraction and development of peony seed oil.