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An optimized solid-liquid method for rapid extraction of phorbol esters from Mozambican Jatropha seeds
Industrial Crops & Products 124 (2018) 941–946
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An optimized solid-liquid method for rapid extraction of phorbol esters from Mozambican Jatropha seeds
T
Hercílio E. Zimilaa, Jaime S. Mandlatea,b, Rogério S. Chivodzea, Hermínio F. Muiamboa, ⁎ Victor Skripetsa, Amália A. Uamussea, a b
Department of Chemistry, Eduardo Mondlane University, P.O. Box 257, Main Campus, Maputo, Mozambique Departamento de Química, Universidade Federal de Santa Maria, 97105-900, Santa Maria, RS, Brazil
A R T I C LE I N FO
A B S T R A C T
Keywords: Phorbol esters Extraction Optimization Validation Experimental design
The method of extraction of phorbol esters from Jatropha curcas L. (Jatropha) seed was optimized, using an experimental design, and validated in this study. Variables such as extraction time, vortex-stirring rate, sample:solvent ratio, solvent type and extraction cycles, were selected and their influence on the extraction yield was screened by Plackett-Burman design. Thereafter, the three factors (extraction time, stirring rate and sample:solvent ratio) were optimized by response surface methodology based on Box-Behnken design. The results revealed that the best conditions to achieve optimum response are sample:methanol ratio of 1 mg:50 μL, two extraction cycles under vortex stirring at 3200 rpm for 3 min/cycle. This method shows good recoveries (84–95%), repeatability (RSD = 1.89%), linearity (R2 = 0.999), robustness, limits of detection (2.19 ng μL−1) and quantitation (6.65 ng μL–1). Using this method, phorbol esters can be extracted for quantification purposes, toxicological studies and application as biopesticides and anti-HIV agents.
1. Introduction
butadienyl]-6′-[16′,18′,20′-nonatrienyl]-bicyclo[3.1.0]hexane-(13-O)2′-[carboxylate]-(16-O)-3′-]8′-butenoic-10′]ate (DHPB), whose structure is shown in Fig. 1 (Hirota et al., 1988). In mammalians, PEs act as tumour-promoters (co-carcinogenic substances) and skin-irritants (Wink et al., 1997) and can reach the tissues by several routes, including dermal, ocular, and oral exposures (Devappa et al., 2013b; Takechi and Imou, 2015). Despite such deleterious effects, these compounds seem to have interesting agricultural and pharmaceutical applications (Devappa, 2012). Indeed, Devappa et al. (2010b) attributed the molluscicidal, insecticidal and antimicrobial activities of methanolic extracts of many parts of Jatropha to PEs. Studies carried out by Devappa et al. (2012) showed that phorbol ester enriched fraction (PEEF) is a potential biocontrol agent of Spodoptera frugiperda insect that commonly attacks crops such as corn, cabbage and potatoes. In addition, Devappa (2012) reported a method for conversion of Jatropha PEs into prostratin, a promising adjuvant in HIV therapy. Therefore, a suitable exploitation of the potential of PEs would increase both the value-chain and economic viability of Jatropha products as well as reduce the occupational exposure in handling Jatropha products. To achieve such goal, the development of a rapid and accurate method for extraction and quantitation of PEs is of paramount importance.
Jatropha curcas L. (Jatropha) belongs to one of the largest and genetically diverse plant family, Euphorbiaceae. It is a drought-resistant oil-crop that has been gaining more attention in the last few decades as a promising environmentally friendly biodiesel feedstock (Brittaine and Lutaladio, 2010). Jatropha is a native plant from South America but largely distributed and grown in almost all tropical and sub-tropical areas around the world (Gübitz et al., 1999; Kumar et al., 2016). De-husked Jatropha seeds contain up to 60% of oil (Makkar et al., 1997) with very interesting composition and physicochemical properties for application in diesel engines after transesterification (Gübitz et al., 1999). Additionally, the direct competition of this oil with food industry is reduced due to the presence of antinutritional and toxic substances, which play a crucial role in defence of Jatropha plant against invaders (Devappa et al., 2010a; Devappa, 2012). Among such secondary metabolites of Jatropha, phorbol esters (PEs) are the most investigated. Structures of six different PEs occurring in Jatropha oil were exhaustively described by Haas et al. (2002). They are intramolecular diesters of the same diterpenic moiety of 12-deoxy-16hydroxyphorbol with different dicarboxylic acid. The most abundant phorbol ester in Jatropha is 12-deoxy-16-hydroxyphorbol-4′-[12′,14′-
⁎
Corresponding author. E-mail address: [email protected] (A.A. Uamusse).
https://doi.org/10.1016/j.indcrop.2018.08.017 Received 16 May 2018; Received in revised form 8 July 2018; Accepted 7 August 2018 Available online 06 September 2018 0926-6690/ © 2018 Published by Elsevier B.V.
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Japan. Ultra-pure water was obtained from a Milli-Q system (Milli-Q direct 8.0, Japan). 2.2. Sampling and sample pre-preparation Jatropha seeds were harvested on June 2016 from Jatropha plants cultivated in Boane, Maputo, Mozambique (26°02′20.4″ South, 32°21′06.5″ East, annual rainfall 752 mm and 23.7 °C mean temperature). The seeds were stored in polyethylene bags, transported and airdried at room temperature. The seeds were cracked and then the kernels finely grounded using mortar and pestle and stored at –14 °C in screw-capped polypropylene vials. 2.3. General procedure The phorbol esters were extracted according to the method described by Devappa et al. (2013a) with some modifications. Briefly, about 40 mg of sample were placed into 15 mL polypropylene vial, extraction solvent was added (1, 2 or 3 mL) and the mixture stirred in vortex (ThermoScientific LP Vortex Mixer 0–3200 rpm). The sample was allowed to settle until clear phase separation (∼3–5 min) at room temperature (22 °C) and then the upper liquid layer was transferred into a clean 15 mL polypropylene vial. The extraction solvents were methanol or 2% tetrahydrofuran:dichloromethane (1:1) in methanol (THF/DCM/MeOH), which were found to be the best in the study carried out by Devappa et al. (2010c). The extraction parameters were adjusted according to the Plackett-Burman and Box-Behnken designs. The extract was dried at 40 °C under rotary evaporator (with the following model for each part: pump EyelaA−1000S, water-bath EyelaOSB2100 , rotator EyelaN-1200A). The dried residue was redissolved in 400 μL of methanol, filtrated through Nylon syringe filter 0.22 μm (diameter 13 mm) to 600 μL Eppendorf tubes, and analysed by HPLC-UV.
Fig. 1. Chemical structure of Jatropha factor 1: 12-deoxy-16-hydroxyphorbol4′-[12′,14′-butadienyl]-6′-[16′,18′,20′-nonatrienyl]-bicyclo[3.1.0]hexane-(13O)-2′-[carboxylate]-(16-O)-3′-]8′-butenoic-10′]ate (DHPB).
A number of analytical techniques for extraction of PEs from Jatropha seeds are reported in the literature. Such methods require large amounts of sample (400 mg to 4 g), solvent (at least 10 mL) as well as long time for sample preparation (Makkar et al., 1997; MartínezHerrera et al., 2006; Devappa et al., 2013a; Baldini et al., 2014). Thereby, they are unsuitable for daily application in monitoring studies. While the majority employed methanol (Makkar et al., 1997; MartínezHerrera et al., 2006; Devappa et al., 2013a; Baldini et al., 2014; Najjar et al., 2014), other authors had used dichloromethane (Makkar et al., 1997) as the extraction solvent. Some approaches applied Soxhlet extractors (Devappa et al., 2013a; Gogoi et al., 2014), while others assisted the extraction process with ultra-sonic waves (Baldini et al., 2014; Devappa et al., 2013a), stirring (Devappa et al., 2013a) or their combination. Inconsistency in extraction conditions (extraction time, temperature, sample:solvent ratio, and stirring rate) among these methods is evident, and it rises difficulties for fair comparison of the results. Studies focused on the optimization of extraction method of PEs from Jatropha seeds are scarce. Pereira et al. (2015) developed a supercritical method for extraction of PEs from Jatropha seed cake which is more eco-friendly than solvent extraction. However its availability is limited for many research laboratories. Some authors had reported that vortex stirring gives better yields and it is more cost-effective than Soxhlet and sonication methods (Devappa et al., 2013a), but this procedure was not yet optimized nor validated. Given the aspects mentioned above, the present study aimed to apply multivariate approach to optimize the conditions of extraction of PEs from Jatropha seeds. The reliability of the results obtained by the proposed method was ensured carrying out the validation process.
2.4. Experimental design and data analysis To identify the main factors affecting the yield of PEs, a set of five factors (extraction time (1, 3, 5 min), stirring rate (600, 1400, 2200 rpm), sample:solvent ratio (1 mg:25 μL, 1 mg:50 μL, 1 mg:75 μL), extraction cycles (1, 2, 3) and solvent type (MeOH, THF/DCM/MeOH)) were selected and screened by 12-run Plackett-Burman design. Two central points were considered to investigate a possible non-linear behaviour of yield as function of factors levels. Factor levels and the full design matrix are shown in Tables 1 and 2, respectively. The subsequent step was done by performing response surface methodology based on Box-Behnken design to determine the optimal range of the three most important variables, namely: extraction time (1, 3, 5 min), stirring rate (1400, 2300, 3200 rpm) and sample:solvent ratio (1 mg:25 μL, 1 mg:50 μL, 1 mg:75 μL). The factor levels and optimization design matrix are shown in Tables 1 and 4, respectively. A total of 168 Table 1 Factors and levels used in experimental designs. Factor
2. Materials and methods Extraction time (min) (A) Stirring rate (rpm) (B) Extraction cycles (C) Sample:solvente ratio (mg:μL) (D) Solvent type (E)
2.1. Chemicals Methanol (MeOH, CAS # 67-56-1) and acetonitrile (CAS # 75-05-8), both HPLC grade, and dichloromethane (DCM, CAS # 75-09-2) (99%) were supplied by SkyLabs, South Africa. Tetrahydrofuran (THF, CAS # 109-99-9) (98%) and 4-octylphenol (CAS # 1806-26-4) (99%) were from Fluka Chemica (South Africa) and Sigma-Aldrich (South Africa), respectively. DHPB standard were offered by Kurume University, 942
Plackett-Burman design
Box-Behnken design
Factor level
Factor level
−1
0
+1
−1
0
+1
1.0
3.0
5.0
1.0
3.0
5.0
600 1 1:25
1 400 2 1:50
2 200 3 1:75
1 400 – 1:25
2 300 – 1:50
3 200 – 1:75
MeOH
——
THF/ DCM/ MeOH
–
–
–
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yield. Those are: (i) two extraction cycles with methanol, sample:solvent ratio of 1 mg:50 μL, under vortex stirring at 2200 rpm for 5 min; (ii) two extraction cycles with methanol, sample:solvent ratio of 1 mg:50 μL, under vortex stirring at 3200 rpm for 3 min. Recovery was determined by dividing the calculated concentration with the known spiked DHPB concentration in a PEs-free sample. The highest concentration of DHPB obtained during the robustness assay (1.24 mg g−1) was assumed as the highest level (100%). From this concentration, levels of 50% and 150% were calculated and the corresponding values are 0.62 mg g−1 and 1.86 mg g−1, respectively. Then, the PEs-free sample was spiked with DHPB at those levels and extracted according to the developed method. The repeatability was assessed by calculating relative standard deviation (RSD) of the six replicates of the sample.
Table 2 Plackett-Burman design matrix with responses. #
A
B
C
D
E
DHPB (mg g−1)
1 2 3 4 5 6 7 8 9 10 11 12 13 14
1 5 3 1 1 5 1 1 5 5 5 3 5 1
2200 600 1400 2200 600 2200 600 600 600 600 2200 1400 2200 2200
3 1 2 3 1 1 3 1 3 3 3 2 1 1
75 25 50 25 75 75 75 25 75 25 25 50 75 25
MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH MeOH MeOH MeOH THF:DCM/MeOH MeOH MeOH MeOH
0.6702 0.0637 0.6060 0.7644 0.0707 0.6804 0.2839 0.0951 0.3948 0.3343 0.7224 0.6577 0.7108 0.5024
± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0797 0.0035 0.1093 0.0128 0.0078 0.0271 0.0076 0.0038 0.0545 0.0497 0.0015 0.0090 0.0314 0.0599
3. Results and discussion
Where: A – extraction time (min), B – stirring rate (rpm), C – extraction cycles, D sample:solvent ratio (1mg: x μL), E – solvent type.
3.1. Screening experiment
experiments were carried out that include 84 for screening by PlackettBurman design (12-run, 2 central points and three replicates) and 84 for Box-Behnken design (14 essays with three replicates for each). Minitab statistical software version 17.0 was used to generate experimental design matrices as well as to perform data analysis. The whole data evaluation was done at a confidence level of 95%.
A 12-run Plackett-Burman design was performed to identify the most important variables (among five, namely extraction time, stirring rate, sample:solvent ratio, extraction cycles and solvent type) on the PEs extraction yield for further optimization. Two centre points were added to investigate a possible non-linear relationship between the response and the experimental conditions. The design matrix and respective responses obtained under different experimental conditions are summarised in Table 2, and are expressed as mean of DHPB (mg g−1) ± standard deviation. The results were evaluated by ANOVA (Table 3), in which an effect will be significant if p < 0.05. Thus, since p-value of solvent type (MeOH and THF/DCM/MeOH) and sample:solvent ratio is greater than 0.05, these factors are not statistically significant. Meanwhile, extraction time, stirring rate and extraction cycles affects significantly the extraction yield of PEs. Positive slope of the main effects plot (Fig. 2) indicates that the factors have a positive influence on the extraction process. Thus, with exception of the solvent type factor, when the tested factors change from their lowest to the highest levels, the overall extraction yield tends to increase. Important information provided by ANOVA is the significance of curvature, which implies a non-linear relationship of the extraction yield toward these factors. Indeed, Fig. 2 shows that, with exception of the stirring rate, the highest yield is obtained when the factors are in its center points. The substitution of methanol with the mixture tetrahydrofuran:dichloromethane (1:1) reduce slightly the extraction yield, which is opposite to the trend observed by Devappa et al. (2010c) in oil. Differences on the matrix composition could be the main reason for this fact. Besides, this modification may have negatively affected the diffusion rate of methanol through the lipoprotein matrix of the seed kernel. Hence, methanol was chosen for response surface. Although the extraction cycles factor is statistically significant, it
2.5. Detection and quantification of PEs An aliquot of 20 μL of extracts were manually injected in a highperformance liquid chromatography (HPLC) with ultraviolet/visible detector (UV/Vis), Shimadzu LC-20A. Chromatographic separation was carried out at 40 °C on a Inertsil ODS-4 C18 column (5 μm, 4.6 mm × 150 mm, GL Sciences Inc., Tokyo, Japan) protected by a guard column of the same material (4.0 mm × 10 mm). The separation was based on isocratic elution of acetonitrile:water (77:23, v/v) at a flow rate of 1 mL min−1. PEs were detected at 282 nm and its retention time is between 8 and 13 min. An external calibration method, using standard DHPB, was employed for quantification of PEs. The calibration curve was built preparing five standards of DHPB at 2.5, 5.0, 10.0, 25.0 and 50.0 ng μL−1 in methanol. 2.6. Method validation The method performance was evaluated in terms of linearity, selectivity, repeatability, recovery, limits of detection (LOD) and quantification (LOQ). All merit figures were evaluated for the optimized method, whose optimum factor levels are 2 extractions with methanol, at sample:solvent ratio of 1mg:50 μL, under vortex stirring at 3200 rpm for 3 min. The experiments for LOD, LOQ and each level of recovery were done in triplicate, while six replications were performed for repeatability studies. The correlation (r) and determination (R2) coefficients of the calibration curve (Section 2.5) were used to evaluate the linearity. A visual method was employed for estimation of LOD. For this method, PEs-free sample extracts were spiked with DHPB 50 ng μL−1 until observation of a peak clearly distinguishable from the baseline at intensity range of 0 to 30 mV. Meanwhile, the LOQ was calculated as LOQ = 10/3xLOD. In order to investigate the method selectivity, the separation factor (α) of PEs peaks with each other were calculated throughthe Eq. (1).
α=
t2 − t0 with t2 > t1 t1 − t0
Table 3 ANOVA for Plackett-Burman design.
(1)
Where: t2 and t1 are retention times of the desired analyte and the peak closest to this; and t0 is the dead time. Method robustness was assessed by testing the influence of two operational conditions, within the optimum range, on the extraction 943
Source
DF
Adj SS
Adj MS
F-Value
P-Value
Model Blocks Linear Extraction time (min) Stirring rate (rpm) Extraction cycles Sample:solvent ratio Solvent Curvature Error Total
7 1 5 1 1 1 1 1 1 20 27
1.68909 0.00018 1.56416 0.04502 1.31420 0.18266 0.01797 0.00432 0.12475 0.08274 1.77183
0.24130 0.00018 0.31283 0.04502 1.31420 0.18266 0.01797 0.00432 0.12475 0.00414
58.33 0.04 75.62 10.88 317.69 44.15 4.34 1.04 30.16
0.000 0.838 0.000 0.004 0.000 0.000 0.050 0.319 0.000
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Table 4 Box-Behnken design matrix with responses.
Table 5 ANOVA for Box-Behnken design.
#
A
B
D
DHPB (mg g−1)
Source
DF
Adj SS
Adj MS
F-Value
P-Value
1 2 3 4 5 6 7 8 9 10 11 12 13 14
5 3 3 1 3 5 3 1 3 3 1 1 3 5
3200 3200 1400 3200 3200 1400 2300 2300 2300 2300 2300 1400 1400 2300
50 25 75 50 75 50 50 25 50 50 75 50 25 25
0.6588 0.6390 0.3987 0.6750 0.6716 0.6050 0.6822 0.5747 0.7282 0.6139 0.5711 0.3770 0.2948 0.6527
Model Linear Stirring rate (rpm) Extraction time (min) Samp.:solv. ratio Square Stirring rate (rpm)*Stirring rate (rpm) Extraction time (min)*Extraction time (min) Samp.:solv. ratio*Samp.:solv. ratio 2-Way Interaction Stirring rate (rpm)*Extraction time (min) Stirring rate (rpm)*Samp.:solv. ratio Extraction time (min)*Samp.:solv. ratio Error Lack-of-Fit Pure Error Total
9 3 1 1 1 3 1
0.439766 0.296287 0.234665 0.050495 0.011127 0.107803 0.083089
0.048863 0.098762 0.234665 0.050495 0.011127 0.035934 0.083089
23.51 47.52 112.92 24.30 5.35 17.29 39.98
0.000 0.000 0.000 0.000 0.031 0.000 0.000
1
0.004695
0.004695
2.26
0.148
1
0.020508
0.020508
9.87
0.005
3 1
0.035677 0.029801
0.011892 0.029801
5.72 14.34
0.005 0.001
1
0.002542
0.002542
1.22
0.282
1
0.003335
0.003335
1.60
0.220
20 3 17 29
0.041565 0.018717 0.022848 0.481331
0.002078 0.006239 0.001344
4.64
0.015
± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0168 0.0457 0.0443 0.0482 0.0225 0.0312 0.0265 0.0150 0.0385 0.6961 0.0366 0.0236 0.0133 0.0290
Where: A – extraction time (min), B – stirring rate (rpm), and D – sample:solvent ratio (1mg: x μL).
was fixed on two because it cannot have decimal places. On the other hand, sample:solvent ratio was considered for response surface, despite its overall response being insignificant. Its behaviour is similar to the extraction cycles: the highest response is achieved when it is at the centre point. Nevertheless, it can assume decimal places unlike the extraction cycles.
sample:solvent ratio (mg:μL) The determination coefficient (R2), the adjusted determination coefficient (R2-adj) and the prediction determination coefficient (R2pred) are 0.892, 0.863 and 0.810, respectively. Hence, the empirical model can explain over 89% of variability of the extraction yield. High closeness between R2 and R2-adj (< 3%) indicates that the terms of the model are significant. Moreover, it is expected that this model shall explain about 81% of variability in predicting new observations (Montgomery, 2013). Fig. 3 shows the contour plots of the interaction between the three tested factors and the relationship between yield and experiment levels. Holding sample:solvent ratio at 1 mg:50 μL (Fig. 3a), the degree of extraction increases as time and stirring rate increase. The highest yield was achieved when extraction time and stirring rate were in the range of 2.5–5.0 min and 2000–3200 rpm, respectively. When a short extraction time (∼2.5–3.0 min) was applied, the stirring frequency should be high to ensure good extraction efficiencies. This is most likely related to the fact that seed samples are rich in oil and, when crushed, they become pasty which hinders the solvent penetration; and, consequently, the lower extraction yield. Increasing stirring rate, the intermolecular forces (van der Waals attractions, hydrogen and dipole-dipole (cohesive and adhesive) bonds) are weakened (De Castro and García, 2002). So, the extraction yield increases as result of increasing of the surface area. This fact was confirmed by the sample: solvent ratio
3.2. Optimization process Having selected main variables, response surface methodology based on Box-Behnken design was employed for optimization. Two factors were fixed at convenient levels, namely: solvent type (methanol) and extraction cycles (2 extractions). Table 4 shows the design matrix and the results, which are expressed as a mean of DHPB ± standard deviation (SD). The levels of extraction time and sample:solvent ratio are the same as those applied in screening experiment, since their optimum range seems to fall in predefined range (1–5 min for extraction time and 1mg:25 μL to 1 mg:75 μL for sample:solvent ratio). On the other hand, the stirring rate range was increased to 1400–3200 rpm) and its optimum range was found to be beyond 2200 rpm (Fig. 2). Evaluation by ANOVA (Table 5), indicates that the quadratic model is statistically significant, confirming the curvature previously predicted by Plackett-Burman design. The relationship between the extraction yield and significant variables is described by regression model of the Eq. (2). DHPB (mg/g) = 0.6753 + 0.0562 A + 0.1211 B + 0.0264 D – 0.1080 B2 – 0.0546 D2 – 0.0610 AB (2) Where: A – stirring rate (rpm), B – extraction time (min), C –
Fig. 2. Main effects plot from Plackett-Burman design showing the impact of the factors. 944
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Fig. 3. Contour plots for average extraction yield of DHPB: (a) Extraction time vs. stirring rate; (b) Sample:solvent ratio vs stirring rate; (c) Sample:solvent ratio vs extraction time.
vs. stirring rate plot (Fig. 3b), which showed that there is a very close relationship between the yield and the stirring rate than the amount of solvent. Fig. 3c shows that high yield was obtained when extraction was performed during 4.0–5.0 min at sample: solvent ratio of 1:30, at least. However lower ratio hampers the achievement of clear phase separations and it is recommended to work with sample:solvent of 1mg:50 μL. According to these observations, the extraction was carried out with methanol, at sample:solvent ratio of 1 mg:50 μL, under vortex stirring at 3200 rpm for 3 min, with 2 extraction cycles. The content of PEs (mg g−1) obtained in these conditions was 1.24 ± 0.024.
Table 6 Summary of validation results. Validation parameter
Value
LOD (ng μL−1) LOQ (ng μL−1) Repeatability (mg g−1)
4.41 13.36 1.24 ± 0.02 (RSD = 1.89 %)
Robustness Condition I (mg g−1) Condition II (mg g−1) Recovery at spike level of 50 % 100 % 150 % Linearity Separation factors αC2/C1 αC3/C2 αC6/C3 αC4+C5/C6
3.3. Analytical performance of the method This step aimed to ensure that the developed method is suitable for the intended use and that the results derived from it can be utilized to determine the reliability and consistency of the analytical data obtained (Fuster et al., 2015). The validation parameters are summarized in Table 6. The calibration curve showed a strong and positive (r = 0.999, R2 = 0.999) relationship between the concentration of DHPB and the peak area, over all tested analytical range of 2.5–50.0 ng μL−1. Studies reporting LOD and LOQ of the methods for determination of PEs are scarce and mostly estimated as equivalent of 12-O-tetradecanoylphorbol-13-acetate, which don’t occur in Jatropha (Makkar, 2016). In this study, the LOD and LOQ of the method were found to be 4.41 and 13.36 ng μL−1, respectively. The mean of recoveries at the three concentration levels tested is 89.0% ± 6.59 and the method also showed a good repeatability with RSD of 1.89%. As can be seen in Fig. 4, the typical chromatogram PEs, no interfering peaks in the range of retention of PEs could be detected. Additionally, all separation factors (Table 6) of the nearest peaks of PEs were found to be greater than 1. These facts are evidence of the
1.17 ± 0.027 1.24 ± 0.024 87.28 % ± 6.79 95.54 % ± 4.40 84.09 % ± 3.48 r = 0.999 1.10 1.13 1.06 1.07
Fig. 4. Chromatogram of methanol extracts of seeds, highlighting the five peaks of the PEs at the retention time range of 8.5–13 min, obtained under conditions described in the Section 2.5. 945
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selectivity of the method. Extraction time and stirring rate are the factors varied to investigate the method robustness. The paired t-test (at 95%) was employed for comparison of the yield means obtained from both conditions. Since tcrit > |tcalc| (12.71 > 2.13), the differences are not statistically significant and, hence, the method is not affected by small and deliberated changes of the experimental conditions.
Applications of Phorbol Esters From Jatropha curcas Oil. Doctoral thesis. Department of Aquaculture and Animal Nutrition (480b), University of Hohenheim. Devappa, R.K., Makkar, H.P.S., Becker, K., 2010a. Biodegradation of Jatropha curcas phorbol esters in soil. J. Sci. Food Agric. 90, 2090–2097. https://doi.org/10.1002/ jsfa.4056. Devappa, R.K., Makkar, H.P.S., Becker, K., 2010b. Jatropha toxicity: a review. J. Toxicol. Environ. Health Part B 13 (6), 476–507. https://doi.org/10.1080/10937404.2010. 499736. Devappa, R.K., Makkar, H.P.S., Becker, K., 2010c. Optimization of conditions for the extraction of phorbol esters from Jatropha oil. Biomass Bioenergy XXX, 1–9. https:// doi.org/10.1016/j.biombioe.2010.03.001. Devappa, R.K., Angulo-Escalante, M.A., Makkar, H.P.S., Becker, K., 2012. Potential of using phorbol esters as an insecticide against Spodoptera frugiperda. Ind. Crops Prod. 38 (1), 50–53. https://doi.org/10.1016/j.indcrop.2012.01.009. Devappa, R.K., Bingham, J.-P., Khanal, S.K., 2013a. High performance liquid chromatography method for rapid quantification of phorbol esters in Jatropha curcas seed. Ind. Crops Prod. 49, 211–219. https://doi.org/10.1016/j.indcrop.2013.04.044. Devappa, R.K., Roach, J.S., Makkar, H.P.S., Becker, K., 2013b. Ecotoxicology and environmental safety occular and dermal toxicity of Jatropha curcas phorbol esters. Ecotoxicol. Environ. Saf. 94, 172–178. https://doi.org/10.1016/j.ecoenv.2013.04. 021. Fuster, J., Negro, S., Salama, A., Marcianes, P., Boeva, L., Barcia, E., 2015. HPLC-UV method development and validation for the quantification of ropinirole in new PLGA multiparticulate systems: microspheres and nanoparticles. Int. J. Pharm. 491, 310–317. https://doi.org/10.1016/j.ijpharm.2015.06.035. Gogoi, R., Niyogi, U.K., Tyagi, A.K., 2014. Reduction of phorbol ester content in jatropha cake using high energy gamma radiation. J. Radiat. Res. Appl. Sci. 7, 2–6. https://doi. org/10.1016/j.jrras.2014.04.002. Gübitz, G.M., Mittelbach, M., Trabi, M., 1999. Exploitation of the tropical oil seed plant Jatropha curcas L. Bioresour. Technol. 67 (1), 73–82. https://doi.org/10.1016/ S0960-8524(99)00069-3. Haas, W., Sterk, H., Mittelbach, M., 2002. Novel 12-deoxy-16-hydroxyphorbol diesters isolated from the seed oil of Jatropha curcas. J. Nat. Prod. 65 (10), 1434–1440. https://doi.org/10.1021/np020060d. Hirota, M., Suttajit, M., Suguri, H., Endo, Y., Shudo, K., Wongchai, V., Hecker, E., Fujiki, H., 1988. A new tumor promoter from the seed oil of Jatropha curcas L., an intramolecular diester of 12-deoxy-16-hydroxyphorbol. Cancer Res. 48, 5800–5804. Kumar, P., Srivastava, V.C., Jha, M.K., 2016. Jatropha curcas phytotomy and applications: development as a potential biofuel plant through biotechnological advancements. Renew. Sustain. Energy Rev. 59, 818–838. https://doi.org/10.1016/j.rser. 2015.12.358. Makkar, H.P.S., 2016. State-of-the-art on detoxification of Jatropha curcas products aimed for use as animal and fish feed: a review. Anim. Feed Sci. Technol. https://doi. org/10.1016/j.anifeedsci.2016.09.013. Makkar, H.P.S., Becker, K., Sporer, F., Wink, M., 1997. Studies on nutritive potential and toxic constituents of different provenances of Jatropha curcas. J. Agric. Food Chem. 45 (8), 3152–3157. Martínez-Herrera, J., Siddhuraju, P., Francis, G., Dávila-Ortíz, G., Becker, K., 2006. Chemical composition, toxic/antimetabolic constituents, and effects of different treatments on their levels, in four provenances of Jatropha curcas L. from Mexico. Food Chem. 96 (1), 80–89. https://doi.org/10.1016/j.foodchem.2005.01.059. Montgomery, D.C., 2013. Design and Analysis of Experiments, 8th ed. John Wiley & Sons, Inc., USA. Najjar, A., Abdullah, N., Saad, W.Z., Ahmad, S., Oskoueian, E., Abas, F., Gherbawy, Y., 2014. Detoxification of toxic phorbol esters from Malaysian Jatropha curcas Linn. kernel by Trichoderma spp. and endophytic fungi. Int. J. Mol. Sci. 15 (2), 2274–2288. https://doi.org/10.3390/ijms15022274. Pereira, C., de, S.S., Pessoa, F.L., Mendonca, S., Ribeiro, J.A., de, A., Mendes, M.F., 2015. Technical and economic evaluation of phorbol esters extraction from Jatropha curcas seed cake using supercritical carbon dioxide. Adv. Chem. Eng. 5 (3), 1–7. https://doi. org/10.4172/2090-4568.1000132. Takechi, S., Imou, K., 2015. Sustainable energy production system from Jatropha in Mozambique project. 22nd International Conference on Production Research. pp. 1–6. Wink, M., Koschmieder, C., Sauerwein, M., Sporer, F., 1997. Phorbol esters of J. curcas – biological activities and potential applications. In: Gubitz, G.M., Mittelbach, M., Trabi, M. (Eds.), Biofuels and Industrial Products from Jatropha curcas. DBV Graz, Germany, pp. 160–166.
4. Conclusions A method of extraction of PEs from Jatropha seeds was optimized and validated for the first time for this sample matrix. It is an accurate and simple procedure that besides requiring shorter time than commonly used methods (around 10 min compared to 20–80 min), offers quantitative recoveries and consumes reduced amount of both sample and solvent. The analysis can be performed having only 20 mg of sample and 3 mL of solvent. Plackett-Burman and Box-Behnken designs showed that the extraction yield is mainly affected by the stirring rate, presumably due to increasing of the surface area. Extraction time, sample:solvent ratio, and extraction cycles gave the best yield around its centre points, while methanol proved to be ideal extraction solvent. A quadratic empirical model was found to be suitable to describe the PEs extraction yield as a function of the most important factors and its interactions. This model covers over 89% of variability in the experimental data and has good predictive capacity. This method is applicable for extraction of PEs from Jatropha seeds for different purposes, including the toxicity screening of the seeds (for breeding purposes), risk assessment on handling and processing Jatropha products, and isolation of PEs for application in agriculture and pharmaceutical studies. Conflict of interests The authors declare no conflict of interests Acknowledgements The authors would like to express their gratitude to Japan Science and Technology Agency (JST) and the Japan International Cooperation Agency (JICA), for financial support, and to all members of the Project Sustainable Production of Biodiesel from Jathropha in Mozambique, especially from Kurume University. References Baldini, M., Ferfuia, C., Bortolomeazzi, R., Verardo, G., Pascali, J., Piasentier, E., Franceschi, L., 2014. Determination of phorbol esters in seeds and leaves of Jatropha curcas and in animal tissue by high-performance liquid chromatography tandem mass spectrometry. Ind. Crops Prod. 59, 268–276. https://doi.org/10.1016/j. indcrop.2014.05.034. Brittaine, R., Lutaladio, N., 2010. Jatropha: A Smallholder Bioenergy Crop – The Potential for Pro-Poor Development Vol. 8 FAO, Rome. De Castro, M.D.L., García, J.L.L., 2002. High-pressure, high-temperature solvent extraction. Acceleration and Automation of Solid Sample Treatment, 1st ed. Elsevier Science B.V., pp. 233–279. https://doi.org/10.1016/S0167-9244(02)80008-7. Devappa, R.K., 2012. Isolation, Characterization and Potential Agro-pharmaceutical
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An optimized solid-liquid method for rapid extraction of phorbol esters from Mozambican Jatropha seeds
T
Hercílio E. Zimilaa, Jaime S. Mandlatea,b, Rogério S. Chivodzea, Hermínio F. Muiamboa, ⁎ Victor Skripetsa, Amália A. Uamussea, a b
Department of Chemistry, Eduardo Mondlane University, P.O. Box 257, Main Campus, Maputo, Mozambique Departamento de Química, Universidade Federal de Santa Maria, 97105-900, Santa Maria, RS, Brazil
A R T I C LE I N FO
A B S T R A C T
Keywords: Phorbol esters Extraction Optimization Validation Experimental design
The method of extraction of phorbol esters from Jatropha curcas L. (Jatropha) seed was optimized, using an experimental design, and validated in this study. Variables such as extraction time, vortex-stirring rate, sample:solvent ratio, solvent type and extraction cycles, were selected and their influence on the extraction yield was screened by Plackett-Burman design. Thereafter, the three factors (extraction time, stirring rate and sample:solvent ratio) were optimized by response surface methodology based on Box-Behnken design. The results revealed that the best conditions to achieve optimum response are sample:methanol ratio of 1 mg:50 μL, two extraction cycles under vortex stirring at 3200 rpm for 3 min/cycle. This method shows good recoveries (84–95%), repeatability (RSD = 1.89%), linearity (R2 = 0.999), robustness, limits of detection (2.19 ng μL−1) and quantitation (6.65 ng μL–1). Using this method, phorbol esters can be extracted for quantification purposes, toxicological studies and application as biopesticides and anti-HIV agents.
1. Introduction
butadienyl]-6′-[16′,18′,20′-nonatrienyl]-bicyclo[3.1.0]hexane-(13-O)2′-[carboxylate]-(16-O)-3′-]8′-butenoic-10′]ate (DHPB), whose structure is shown in Fig. 1 (Hirota et al., 1988). In mammalians, PEs act as tumour-promoters (co-carcinogenic substances) and skin-irritants (Wink et al., 1997) and can reach the tissues by several routes, including dermal, ocular, and oral exposures (Devappa et al., 2013b; Takechi and Imou, 2015). Despite such deleterious effects, these compounds seem to have interesting agricultural and pharmaceutical applications (Devappa, 2012). Indeed, Devappa et al. (2010b) attributed the molluscicidal, insecticidal and antimicrobial activities of methanolic extracts of many parts of Jatropha to PEs. Studies carried out by Devappa et al. (2012) showed that phorbol ester enriched fraction (PEEF) is a potential biocontrol agent of Spodoptera frugiperda insect that commonly attacks crops such as corn, cabbage and potatoes. In addition, Devappa (2012) reported a method for conversion of Jatropha PEs into prostratin, a promising adjuvant in HIV therapy. Therefore, a suitable exploitation of the potential of PEs would increase both the value-chain and economic viability of Jatropha products as well as reduce the occupational exposure in handling Jatropha products. To achieve such goal, the development of a rapid and accurate method for extraction and quantitation of PEs is of paramount importance.
Jatropha curcas L. (Jatropha) belongs to one of the largest and genetically diverse plant family, Euphorbiaceae. It is a drought-resistant oil-crop that has been gaining more attention in the last few decades as a promising environmentally friendly biodiesel feedstock (Brittaine and Lutaladio, 2010). Jatropha is a native plant from South America but largely distributed and grown in almost all tropical and sub-tropical areas around the world (Gübitz et al., 1999; Kumar et al., 2016). De-husked Jatropha seeds contain up to 60% of oil (Makkar et al., 1997) with very interesting composition and physicochemical properties for application in diesel engines after transesterification (Gübitz et al., 1999). Additionally, the direct competition of this oil with food industry is reduced due to the presence of antinutritional and toxic substances, which play a crucial role in defence of Jatropha plant against invaders (Devappa et al., 2010a; Devappa, 2012). Among such secondary metabolites of Jatropha, phorbol esters (PEs) are the most investigated. Structures of six different PEs occurring in Jatropha oil were exhaustively described by Haas et al. (2002). They are intramolecular diesters of the same diterpenic moiety of 12-deoxy-16hydroxyphorbol with different dicarboxylic acid. The most abundant phorbol ester in Jatropha is 12-deoxy-16-hydroxyphorbol-4′-[12′,14′-
⁎
Corresponding author. E-mail address: [email protected] (A.A. Uamusse).
https://doi.org/10.1016/j.indcrop.2018.08.017 Received 16 May 2018; Received in revised form 8 July 2018; Accepted 7 August 2018 Available online 06 September 2018 0926-6690/ © 2018 Published by Elsevier B.V.
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Japan. Ultra-pure water was obtained from a Milli-Q system (Milli-Q direct 8.0, Japan). 2.2. Sampling and sample pre-preparation Jatropha seeds were harvested on June 2016 from Jatropha plants cultivated in Boane, Maputo, Mozambique (26°02′20.4″ South, 32°21′06.5″ East, annual rainfall 752 mm and 23.7 °C mean temperature). The seeds were stored in polyethylene bags, transported and airdried at room temperature. The seeds were cracked and then the kernels finely grounded using mortar and pestle and stored at –14 °C in screw-capped polypropylene vials. 2.3. General procedure The phorbol esters were extracted according to the method described by Devappa et al. (2013a) with some modifications. Briefly, about 40 mg of sample were placed into 15 mL polypropylene vial, extraction solvent was added (1, 2 or 3 mL) and the mixture stirred in vortex (ThermoScientific LP Vortex Mixer 0–3200 rpm). The sample was allowed to settle until clear phase separation (∼3–5 min) at room temperature (22 °C) and then the upper liquid layer was transferred into a clean 15 mL polypropylene vial. The extraction solvents were methanol or 2% tetrahydrofuran:dichloromethane (1:1) in methanol (THF/DCM/MeOH), which were found to be the best in the study carried out by Devappa et al. (2010c). The extraction parameters were adjusted according to the Plackett-Burman and Box-Behnken designs. The extract was dried at 40 °C under rotary evaporator (with the following model for each part: pump EyelaA−1000S, water-bath EyelaOSB2100 , rotator EyelaN-1200A). The dried residue was redissolved in 400 μL of methanol, filtrated through Nylon syringe filter 0.22 μm (diameter 13 mm) to 600 μL Eppendorf tubes, and analysed by HPLC-UV.
Fig. 1. Chemical structure of Jatropha factor 1: 12-deoxy-16-hydroxyphorbol4′-[12′,14′-butadienyl]-6′-[16′,18′,20′-nonatrienyl]-bicyclo[3.1.0]hexane-(13O)-2′-[carboxylate]-(16-O)-3′-]8′-butenoic-10′]ate (DHPB).
A number of analytical techniques for extraction of PEs from Jatropha seeds are reported in the literature. Such methods require large amounts of sample (400 mg to 4 g), solvent (at least 10 mL) as well as long time for sample preparation (Makkar et al., 1997; MartínezHerrera et al., 2006; Devappa et al., 2013a; Baldini et al., 2014). Thereby, they are unsuitable for daily application in monitoring studies. While the majority employed methanol (Makkar et al., 1997; MartínezHerrera et al., 2006; Devappa et al., 2013a; Baldini et al., 2014; Najjar et al., 2014), other authors had used dichloromethane (Makkar et al., 1997) as the extraction solvent. Some approaches applied Soxhlet extractors (Devappa et al., 2013a; Gogoi et al., 2014), while others assisted the extraction process with ultra-sonic waves (Baldini et al., 2014; Devappa et al., 2013a), stirring (Devappa et al., 2013a) or their combination. Inconsistency in extraction conditions (extraction time, temperature, sample:solvent ratio, and stirring rate) among these methods is evident, and it rises difficulties for fair comparison of the results. Studies focused on the optimization of extraction method of PEs from Jatropha seeds are scarce. Pereira et al. (2015) developed a supercritical method for extraction of PEs from Jatropha seed cake which is more eco-friendly than solvent extraction. However its availability is limited for many research laboratories. Some authors had reported that vortex stirring gives better yields and it is more cost-effective than Soxhlet and sonication methods (Devappa et al., 2013a), but this procedure was not yet optimized nor validated. Given the aspects mentioned above, the present study aimed to apply multivariate approach to optimize the conditions of extraction of PEs from Jatropha seeds. The reliability of the results obtained by the proposed method was ensured carrying out the validation process.
2.4. Experimental design and data analysis To identify the main factors affecting the yield of PEs, a set of five factors (extraction time (1, 3, 5 min), stirring rate (600, 1400, 2200 rpm), sample:solvent ratio (1 mg:25 μL, 1 mg:50 μL, 1 mg:75 μL), extraction cycles (1, 2, 3) and solvent type (MeOH, THF/DCM/MeOH)) were selected and screened by 12-run Plackett-Burman design. Two central points were considered to investigate a possible non-linear behaviour of yield as function of factors levels. Factor levels and the full design matrix are shown in Tables 1 and 2, respectively. The subsequent step was done by performing response surface methodology based on Box-Behnken design to determine the optimal range of the three most important variables, namely: extraction time (1, 3, 5 min), stirring rate (1400, 2300, 3200 rpm) and sample:solvent ratio (1 mg:25 μL, 1 mg:50 μL, 1 mg:75 μL). The factor levels and optimization design matrix are shown in Tables 1 and 4, respectively. A total of 168 Table 1 Factors and levels used in experimental designs. Factor
2. Materials and methods Extraction time (min) (A) Stirring rate (rpm) (B) Extraction cycles (C) Sample:solvente ratio (mg:μL) (D) Solvent type (E)
2.1. Chemicals Methanol (MeOH, CAS # 67-56-1) and acetonitrile (CAS # 75-05-8), both HPLC grade, and dichloromethane (DCM, CAS # 75-09-2) (99%) were supplied by SkyLabs, South Africa. Tetrahydrofuran (THF, CAS # 109-99-9) (98%) and 4-octylphenol (CAS # 1806-26-4) (99%) were from Fluka Chemica (South Africa) and Sigma-Aldrich (South Africa), respectively. DHPB standard were offered by Kurume University, 942
Plackett-Burman design
Box-Behnken design
Factor level
Factor level
−1
0
+1
−1
0
+1
1.0
3.0
5.0
1.0
3.0
5.0
600 1 1:25
1 400 2 1:50
2 200 3 1:75
1 400 – 1:25
2 300 – 1:50
3 200 – 1:75
MeOH
——
THF/ DCM/ MeOH
–
–
–
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yield. Those are: (i) two extraction cycles with methanol, sample:solvent ratio of 1 mg:50 μL, under vortex stirring at 2200 rpm for 5 min; (ii) two extraction cycles with methanol, sample:solvent ratio of 1 mg:50 μL, under vortex stirring at 3200 rpm for 3 min. Recovery was determined by dividing the calculated concentration with the known spiked DHPB concentration in a PEs-free sample. The highest concentration of DHPB obtained during the robustness assay (1.24 mg g−1) was assumed as the highest level (100%). From this concentration, levels of 50% and 150% were calculated and the corresponding values are 0.62 mg g−1 and 1.86 mg g−1, respectively. Then, the PEs-free sample was spiked with DHPB at those levels and extracted according to the developed method. The repeatability was assessed by calculating relative standard deviation (RSD) of the six replicates of the sample.
Table 2 Plackett-Burman design matrix with responses. #
A
B
C
D
E
DHPB (mg g−1)
1 2 3 4 5 6 7 8 9 10 11 12 13 14
1 5 3 1 1 5 1 1 5 5 5 3 5 1
2200 600 1400 2200 600 2200 600 600 600 600 2200 1400 2200 2200
3 1 2 3 1 1 3 1 3 3 3 2 1 1
75 25 50 25 75 75 75 25 75 25 25 50 75 25
MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH THF:DCM/MeOH MeOH MeOH MeOH THF:DCM/MeOH MeOH MeOH MeOH
0.6702 0.0637 0.6060 0.7644 0.0707 0.6804 0.2839 0.0951 0.3948 0.3343 0.7224 0.6577 0.7108 0.5024
± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0797 0.0035 0.1093 0.0128 0.0078 0.0271 0.0076 0.0038 0.0545 0.0497 0.0015 0.0090 0.0314 0.0599
3. Results and discussion
Where: A – extraction time (min), B – stirring rate (rpm), C – extraction cycles, D sample:solvent ratio (1mg: x μL), E – solvent type.
3.1. Screening experiment
experiments were carried out that include 84 for screening by PlackettBurman design (12-run, 2 central points and three replicates) and 84 for Box-Behnken design (14 essays with three replicates for each). Minitab statistical software version 17.0 was used to generate experimental design matrices as well as to perform data analysis. The whole data evaluation was done at a confidence level of 95%.
A 12-run Plackett-Burman design was performed to identify the most important variables (among five, namely extraction time, stirring rate, sample:solvent ratio, extraction cycles and solvent type) on the PEs extraction yield for further optimization. Two centre points were added to investigate a possible non-linear relationship between the response and the experimental conditions. The design matrix and respective responses obtained under different experimental conditions are summarised in Table 2, and are expressed as mean of DHPB (mg g−1) ± standard deviation. The results were evaluated by ANOVA (Table 3), in which an effect will be significant if p < 0.05. Thus, since p-value of solvent type (MeOH and THF/DCM/MeOH) and sample:solvent ratio is greater than 0.05, these factors are not statistically significant. Meanwhile, extraction time, stirring rate and extraction cycles affects significantly the extraction yield of PEs. Positive slope of the main effects plot (Fig. 2) indicates that the factors have a positive influence on the extraction process. Thus, with exception of the solvent type factor, when the tested factors change from their lowest to the highest levels, the overall extraction yield tends to increase. Important information provided by ANOVA is the significance of curvature, which implies a non-linear relationship of the extraction yield toward these factors. Indeed, Fig. 2 shows that, with exception of the stirring rate, the highest yield is obtained when the factors are in its center points. The substitution of methanol with the mixture tetrahydrofuran:dichloromethane (1:1) reduce slightly the extraction yield, which is opposite to the trend observed by Devappa et al. (2010c) in oil. Differences on the matrix composition could be the main reason for this fact. Besides, this modification may have negatively affected the diffusion rate of methanol through the lipoprotein matrix of the seed kernel. Hence, methanol was chosen for response surface. Although the extraction cycles factor is statistically significant, it
2.5. Detection and quantification of PEs An aliquot of 20 μL of extracts were manually injected in a highperformance liquid chromatography (HPLC) with ultraviolet/visible detector (UV/Vis), Shimadzu LC-20A. Chromatographic separation was carried out at 40 °C on a Inertsil ODS-4 C18 column (5 μm, 4.6 mm × 150 mm, GL Sciences Inc., Tokyo, Japan) protected by a guard column of the same material (4.0 mm × 10 mm). The separation was based on isocratic elution of acetonitrile:water (77:23, v/v) at a flow rate of 1 mL min−1. PEs were detected at 282 nm and its retention time is between 8 and 13 min. An external calibration method, using standard DHPB, was employed for quantification of PEs. The calibration curve was built preparing five standards of DHPB at 2.5, 5.0, 10.0, 25.0 and 50.0 ng μL−1 in methanol. 2.6. Method validation The method performance was evaluated in terms of linearity, selectivity, repeatability, recovery, limits of detection (LOD) and quantification (LOQ). All merit figures were evaluated for the optimized method, whose optimum factor levels are 2 extractions with methanol, at sample:solvent ratio of 1mg:50 μL, under vortex stirring at 3200 rpm for 3 min. The experiments for LOD, LOQ and each level of recovery were done in triplicate, while six replications were performed for repeatability studies. The correlation (r) and determination (R2) coefficients of the calibration curve (Section 2.5) were used to evaluate the linearity. A visual method was employed for estimation of LOD. For this method, PEs-free sample extracts were spiked with DHPB 50 ng μL−1 until observation of a peak clearly distinguishable from the baseline at intensity range of 0 to 30 mV. Meanwhile, the LOQ was calculated as LOQ = 10/3xLOD. In order to investigate the method selectivity, the separation factor (α) of PEs peaks with each other were calculated throughthe Eq. (1).
α=
t2 − t0 with t2 > t1 t1 − t0
Table 3 ANOVA for Plackett-Burman design.
(1)
Where: t2 and t1 are retention times of the desired analyte and the peak closest to this; and t0 is the dead time. Method robustness was assessed by testing the influence of two operational conditions, within the optimum range, on the extraction 943
Source
DF
Adj SS
Adj MS
F-Value
P-Value
Model Blocks Linear Extraction time (min) Stirring rate (rpm) Extraction cycles Sample:solvent ratio Solvent Curvature Error Total
7 1 5 1 1 1 1 1 1 20 27
1.68909 0.00018 1.56416 0.04502 1.31420 0.18266 0.01797 0.00432 0.12475 0.08274 1.77183
0.24130 0.00018 0.31283 0.04502 1.31420 0.18266 0.01797 0.00432 0.12475 0.00414
58.33 0.04 75.62 10.88 317.69 44.15 4.34 1.04 30.16
0.000 0.838 0.000 0.004 0.000 0.000 0.050 0.319 0.000
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Table 4 Box-Behnken design matrix with responses.
Table 5 ANOVA for Box-Behnken design.
#
A
B
D
DHPB (mg g−1)
Source
DF
Adj SS
Adj MS
F-Value
P-Value
1 2 3 4 5 6 7 8 9 10 11 12 13 14
5 3 3 1 3 5 3 1 3 3 1 1 3 5
3200 3200 1400 3200 3200 1400 2300 2300 2300 2300 2300 1400 1400 2300
50 25 75 50 75 50 50 25 50 50 75 50 25 25
0.6588 0.6390 0.3987 0.6750 0.6716 0.6050 0.6822 0.5747 0.7282 0.6139 0.5711 0.3770 0.2948 0.6527
Model Linear Stirring rate (rpm) Extraction time (min) Samp.:solv. ratio Square Stirring rate (rpm)*Stirring rate (rpm) Extraction time (min)*Extraction time (min) Samp.:solv. ratio*Samp.:solv. ratio 2-Way Interaction Stirring rate (rpm)*Extraction time (min) Stirring rate (rpm)*Samp.:solv. ratio Extraction time (min)*Samp.:solv. ratio Error Lack-of-Fit Pure Error Total
9 3 1 1 1 3 1
0.439766 0.296287 0.234665 0.050495 0.011127 0.107803 0.083089
0.048863 0.098762 0.234665 0.050495 0.011127 0.035934 0.083089
23.51 47.52 112.92 24.30 5.35 17.29 39.98
0.000 0.000 0.000 0.000 0.031 0.000 0.000
1
0.004695
0.004695
2.26
0.148
1
0.020508
0.020508
9.87
0.005
3 1
0.035677 0.029801
0.011892 0.029801
5.72 14.34
0.005 0.001
1
0.002542
0.002542
1.22
0.282
1
0.003335
0.003335
1.60
0.220
20 3 17 29
0.041565 0.018717 0.022848 0.481331
0.002078 0.006239 0.001344
4.64
0.015
± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0168 0.0457 0.0443 0.0482 0.0225 0.0312 0.0265 0.0150 0.0385 0.6961 0.0366 0.0236 0.0133 0.0290
Where: A – extraction time (min), B – stirring rate (rpm), and D – sample:solvent ratio (1mg: x μL).
was fixed on two because it cannot have decimal places. On the other hand, sample:solvent ratio was considered for response surface, despite its overall response being insignificant. Its behaviour is similar to the extraction cycles: the highest response is achieved when it is at the centre point. Nevertheless, it can assume decimal places unlike the extraction cycles.
sample:solvent ratio (mg:μL) The determination coefficient (R2), the adjusted determination coefficient (R2-adj) and the prediction determination coefficient (R2pred) are 0.892, 0.863 and 0.810, respectively. Hence, the empirical model can explain over 89% of variability of the extraction yield. High closeness between R2 and R2-adj (< 3%) indicates that the terms of the model are significant. Moreover, it is expected that this model shall explain about 81% of variability in predicting new observations (Montgomery, 2013). Fig. 3 shows the contour plots of the interaction between the three tested factors and the relationship between yield and experiment levels. Holding sample:solvent ratio at 1 mg:50 μL (Fig. 3a), the degree of extraction increases as time and stirring rate increase. The highest yield was achieved when extraction time and stirring rate were in the range of 2.5–5.0 min and 2000–3200 rpm, respectively. When a short extraction time (∼2.5–3.0 min) was applied, the stirring frequency should be high to ensure good extraction efficiencies. This is most likely related to the fact that seed samples are rich in oil and, when crushed, they become pasty which hinders the solvent penetration; and, consequently, the lower extraction yield. Increasing stirring rate, the intermolecular forces (van der Waals attractions, hydrogen and dipole-dipole (cohesive and adhesive) bonds) are weakened (De Castro and García, 2002). So, the extraction yield increases as result of increasing of the surface area. This fact was confirmed by the sample: solvent ratio
3.2. Optimization process Having selected main variables, response surface methodology based on Box-Behnken design was employed for optimization. Two factors were fixed at convenient levels, namely: solvent type (methanol) and extraction cycles (2 extractions). Table 4 shows the design matrix and the results, which are expressed as a mean of DHPB ± standard deviation (SD). The levels of extraction time and sample:solvent ratio are the same as those applied in screening experiment, since their optimum range seems to fall in predefined range (1–5 min for extraction time and 1mg:25 μL to 1 mg:75 μL for sample:solvent ratio). On the other hand, the stirring rate range was increased to 1400–3200 rpm) and its optimum range was found to be beyond 2200 rpm (Fig. 2). Evaluation by ANOVA (Table 5), indicates that the quadratic model is statistically significant, confirming the curvature previously predicted by Plackett-Burman design. The relationship between the extraction yield and significant variables is described by regression model of the Eq. (2). DHPB (mg/g) = 0.6753 + 0.0562 A + 0.1211 B + 0.0264 D – 0.1080 B2 – 0.0546 D2 – 0.0610 AB (2) Where: A – stirring rate (rpm), B – extraction time (min), C –
Fig. 2. Main effects plot from Plackett-Burman design showing the impact of the factors. 944
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Fig. 3. Contour plots for average extraction yield of DHPB: (a) Extraction time vs. stirring rate; (b) Sample:solvent ratio vs stirring rate; (c) Sample:solvent ratio vs extraction time.
vs. stirring rate plot (Fig. 3b), which showed that there is a very close relationship between the yield and the stirring rate than the amount of solvent. Fig. 3c shows that high yield was obtained when extraction was performed during 4.0–5.0 min at sample: solvent ratio of 1:30, at least. However lower ratio hampers the achievement of clear phase separations and it is recommended to work with sample:solvent of 1mg:50 μL. According to these observations, the extraction was carried out with methanol, at sample:solvent ratio of 1 mg:50 μL, under vortex stirring at 3200 rpm for 3 min, with 2 extraction cycles. The content of PEs (mg g−1) obtained in these conditions was 1.24 ± 0.024.
Table 6 Summary of validation results. Validation parameter
Value
LOD (ng μL−1) LOQ (ng μL−1) Repeatability (mg g−1)
4.41 13.36 1.24 ± 0.02 (RSD = 1.89 %)
Robustness Condition I (mg g−1) Condition II (mg g−1) Recovery at spike level of 50 % 100 % 150 % Linearity Separation factors αC2/C1 αC3/C2 αC6/C3 αC4+C5/C6
3.3. Analytical performance of the method This step aimed to ensure that the developed method is suitable for the intended use and that the results derived from it can be utilized to determine the reliability and consistency of the analytical data obtained (Fuster et al., 2015). The validation parameters are summarized in Table 6. The calibration curve showed a strong and positive (r = 0.999, R2 = 0.999) relationship between the concentration of DHPB and the peak area, over all tested analytical range of 2.5–50.0 ng μL−1. Studies reporting LOD and LOQ of the methods for determination of PEs are scarce and mostly estimated as equivalent of 12-O-tetradecanoylphorbol-13-acetate, which don’t occur in Jatropha (Makkar, 2016). In this study, the LOD and LOQ of the method were found to be 4.41 and 13.36 ng μL−1, respectively. The mean of recoveries at the three concentration levels tested is 89.0% ± 6.59 and the method also showed a good repeatability with RSD of 1.89%. As can be seen in Fig. 4, the typical chromatogram PEs, no interfering peaks in the range of retention of PEs could be detected. Additionally, all separation factors (Table 6) of the nearest peaks of PEs were found to be greater than 1. These facts are evidence of the
1.17 ± 0.027 1.24 ± 0.024 87.28 % ± 6.79 95.54 % ± 4.40 84.09 % ± 3.48 r = 0.999 1.10 1.13 1.06 1.07
Fig. 4. Chromatogram of methanol extracts of seeds, highlighting the five peaks of the PEs at the retention time range of 8.5–13 min, obtained under conditions described in the Section 2.5. 945
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selectivity of the method. Extraction time and stirring rate are the factors varied to investigate the method robustness. The paired t-test (at 95%) was employed for comparison of the yield means obtained from both conditions. Since tcrit > |tcalc| (12.71 > 2.13), the differences are not statistically significant and, hence, the method is not affected by small and deliberated changes of the experimental conditions.
Applications of Phorbol Esters From Jatropha curcas Oil. Doctoral thesis. Department of Aquaculture and Animal Nutrition (480b), University of Hohenheim. Devappa, R.K., Makkar, H.P.S., Becker, K., 2010a. Biodegradation of Jatropha curcas phorbol esters in soil. J. Sci. Food Agric. 90, 2090–2097. https://doi.org/10.1002/ jsfa.4056. Devappa, R.K., Makkar, H.P.S., Becker, K., 2010b. Jatropha toxicity: a review. J. Toxicol. Environ. Health Part B 13 (6), 476–507. https://doi.org/10.1080/10937404.2010. 499736. Devappa, R.K., Makkar, H.P.S., Becker, K., 2010c. Optimization of conditions for the extraction of phorbol esters from Jatropha oil. Biomass Bioenergy XXX, 1–9. https:// doi.org/10.1016/j.biombioe.2010.03.001. Devappa, R.K., Angulo-Escalante, M.A., Makkar, H.P.S., Becker, K., 2012. Potential of using phorbol esters as an insecticide against Spodoptera frugiperda. Ind. Crops Prod. 38 (1), 50–53. https://doi.org/10.1016/j.indcrop.2012.01.009. Devappa, R.K., Bingham, J.-P., Khanal, S.K., 2013a. High performance liquid chromatography method for rapid quantification of phorbol esters in Jatropha curcas seed. Ind. Crops Prod. 49, 211–219. https://doi.org/10.1016/j.indcrop.2013.04.044. Devappa, R.K., Roach, J.S., Makkar, H.P.S., Becker, K., 2013b. Ecotoxicology and environmental safety occular and dermal toxicity of Jatropha curcas phorbol esters. Ecotoxicol. Environ. Saf. 94, 172–178. https://doi.org/10.1016/j.ecoenv.2013.04. 021. Fuster, J., Negro, S., Salama, A., Marcianes, P., Boeva, L., Barcia, E., 2015. HPLC-UV method development and validation for the quantification of ropinirole in new PLGA multiparticulate systems: microspheres and nanoparticles. Int. J. Pharm. 491, 310–317. https://doi.org/10.1016/j.ijpharm.2015.06.035. Gogoi, R., Niyogi, U.K., Tyagi, A.K., 2014. Reduction of phorbol ester content in jatropha cake using high energy gamma radiation. J. Radiat. Res. Appl. Sci. 7, 2–6. https://doi. org/10.1016/j.jrras.2014.04.002. Gübitz, G.M., Mittelbach, M., Trabi, M., 1999. Exploitation of the tropical oil seed plant Jatropha curcas L. Bioresour. Technol. 67 (1), 73–82. https://doi.org/10.1016/ S0960-8524(99)00069-3. Haas, W., Sterk, H., Mittelbach, M., 2002. Novel 12-deoxy-16-hydroxyphorbol diesters isolated from the seed oil of Jatropha curcas. J. Nat. Prod. 65 (10), 1434–1440. https://doi.org/10.1021/np020060d. Hirota, M., Suttajit, M., Suguri, H., Endo, Y., Shudo, K., Wongchai, V., Hecker, E., Fujiki, H., 1988. A new tumor promoter from the seed oil of Jatropha curcas L., an intramolecular diester of 12-deoxy-16-hydroxyphorbol. Cancer Res. 48, 5800–5804. Kumar, P., Srivastava, V.C., Jha, M.K., 2016. Jatropha curcas phytotomy and applications: development as a potential biofuel plant through biotechnological advancements. Renew. Sustain. Energy Rev. 59, 818–838. https://doi.org/10.1016/j.rser. 2015.12.358. Makkar, H.P.S., 2016. State-of-the-art on detoxification of Jatropha curcas products aimed for use as animal and fish feed: a review. Anim. Feed Sci. Technol. https://doi. org/10.1016/j.anifeedsci.2016.09.013. Makkar, H.P.S., Becker, K., Sporer, F., Wink, M., 1997. Studies on nutritive potential and toxic constituents of different provenances of Jatropha curcas. J. Agric. Food Chem. 45 (8), 3152–3157. Martínez-Herrera, J., Siddhuraju, P., Francis, G., Dávila-Ortíz, G., Becker, K., 2006. Chemical composition, toxic/antimetabolic constituents, and effects of different treatments on their levels, in four provenances of Jatropha curcas L. from Mexico. Food Chem. 96 (1), 80–89. https://doi.org/10.1016/j.foodchem.2005.01.059. Montgomery, D.C., 2013. Design and Analysis of Experiments, 8th ed. John Wiley & Sons, Inc., USA. Najjar, A., Abdullah, N., Saad, W.Z., Ahmad, S., Oskoueian, E., Abas, F., Gherbawy, Y., 2014. Detoxification of toxic phorbol esters from Malaysian Jatropha curcas Linn. kernel by Trichoderma spp. and endophytic fungi. Int. J. Mol. Sci. 15 (2), 2274–2288. https://doi.org/10.3390/ijms15022274. Pereira, C., de, S.S., Pessoa, F.L., Mendonca, S., Ribeiro, J.A., de, A., Mendes, M.F., 2015. Technical and economic evaluation of phorbol esters extraction from Jatropha curcas seed cake using supercritical carbon dioxide. Adv. Chem. Eng. 5 (3), 1–7. https://doi. org/10.4172/2090-4568.1000132. Takechi, S., Imou, K., 2015. Sustainable energy production system from Jatropha in Mozambique project. 22nd International Conference on Production Research. pp. 1–6. Wink, M., Koschmieder, C., Sauerwein, M., Sporer, F., 1997. Phorbol esters of J. curcas – biological activities and potential applications. In: Gubitz, G.M., Mittelbach, M., Trabi, M. (Eds.), Biofuels and Industrial Products from Jatropha curcas. DBV Graz, Germany, pp. 160–166.
4. Conclusions A method of extraction of PEs from Jatropha seeds was optimized and validated for the first time for this sample matrix. It is an accurate and simple procedure that besides requiring shorter time than commonly used methods (around 10 min compared to 20–80 min), offers quantitative recoveries and consumes reduced amount of both sample and solvent. The analysis can be performed having only 20 mg of sample and 3 mL of solvent. Plackett-Burman and Box-Behnken designs showed that the extraction yield is mainly affected by the stirring rate, presumably due to increasing of the surface area. Extraction time, sample:solvent ratio, and extraction cycles gave the best yield around its centre points, while methanol proved to be ideal extraction solvent. A quadratic empirical model was found to be suitable to describe the PEs extraction yield as a function of the most important factors and its interactions. This model covers over 89% of variability in the experimental data and has good predictive capacity. This method is applicable for extraction of PEs from Jatropha seeds for different purposes, including the toxicity screening of the seeds (for breeding purposes), risk assessment on handling and processing Jatropha products, and isolation of PEs for application in agriculture and pharmaceutical studies. Conflict of interests The authors declare no conflict of interests Acknowledgements The authors would like to express their gratitude to Japan Science and Technology Agency (JST) and the Japan International Cooperation Agency (JICA), for financial support, and to all members of the Project Sustainable Production of Biodiesel from Jathropha in Mozambique, especially from Kurume University. References Baldini, M., Ferfuia, C., Bortolomeazzi, R., Verardo, G., Pascali, J., Piasentier, E., Franceschi, L., 2014. Determination of phorbol esters in seeds and leaves of Jatropha curcas and in animal tissue by high-performance liquid chromatography tandem mass spectrometry. Ind. Crops Prod. 59, 268–276. https://doi.org/10.1016/j. indcrop.2014.05.034. Brittaine, R., Lutaladio, N., 2010. Jatropha: A Smallholder Bioenergy Crop – The Potential for Pro-Poor Development Vol. 8 FAO, Rome. De Castro, M.D.L., García, J.L.L., 2002. High-pressure, high-temperature solvent extraction. Acceleration and Automation of Solid Sample Treatment, 1st ed. Elsevier Science B.V., pp. 233–279. https://doi.org/10.1016/S0167-9244(02)80008-7. Devappa, R.K., 2012. Isolation, Characterization and Potential Agro-pharmaceutical
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