Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Industrial Crops and Products 76 (2015) 18–24

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Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology Hui-Zhen Li, Zhi-Jun Zhang ∗ , Tian-Yu Hou, Xiao-Jun Li, Tie Chen School of Chemical Engineering and Environment, North University of China, Taiyuan 030051, China

a r t i c l e

i n f o

Article history: Received 12 February 2015 Received in revised form 5 June 2015 Accepted 7 June 2015 Keywords: Perilla seed oil Optimization by RSM Physical and chemical characteristics Fatty acids composition

a b s t r a c t Response surface methodology (RSM) was used to optimize ultrasound-assisted extraction (UAE) conditions of perilla seed oil including extraction temperature, time, and liquid-to-solid ratio. The results revealed that extraction time had a significant effect on oil yield. Based on the RSM results, the optimum conditions included an extraction temperature of 41.26 ◦ C, an extraction time of 17.11 min, and a liquidto-solid ratio of 7.02:1. Under these conditions, the maximum oil yield was 36.27%. The physical and chemical characteristics of perilla oil were evaluated. Perilla had high iodine and low acid and peroxide values, indicating that the seed oil has the good qualities of an edible oil and can be stored for a long period of time without deterioration. The fatty acid profile of perilla oil included saturated (6.99%), monounsaturated (16.76%), and polyunsaturated fatty acids (76.25%). Linolenic (63.93%), linoleic (12.32%), and oleic acid (16.65%) were the main fatty acids in perilla seed oil. The thermal stability experiments revealed that perilla oil decomposition began at 320.2 ◦ C, with two stages at 421.3 ◦ C and 466.6 ◦ C. Based on its physical and chemical properties, perilla oil should have applications in the cosmetic, pharmaceutical, and food industries. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Perilla (Perilla frutescens), an aromatic vegetable, has been used to treat fish and crab poisoning (Takahashi, 1969) and is widely used for cooking and medicinal purposes in several Asian countries (Igarashi and Miyazaki, 2013). Perilla seeds contain high levels of ␣-linolenic acid (ALA, C18:3) (Shin and Kim, 1994; Seong and Song, 2012), ranging from 52.58 to 61.98% (Zhou et al., 2014; Ciftci et al., 2012). Studies have reported that increased dietary intake levels of ALA, a precursor of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have beneficial effects in human health (Lee and Song, 2012). Conventional medicine has demonstrated that perilla oil can be used in the treatment of indigestion, depression, and certain cardiovascular diseases (Jo et al., 2013). In addition to ALA, several other compounds have been identified in perilla oil, including vitamin E, sterols, flavonoids, and phenolic compounds (Lee et al., 2013). As a result of its medicinal properties and nutrient profile (Eckert et al., 2010), it is crucial to develop methods for the extraction of perilla oil. There are several available methods for the extraction of oils from plant seeds, including organic solvent, aqueous enzymatic,

∗ Corresponding author. E-mail address: [email protected] (Z.-J. Zhang). http://dx.doi.org/10.1016/j.indcrop.2015.06.021 0926-6690/© 2015 Elsevier B.V. All rights reserved.

and supercritical CO2 extraction (Jia et al., 2013). Among these methods, aqueous enzymatic extraction and supercritical CO2 extraction are costly. Solvent extraction is commonly used because of its simplicity and cost-effectiveness. Ultrasonic extraction, which has gained increasing popularity, can be used in conjunction with, or in place of, traditional extraction techniques because of its reduced extraction times and cost-effectiveness (Mierzwa et al., 1997). Ultrasound-assisted extraction (UAE) contributes to high extraction yield and is easily adapted to industrial scale applications (Cravotto et al., 2008; Vinatoru, 2001). However, no studies have focused on the optimization of perilla oil extraction. Response surface methodology (RSM), which was first introduced by Box and Wilson (1951), is a useful tool for optimizing experimental protocols. RSM can be effectively used to evaluate the effects of multiple factors and their interactions on one or more response variables (Xu et al., 2013; Azmir et al., 2014). One of the advantages of RSM is that it reduces the number of experiments and provides a mathematical model (Karacabey and Mazza, 2010; Nagendra et al., 2011; Wang et al., 2012). The objectives of this study were to (a) determine the effects of UAE extraction temperature, time, and liquid-to-solid ratio on perilla oil yield, (b) optimize the extraction conditions of perilla oil using RSM, and (c) analyze the physical and chemical characteristics of perilla oil.

H.-Z. Li et al. / Industrial Crops and Products 76 (2015) 18–24 Table 1 Box–Behnken design and observed responses of perilla oil yield using UAE.

2. Materials and methods 2.1. Plant materials

Run

P. frutescens seeds (oil content: 37.8%) were collected in October 2012 from North University of China (Taiyuan, Shanxi Province, China). The dried seeds were milled to approximately 250 ␮m and stored in air tight containers at room temperature. 2.2. Extraction of perilla oil using UAE Oil was extracted from 5 g of perilla seeds (dried and milled) using n-hexane. The extraction was performed in a tunable ultrasonic bath (TH-400BQG, 220 V and 50 Hz, Tianhua Ultrasonic Electronic Equipment Co., China) at 30 ◦ C for 15 min using a liquidto-solid ratio of 5:1 and a power of 400 W. Following the extraction, a rotary vacuum evaporator (SHZ-95B, Yuhua Ltd., China) was used to remove the solvent. The oil was transferred into a glass vial and stored at 0–4 ◦ C for physical and chemical analyses. Oil yield was determined per seed sample (100 g) on a dry-weight basis, using the following equation, Oil yield (%) =

 weight of extracted oil  weight of seeds

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

UAE temperature

UAE time

Liquid–solid ratio

Oil yield (%)

X1 (◦ C)

X2 (min)

X3 (ml:g)

Experimental values predicted values

40 50 40 30 30 30 40 40 50 50 40 40 50 40 30 40 40

20 15 10 20 10 15 15 20 15 10 15 10 20 15 15 15 15

5:1 9:1 9:1 7:1 7:1 9:1 7:1 9:1 5:1 7:1 7:1 5:1 7:1 7:1 5:1 7:1 7:1

33.20 32.45 25.56 32.25 27.10 30.25 35.58 30.55 28.95 27.55 36.88 27.98 33.45 36.25 28.55 33.95 35.85

32.02 31.05 26.74 32.03 27.09 29.08 35.70 31.94 30.11 27.77 35.70 26.59 33.46 35.70 29.95 35.70 35.70

× 100% oil extraction. Data analyses and RSM were performed with Design Expert software program (Version 8; Stat-Ease, Inc., Minneapolis, MN, USA).

2.3. Single factor experiments The effect of ultrasonic power on total oil extraction was determined at 300, 350, 400, 450, and 500 W with n-hexane as the extraction solvent and an extraction temperature of 30 ◦ C, an extraction time of 15 min, and a liquid-to-solid ratio 5:1. The effect of extraction temperature on total oil extraction was determined at 20, 30, 40, 50, and 60 ◦ C with n-hexane as the extraction solvent and an ultrasonic power of 400 W, an extraction time of 15 min, and a liquid-to-solid ratio of 5:1. The effect of extraction time on total oil extraction was determined at 10, 15, 20, 25, and 30 min with n-hexane as the extraction solvent and an ultrasonic power of 400 W, an extraction temperature of 40 ◦ C, and a liquid-to-solid ratio of 5:1. Finally, the effect of liquid–solid ratio on total oil extraction was determined at different ratios (3:1, 5:1, 7:1, 9:1 and 11:1) with n-hexane as the extraction solvent and an ultrasonic power of 400 W, an extraction temperature of 40 ◦ C, and an extraction time of 15 min. 2.4. RSM design and statistical analysis Based on the single factor experiments, a central composite design was used to determine the effects of three independent variables, i.e., temperature (X1 ), time (X2 ), and liquid-to-solid ratio (X3 ), on perilla oil yield (Y). The independent variables were coded at three levels (−1, 0, and 1). The complete design consisted of 17 experimental points including six replications of the central points (all variables were coded as zero). A randomized experimental order was used to reduce the effect of unexplained variability on the observed response. Table 1 shows the run order, variable conditions, and the experimental and predicted values. A second degree polynomial equation derived from RSM was used, Y = b0 + b1 X 1 + b2 X 2 + b3 X 3 + b11 X 1 2 + b22 X 2 2 + b33 X 3 2 + b12 X 1 X 2 + b13 X 1 X 2 + b23 X 2 X 3

19

(1)

where Y is the response variable (oil yield); b0 , b1 , b2 , b3 , b11 , b22 , . . . are the regression coefficients; and X1, X2 and X3 are the non-coded values for temperature, time, and liquid-to-solid ratio, respectively. Data were analyzed by ANOVA to determine the lack of fit and the effects of linear, quadratic, and interaction variables on perilla

2.5. Characterization of perilla oil Seed moisture was determined by AOAC method 930.15 (AOAC, 1990). Refractive index was determined in a refractometer (KEM Co. Ltd., Series RA-130, Japan). ISO (International Organization for Standardization) standards were used for the determination of peroxide value (ISO 3960, 2001), acid value (ISO 660, 1996), iodine value (ISO 3961, 1996), saponification value (ISO 3657, 2002), and unsaponifiable matter (ISO 3596, 2000).

2.6. Fatty acid composition analysis The fatty acid composition of perilla oil was determined by first converting the oil into fatty acid methyl esters (FAME). Briefly, 1 ml of n-hexane and 200 ␮l of 2 M sodium methoxide were added to 40 mg of oil. The mixture was heated in a water bath at 50 ◦ C for few seconds and mixed with 200 ␮l of 2 N HCl. The top layer (1 ␮l) was injected into a GC (HP-7900, Tianmei Scientific Instrument Co., China) coupled to a flame ionization detector (FID) and a polar capillary column (HP-Innowax polyethylene glycol, 0.25 mm × 30 m × 0.25 ␮m). The detector temperature was 240 ◦ C; the column temperature was held at 120 ◦ C for 1 min, increased to 180 ◦ C at 10 ◦ C/min, increased to 200 ◦ C at 5 ◦ C/min, and held at 200 ◦ C for 4 min. The carrier gas was helium at a flow rate of 1.1 ml/min. The run time was 45 min.

2.7. Phytosterol levels in perilla oil Phytosterol levels were measured according to the method by Schwartz et al. (2008). GC was performed in an HP 7900 (Tianmei Scientific Instrument Co., China), which was run in the splitless mode. The injector and detector temperatures were 300 ◦ C. The column temperature was held at 245 ◦ C for 1 min, increased to 275 ◦ C at 3 ◦ C/min, and held at 275 ◦ C for 20 min. The carrier gas was helium at a flow rate of 3 ml/min. The relative amount of each phytosterol was expressed as milligrams per gram of fat.

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a

c

b

d

Fig. 1. The effect of UAE power (a), UAE temperature (b), UAE time (c) and liquid–solid ration (d) on the yield of perilla oil.

2.8. Tocopherol levels in perilla oil Tocopherol levels were measured according to the method reported by Ixtaina et al. (2011) in a high performance liquid chromatograph (U3000, Thermoelectric Co. Ltd., USA) coupled to a fluorescence detector (Agilent, 1100series) and a Hypersil ODS column (250 mm × 4 mm, Alltech Associates, Inc., USA). The mobile phase consisted of 98% methanol and 2% water at 1 ml/min. Standard tocopherol isomers (Sigma–Aldrich Co., USA) were used for the identification and external calibration of each isomer. 2.9. Thermal stability The thermal stability of perilla oil was assessed by thermogravimetric analysis (TGA) using a NETZSCH STA 449F3 (NETZSCH Instruments, Germany). Approximately 3–4 mg of perilla oil and linseed oil were weighed in solid fat index (SFI) aluminum pans (No. S08/HBB37408, SETARAM); an empty pan was used as a reference. The sample and reference pans were placed inside the calorimeter. Inert nitrogen gas was used to purge gas at 40 ml/min at 10 ◦ C/min. The weight and decomposition temperatures of the oil samples were recorded from room temperature to 700 ◦ C. 3. Results and discussion 3.1. Single factor analysis Oil yield increased with increasing ultrasonic power up to 400 W (Fig. 1a). At ultrasonic power levels >400 W, oil yield decreased. This result was consistent with findings obtained with euphol from Euphorbia tirucalli (Vuong et al., 2014) and in contrast with findings obtained with procyanidins from Larix gmelinii bark (Sun et al., 2013). The results obtained in our study could be attributed to increased oil thermal decomposition at high ultrasonic power

levels. In addition, at ultrasonic power levels >400 W, oil color deepened, indicative of reduced oil quality. Therefore, the optimal UAE power was 400 W. As shown in Fig. 1b, extraction yield increased with increasing extraction temperatures up to 40 ◦ C, followed by a small reduction in oil yield (Fig. 1b). In this study, temperatures >40 ◦ C did not facilitate the oil extraction process. Therefore, the optimal extraction temperature was 40 ◦ C. From 10 to 15 min of extraction time, oil yield increased, reaching a maximum at 15 min (Fig. 1c). However, with prolonged extraction time, extraction yield remained constant, suggesting that the oil had been completely extracted. Therefore, the optimal extraction time was 15 min. There was a significant increase in oil yield with increasing liquid-to-solid ratios from 5:1 to 7:1. However, at ratios >7:1, extraction yield decreased (Fig. 1d). This result could be attributed to the presence of excess solvent, which may have influenced the cavitation effect of UAE, thereby leading to reduced oil yield. Therefore, the optimal liquid-to-solid ratio was 7:1. 3.2. Second-order polynomial model Perilla oil yield based on the RSM design is shown in Table 1; the ANOVA results are shown in Table 2. The model F value (7.84) and low P value (0.0064) revealed that the model was statistically significant. There was only a 0.64% chance that the model F value was due to error. The coefficient of determination (R2 ) of the model was 0.9098, indicating that 90.98% of the experimental oil yield values matched the model-predicted values. According to Lee et al. (2010), a model is adequate when R2 > 0.75. In this study, lack of fit, which measures the fitness of the model, was not significant (P > 0.05); therefore, the number of experiments were sufficient to determine the effects of the independent variables on perilla oil yield (Montgomery, 2001). The results revealed that the mathe-

H.-Z. Li et al. / Industrial Crops and Products 76 (2015) 18–24 Table 2 Analysis of variance (ANOVA) for the quadratic polynomial mode. source Model X1 X2 X3 X1 X2 X1 X3 X2 X3 X1 2 X2 2 X3 2 Residual Lack of fit Pure error Cor total R2 Adj.R2 *

Sum of squares 183.32 2.26 56.50 2.112E-003 0.14 0.81 0.013 25.14 42.34 43.35 18.18 13.39 4.79 201.50 0.9098 0.7938

df 9 1 1 1 1 1 1 1 1 1 7 3 4 16

Mean square 20.37 2.26 56.50 2.112E-003 0.14 0.81 0.013 25.14 42.34 43.35 2.60 4.46 1.20

F value

21

Table 3 Physical and chemical characteristics of perilla oil. P-value* Prob F

7.84 0.87 21.75 8.134E-004 0.054 0.31 5.092E-003 9.68 16.30 16.69

0.0064 0.3822 0.0023 0.9780 0.8227 0.5939 0.9451 0.0171 0.0049 0.0047

3.72

0.1183

Properties

Value

Moisture and volatile (%) Refractive index Acid value (mg/g oil) Iodine value (g/100 g oil) Saponification value (mg KOH/g oil) Unsaponifiable matter (%) Peroxide value (meq. O2 /kg oil)

0.06 ± 0.03 1.482 ± 0.002 0.773 ± 0.05 176.688 ± 0.35 206.716 ± 0.45 0.6 ± 0.12 1.709 ± 0.15

Phytosterol (mg/kg) Stigmasterol ␤-Sitosterol Campesterol

105.25 ± 3 3186.12 ± 1.2 186.58 ± 1.2

Tocopherol (mg/kg) ␣-Tocopherol ␥-Tocopherol ␦-Tocopherol Physical state at room temperature

33.52 ± 0.002 453.88 ± 0.001 10.85 ± 0.001 Liquid

P < 0.01 highly significant; 0.01 < P < 0.05 significant; P > 0.05 not significant.

matical model was adequate for the prediction of oil yield and was fitted to the following second-order polynomial equation, Y = 35.702 + 0.531X 1 + 2.658X 2 + 0.016X 3 + 0.188X 1 X 2 2

2

+ 0.450X 1 X 3 − 0.058X 1 X 3 − 2.444X 1 − 3.171X 2 − 3.209X 3

of the liquid-to-solid ratio, because the system may have already reached equilibrium with prolonged extraction times. 3.4. Optimization of the conditions

2

The effects of X2 , X2 2 , and X3 2 on oil yield were highly significant (P < 0.01). Similarly, the effect of X1 2 was significant (P < 0.05). On the other hand, X1 , X3 , X1 X2 , X1 X3 , and X2 X3 had no significant effects (P > 0.05) on oil yield. Based on the linear and quadratic coefficients, we concluded that the order of factors affecting the response value of oil yield was extraction time > extraction temperature > liquid-to-solid ratio. 3.3. RSM analysis Three-dimensional (3D) response surface graphs and twodimensional (2D) contour plots were constructed. Response surface graphs are useful to determine the maximum, minimum, and middle points of the response. Contour plots are useful to determine the level of the variables that contribute to a desired response; the levels of the variables are plotted in a curve with equal response. Therefore, contour plots are easier to interpret. Fig. 2 shows the effect of extraction temperature and time on oil yield at a constant liquid-to-solid ratio (7:1). Oil yield increased with increasing extraction time until reaching a plateau at >17 min, indicating that prolonged sonication did not result in further improvements in extraction efficiency. On the other hand, extraction temperatures <41.26 ◦ C had positive effects on oil yield. It is likely that high extraction temperatures reduce mass transfer time and improve oil extraction rates. The effects of temperature and liquid-to-solid ratio on oil yield at a constant extraction time (15 min) are shown in Fig. 3. The interaction between these two variables had a non-significant effect on oil yield; however, the quadratic variables had significant effects on oil yield (P < 0.05). This result may be attributed to the effect of extraction time, which stabilizes the system at 15 min. As a result, the effects of the two variables are non-significant at this extraction time. Fig. 4 shows the effect of extraction time and liquid-to-solid ratio on oil yield at a constant extraction temperature (40 ◦ C). Oil yield increased with increasing extraction time and liquid-to-solid ratio. With prolonged extraction times, oil yield increased until it reached a plateau and subsequently declined with increasing liquid-to-solid ratios. The effect of extraction time was more significant than that

According to the second-order polynomial equation, the optimum conditions for oil yield included a temperature of 41.26 ◦ C, an extraction time of 17.11 min, and a liquid-to-solid ratio of 7.02:1. Under these conditions, the predicted oil yield was 36.30%, which was higher than that obtained from traditional n-hexane extraction (35.2%) and pressing extraction (28.6%). For convenience purposes, the optimum conditions were slightly modified to a temperature of 41 ◦ C, an extraction time of 17 min, and a liquid-to-solid ratio of 7:1. The results revealed that the experimental value (36.27%) was consistent with the predictive values. The extraction conditions obtained by RSM were not only accurate and reliable, but also had practical value (Xu et al., 2013). 3.5. Physical and chemical characteristics of perilla oil At room temperature, perilla oil was yellow and had a higher refractive index (1.482) than soybean oil (1.477) (Nehdi et al., 2012) and corn oil (1.473) (Nehdi, 2011). The iodine value (176.688 g/100 g oil) of perilla oil was higher than that of soybean oil (122.56 g/100 g oil) and corn oil (117.44 g/100 g oil) (Nehdi et al., 2012; Nehdi, 2011). High refractive indexes and iodine values indicate a high content of unsaturated fatty acids (Table 3) and indicates that the seed oil has the qualities of edible oil (Rezig et al., 2012). The acid and peroxide values were very low (0.773 mg/g oil and 1.709 meq. O2 /kg oil, respectively), indicating that perillla oil has high antioxidant capacity. The saponification value of perilla oil (206.716 mg KOH/g oil) was higher than that of soybean oil (179.45 mg KOH/g), linseed oil (190.86 mg KOH/g oil), sunflower oil (188.98 mg KOH/g oil), and olive oil (191.93 mg KOH/g oil) (Cerchiara et al., 2010), which indicates a very high content of low molecular weight triacylglycerols. Nevertheless, perilla oil had a low unsaponifiable value (0.6%). Phytosterols and tocopherols are important components in vegetable oils. In this study, phytosterol and tocopherol levels in perilla oil were determined (Table 3). The results showed that perilla oil contained 105.25, 3186.12, and 186.58 mg/kg stigmasterol, ␤-sitosterol, and campesterol, respectively; ␤-sitosterol was the main sterol. Additionally, perilla oil contained 33.52, 453.88, and 10.85 mg/kg oil of ␣-tocopherol, ␥-tocopherol, and ␦-tocopherol, respectively. Bozan and Temelli (2008) reported similar ␥-tocopherol levels in perilla oil. The total tocopherol content

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Fig. 2. Response surface and contour plot for the oil yield as a function of temperature and time at a fixed liquid–solid ratio of 7:1.

Fig. 3. Response surface and contour plot for the oil yield as a function of temperature and liquid–solid ratio at a fixed time of 15 min.

Fig. 4. Response surface and contour plot for the oil yield as a function of time and liquid–solid ratio at a fixed temperature of 40 ◦ C.

was 498.25 mg/kg oil, which was higher than that of peanut oil (165.5 mg/kg) and rapeseed oil (151.5 mg/kg) (Mou and Chen, 2006). Therefore, perilla oil is a good source of the natural antioxidants, such as phytosterol and tocopherol. 3.6. Fatty acid composition The fatty acid composition of perilla oil is shown in Table 4. ALA, linoleic, and oleic acid were the most abundant unsaturated

fatty acids in perilla oil. ALA (C18:3 , 61.93%), linoleic (C18:2 , 14.32%), and oleic acid (C18:1 , 16.65%) comprised approximately 93% of the total fatty acids in perilla seed oil. Unsaturated fatty acids can affect the physical properties of cell membrane (Nasri et al., 2005). ALA is an omega-3 fatty acid, which is essential for humans; its beneficial health effects are dependent on the ratio between n-6 and n-3 fatty acids, which should be approximately 4–1 (Simopoulos, 2002). Perilla seed oil contains the lowest n-6 to n-3 ratio among several vegetable oils with high ALA levels (Ciftci et al., 2012).

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Fig. 5. TG and DTG of perilla oil (A) and linseed oil (B).

Table 4 Fatty acid composition of perilla oil.

4. Conclusion

Fatty acid composition

Content (%)

Saturated fatty acid Octylic acid (C8:0 ) Palmitic acid (C16:0 ) Stearic acid (C18:0 ) Arachidic acid (C20:0 ) Behenic acid (C22:0 ) Lignoceric acid (C24:0 )

0.68 ± 0.02 4.11 ± 0.15 1.87 ± 0.10 0.18 ± 0.02 0.08 ± 0.01 0.07 ± 0.01

Monoinsaturated fatty acid Palmitoleic (C16:1 ) Oleic acid (C18:1 )

0.11 ± 0.03 16.65 ± 0.05

Polyinsaturated fatty acid Linoleic acid (C18:2 ) Linolenic acid (C18:3 ) SAFA MUFA PUFA P/S

14.32 ± 0.08 61.93 ± 0.10 6.99 16.76 76.25 10.91

Perilla oil extraction was optimized by RSM. The optimum extraction parameters were determined; the predicted oil yield value was in accordance with the experimental value. The optimum UAE conditions of perilla oil included an extraction temperature of 41 ◦ C, an extraction time of 17 min, and a liquid-to-solid ratio of 7:1. Under these conditions, the maximum oil yield was 36.27%. Compared to other oil extraction methods, UAE reduced extraction time and solvent volume and increased perilla oil yield. Perilla oil had high iodine value and low acid and peroxide values; therefore, perilla oil has the good qualities of edible oil. Perilla oil had high levels of phytosterol and tocopherol, which protect against oxidative damage. The major fatty acids were ALA, linoleic, and oleic acid. Additionally, perilla oil contained high levels of polyunsaturated fatty acids. Due to its physical and chemical properties, perilla oil should have applications in the cosmetic, pharmaceutical, and food industries. Acknowledgments

Perilla seed oil has a polyunsaturated/saturated (P/S) ratio of 10.91, which is in accordance with its high refractive index. A high P/S ratio is favorable for the reduction of serum cholesterol levels and atherosclerosis risk and for the prevention of heart disease (Oomah et al., 2002).

This work was supported by the Research Project Supported by Shanxi Scholarship Council of China (2013-80) and International Science and Technology Cooperation Program of Shanxi Province (2013081004). References

3.7. Thermal stability Fig. 5 shows the TG and DTG curves of perilla oil. The weight of the sample remains constant until its decomposition begins. Thermal stability was determined from the onset temperature of decomposition. Onset temperature is defined as the temperature at which sample decomposition begins. Perilla oil had a higher initial decomposition temperature (320.2 ◦ C) than linseed oil (304.8 ◦ C). Therefore, perilla oil was more thermo-stable than linseed oil. A 90% mass loss occurred at 513.2 ◦ C and 512.9 ◦ C in perilla oil and linseed oil, respectively. Perilla oil decomposition occurred in two stages, i.e., at 421.3 ◦ C and 466.60 ◦ C. Linseed oil had three decomposition stages, i.e., at 417.4 ◦ C, 431.3 ◦ C, and 464.0 ◦ C. The number of stages in oil decomposition is dependent on the chemical structure and fatty acid composition of the oil. Thermal stability is dependent on the fatty acid chain length, degree of unsaturation, and branching (Garcia et al., 2010; Borugadda and Goud, 2014). Santos et al. (2004) reported that the first stage could be attributed to the thermal decomposition of polyunsaturated fatty acids. The second and third stages may be attributed to the decomposition of monounsaturated and saturated fatty acids, respectively (Sbihi et al., 2013).

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