Chemical Characterization of Jatropha curcas L. Seed Oil and Its

Apr 30, 2015 - Because they are still considered a native plant, J. curcas L. seeds were .... two different regions of the country were tested because...
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Chemical Characterization of Jatropha curcas L. Seed Oil and Its Biodiesel by Ambient Desorption/Ionization Mass Spectrometry Anna Maria A. P. Fernandes,† Soraya El-Khatib,† Ildenize B. S. Cunha,† Andréia M. Porcari,† Marcos N. Eberlin,† Marcio J. Silva,‡ Paulo R. Silva,§ Valnei S. Cunha,§ Romeu J. Daroda,§ and Rosana M. Alberici*,†,§ †

ThoMSon Mass Spectrometry Laboratory, Institute of Chemistry, and ‡Center for Molecular Biology and Genetic Engineering, University of Campinas (UNICAMP), 13083-970 Campinas, São Paulo, Brazil § National Institute of Metrology, Quality and Technology (INMETRO), 25250-020 Duque de Caxias, Rio de Janeiro, Brazil ABSTRACT: Biodiesel has become increasingly attractive because of its environmental benefits and production from renewable resources. The use of Jatropha curcas L. oil as the feedstock for biodiesel production has attracted growing interest because it is a non-edible oil. Herein, easy ambient sonic-spray ionization mass spectrometry (EASI−MS) was used to chemically characterize, at the molecular level, J. curcas L. oil and its biodiesel via monitoring its triacylglycerols (TAG), free fatty acids (FFA), and profiles of fatty acid methyl esters (FAME). The results provide further support for those obtained by the standard parameters of fuel quality. The EASI−MS analysis described herein is simple, requires only a tiny droplet of the sample, and is conducted without any pre-separation or chemical manipulation steps.

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INTRODUCTION Increasing crude oil prices and diminishing supplies of fossil fuels have led to the imperative necessity to develop alternative fuel sources.1 Renewable biofuels are currently among top priorities, and biodiesel composed of fatty acid methyl esters (FAME) seems to offer a viable alternative to petrodiesel.2 Although biodiesel production is based on the use of methanol, it can be obtained from methane in natural gas (fossil) or from biogas, making whole FAME renewable. Despite increasing the NOx emission, biodiesel exhibits several advantages over petrodiesel, such as low toxicity, high biodegradation rates, and lower exhaust emissions (e.g., particulate matter, hydrocarbons, and carbon monoxide), besides lower emission of carbon dioxide, and, hence, has a reduced impact on global warming.3 Despite this set of important advantages, a great drawback for large-scale biodiesel production is the high price of the feedstocks and the controversial use of edible oils. Therefore, the use of Jatropha curcas L., a Brazilian plant species with high resistance and growth with few exigencies of nutrients, seems to offer a viable alternative for biodiesel production.4 J. curcas L. is a drought-resistant tree belonging to the Euphorbiaceae family, which is cultivated in almost all tropical areas and extending its occurrence in Central and South America, southeast Asia, India, and Africa. It produces seeds for 50 years with a high oil content of approximately 37% or more, with seed yield per hectare as high as 0.20 × 106 tons year−1 and oil yields as high as 2.0−3.0 tons ha−1 year−1.3 J. curcas L. oil is considered a non-edible oil because of the presence of toxic phorbol esters.5,6 In some countries, such as India, J. curcas L. oil has already become a choice for biodiesel production as a result of the deficiency of matrices.7 Characterization of J. curcas L. oil has been determined through the identification and quantification of fatty acids by gas chromatography (GC)8 or high-performance liquid chromatography (HPLC).9 In recent years, mass spectrometry (MS) has © XXXX American Chemical Society

emerged as one of the most versatile and sensitive analytical techniques. Direct MS analysis using electrospray ionization (ESI) or matrix-assisted laser desorption/ionization (MALDI), has been applied to many areas of science, including the characterization of oils, fats, and biodiesel.10−14 Recently, we have demonstrated the use of ambient MS15 as a direct and nearly undisturbed method to perform efficient single-shot characterization, at the molecular level, for both oil16 feedstocks and their biodiesel products,17,18 via triacylglycerol (TAG) and FAME profiles, including impurities.19 For that purpose, we used mainly a direct desorption/ionization technique termed easy ambient sonic spray ionization mass spectrometry (EASI−MS),20 which allows for direct and fast MS analysis of samples in the open atmosphere with no sample preparation, pre-separation, or derivatization procedures. The EASI−MS technique has already been used to follow the maturation of J. curcas L. seeds via monitoring of the TAG profile of the oil.21 In this work, J. curcas L. oil and its biodiesel were chemically characterized at the molecular level using TAG, free fatty acids (FFA), and FAME profiles obtained by EASI−MS. For comparison, standard physical−chemical parameters, such as induction period, acid number, heat of combustion, and iodine value, were also evaluated.

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EXPERIMENTAL SECTION

Chemical Reagents and Samples. Because they are still considered a native plant, J. curcas L. seeds were obtained from the breeding programs of the Agronomic Institute of Campinas, Campinas, São Paulo, Brazil, and “Julio de Mesquita Filho” State University, Ilha Solteria, São Paulo, Brazil. Therefore, seeds from these institutes were named AIC and JMF, respectively.

Received: October 22, 2014 Revised: April 9, 2015

A

DOI: 10.1021/ef5023785 Energy Fuels XXXX, XXX, XXX−XXX

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Energy & Fuels HPLC-grade methanol and hexane were purchased from Merck SA (Rio de Janeiro, Brazil) and used without further purification. Methyl10-heptadecenoate was purchased from Sigma-Aldrich (St Louis, MO). C19 internal standard (IS) was purchased from Sigma (98%). Oil Extraction. For oil extraction, both mechanical and chemical methods were used. In both cases, seeds were previously dried in air for 24 h and then in an oven at 60 °C to reduce the moisture. For mechanical extraction, J. curcas L. oil was extracted in a Mini-Mill Scoth Tech brand, model ETR60II, by cold pressing. After the extraction step, the oils were filtered using a filter press for removal of particulate matter. For chemical extraction, J. curcas L. oil extraction was performed using hexane as solvent in a Soxhlet extractor. The crude extract was separated using a rotoevaporator. Samples extracted by mechanical and chemical extractions were named ME and CE, respectively. Synthesis of Biodiesel. Biodiesel was prepared from J. curcas L. oil using the transesterification process with a basic catalyst. The reaction of the oil with methanol was performed by stirring and heating at 45 °C. The dried J. curcas L. oil reacted with the catalyst (potassium hydroxide) dissolved in methanol for 45 min at 45 °C. After the reaction was completed, the reaction medium was transferred to a separation funnel and left for 24 h to allow phase separation. The biodiesel was separated from the glycerin by decanting. The organic layer was then washed 3 times with a solution of hydrochloric acid, followed by water until pH 7.22,23 Determination of Oxidative Stability. To evaluate the oxidation stability of the biodiesel samples, the oxidation induction period (IP) was measured with the use of a Rancimat apparatus (Metrohm 873) as described by EN 14112.24 Biodiesel samples (3 g) were heated to 110 °C. Air was then passed through the samples at a flow rate of 10 L h−1 and then through a trap containing water. The kinetics of the oxidation was followed by the sudden increase in conductivity of the water as a result of the formation of volatile organic acids. All determinations were performed in triplicate, and the mean value ± expanded uncertainty about the mean was reported unless otherwise noted. Determination of the Iodine Value. The iodine value was determined following EN 14111.25 The iodine value was performed in duplicate, and the mean value ± expanded uncertainty about the mean was reported. Determination of Specific Mass, Carbon Residue, and Cold Filter Plugging. Determination of the specific mass was conducted according to the ABNT NBR 14065 method26 using a DMA38 Anton Paar digital densimeter. Determination of the carbon residue (Micro Carbon Residue Tester, Tanaka Scientific) was conducted according to the ABNT NBR 15586 method.27 Determination of the cold filter plugging (FPP 5Gs, ISL) was conducted according to the ABNT NBR 14747 method.28 The cloud point was conducted according to the ASTM D2500 method.29 All of these parameters were measured in triplicate, and the mean value ± expanded uncertainty about the mean was reported. Gas Chromatography−Flame Ionization Detector (GC−FID) Analysis. The fatty acid profile identification and composition determination were performed on a Shimadzu GC-2010 plus gas chromatograph with a FID. A capillary polar wax column, polyethylene glycol (PEG)-coated (length of 30 m, internal diameter of 0.32 mm, and film thickness of 0.25 μm), and helium as the carrier gas were used for the separation of fatty acid esters by the EN 14103 method.30 A C19 IS was used for the quantification of all esters. Chromatographic conditions were as follows: capillary column, Rtx-Wax, Restek (30 m length × 0.32 mm internal diameter × 0.25 mm film thickness); injection volume of 1 μL; oven at 100 °C for 3 min, 15 °C min−1 to 150 °C, 6 °C min−1 to 240 °C, and keep for 3 min; split mode with a ratio of 100:1; He carrier gas with a flow rate of 2.9 mL min−1; and injection temperature of 250 °C. The GC−FID analysis was performed in triplicate. EASI−MS Analysis. For EASI we used a homemade ionization source easily constructed as previously described in detail elsewhere.20,31,32 A spray with tiny droplets is formed by employing a carrier gas and solvent. These droplets desorb the analytes from surfaces promoting their ionization and transfer to mass spectrometers. This ionization process, unlike other ionization techniques, occurs in an

Figure 1. EASI(−)−MS of J. curcas oil mechanically extracted from the AIC sample. external environment to the mass spectrometer. EASI was performed in the positive- and negative-ion modes using a single quadrupole mass spectrometer (LCMS2010, Shimadzu). A tiny droplet of the sample (2 μL) was dropped directly onto a paper surface (brown Kraft envelope paper). Common parameters for EASI were a methanol flow rate of 20 μL min−1, N2 nebulizing gas at 3 L min−1, and a paper entrance angle of ∼30°. For negative-ion mode analysis, the methanol was doped with ammonium hydroxide. Mass spectra were accumulated over 30 s and scanned over the m/z range of 100−1000 in both polarities. For each sample, oil AIC (CE), oil AIC (ME), oil JMF (CE), oil AIC (ME), biodiesel AIC (CE), biodiesel AIC (ME), biodiesel JMF (CE), and biodiesel JMF (ME) analysis was performed in triplicate. The EASI source was also coupled to a Q-Exactive 2.2 SP1 mass spectrometer (Thermo Scientific, Hemel Hempstead, U.K.) in profile mode with a resolution of 70 000 at m/z 400. The exact mass of the compounds was calculated using Qualbrowser in Xcalibur 2.2. Calibration in positive and negative ion modes were performed every 2 days using calibration solutions prepared according to the instructions of the manufacturer. All Q-Exactive parameters were optimized to improve sensitivity and selectivity. Biodiesel/Diesel Blends. This procedure was executed according to previous work, which was performed with petrodiesel/soybean biodiesel blends.33 The petrodiesel was supplied by Petrobras, coded as S1800, and sampled under the acronym TQ-4729. Samples were prepared by mixing biodiesel with petrodiesel in the following proportions: 0.5, 1.0, 3.0, 5.0, and 7.0% (w/w). These blends, called B0.5, B1, B3, B5, and B7, respectively, were then used to construct the analytical curve. The biodiesel/petrodiesel blend samples were diluted 10 times in methanol before EASI(+)−MS analysis. For this quantitation, methyl-10-heptadecenoate (C18H34O2; molecular mass = 282 Da; final concentration of 115 μg mL−1 in hexane) was used as the IS. Blends were analyzed in triplicate. The calibration curve was constructed by plotting the blend levels versus the ratio of the absolute intensity of the ester (m/z 317) to that of the IS (m/z 305). Statistical Analysis. Statistical calculations reported in Tables 4 and 3 were performed using the GraphPad In-Stat 3.10 software. It applied the unpaired t test with Welch correction (Table 4) and the one-way analysis of variance (ANOVA) followed by Bonferroni's post hoc test (Table 3). For the multivariate statistical analysis in Figure 5, the lists of m/z values (relative intensities normalized to the most intense ion peak in the range) were saved as .csv files and uploaded into the Metaboanalyst 3.0 web-based tool.34 Data obtained by positive-ion mode were used to evaluate differences in TAG and diacylglycerol (DAG) composition of chemically and mechanically extracted oils. On the other hand, data adquired in negative-ion mode were used to evaluate differences in fatty acid compositions of oils and biodiesels. An autoscaling pre-processing method was applied in both cases; therefore, the presence of ions could be taken into account independently of their abundances. By this method, the relative intensities of the ion peaks are mean-centered and divided by the standard deviation of each ion. Partial least-squares discriminant analysis (PLS-DA) was performed to evaluate sample discrimination. Variable importance in projection (VIP) from PLS-DA B

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Table 1. Main FFA and Their Desprotonated Ion Relative Abundances Detected by EASI(−)−MS for J. curcas L. Oil and Its Biodiesela ME AIC oil

ME JMF oil

CE AIC oil

CE JMF oil

exact mass

experimental massb

error (ppm)b

ME AIC biodiesel

ME JMF biodiesel

CE AIC biodiesel

CE JMF biodiesel

C16H31O2

255.23240

255.23283

+1.097

L

C18H31O2

279.23240

279.23384

+1.198

281

O

C18H33O2

281.24805

281.24954

+1.203

283

S

C18H35O2

283.26370

283.26533

+1.217

14.6 ± 1.3 13.9 ± 1.6 79.8 ± 2.9 60.4 ± 2.9 100.0 ± 0.0 100.0 ± 0.0 4.1 ± 1.0 9.7 ± 1.4

13.0 ± 0.3 17.8 ± 1.4 85.6 ± 5.9 81.4 ± 7.3 100.0 ± 0.0 100.0 ± 0.0 3.9 ± 1.2 8.9 ± 1.2

11.3 ± 2.0 35.4 ± 17.2 82.8 ± 6.0 57.3 ± 8.8 100.0 ± 0.0 100.0 ± 0.0 7.7 ± 0.5 11.9 ± 1.8

14.6 ± 2.6 65.7 ± 6.6 95.3 ± 1.4 44.7 ± 6.4 100.0 ± 0.0 100.0 ± 0.0 4.1 ± 1.3 10.0 ± 0.8

[FFA − H]− m/z

FFA assignment

molecular formulab

255

P

279

a Data are expressed as the mean percentage ± standard deviation (SD). bObtained using a high resolution mass spectrometer (Orbitrap) for J. curcas L. biodiesel.

Figure 2. EASI(+)−MS of J. curcas L. oil (A) mechanically and (B) chemically extracted from the AIC sample. was used to recognize the features that are most relevant to the model. Cross-validation was performed and analyzed by means of the Q2 value (cross-validated R2).

GC−FID of the oil mechanically extracted from seeds (AIC sample) exhibited the following fatty acid composition: 13.7% palmitic acid (C16:0), 0.8% palmitoleic acid (C16:1), 7.0% stearic acid (C18:0), 44.2% oleic acid (C18:1), 34.1% linoleic acid (C18:2), and 0.2% linolenic acid (C18:3). The fatty acid composition of J. curcas L. oil has previously been reported,36−38 in which its unsaturated fatty acid content was found to range from 77 to 83%, whereas palmitic and stearic acids were found as the major saturated fatty acids in the oil. The observed variation in the percentage of fatty acid composition likely results from the diverse agroclimatic condition of cultivation of the seed. The fatty acid oil composition is similar to those reported for some conventional oil seeds, such as soybean, peanut, and sunflower.8

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RESULTS AND DISCUSSION As representative J. curcas L. samples, two different seeds (AIC and JMF) from two different regions of the country were tested because this plant is still a wild plant. Additionally, two methods of extraction, i.e., mechanical and chemical, were used. J. curcas L. is being explored for its oil yield potential (27−40% oil) throughout the world.35 In the present study, the oil yields were approximately 27% for mechanical extraction and 48% for chemical extraction. The chromatographic profile obtained by C

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Table 2. Main TAG and DAG and Their Sodium Adduct Relative Abundances Detected by EASI(+)−MS for J. curcas L. Oil Samplesa

a

[TAG + Na]+ or [DAG + Na]+ m/z

TAG or DAG assignment

molecular formulab

exact mass

experimental massb

error (ppm)b

ME AIC

ME JMF

CE AIC

CE JMF

615 641 877 879 881 901 903 905 907

PL OL PLL PLO POO LLL OLL OOL OOO

C37H68O5Na C39H70O5Na C55H98O6Na C55H100O6Na C55H102O6Na C57H98O6Na C57H100O6Na C57H102O6Na C57H104O6Na

615.49644 641.51209 877.72556 879.74121 881.75740 901.72556 903.74121 905.75686 907.77251

615.49645 641.51175 877.72921 879.74347 881.75823 901.73091 903.74372 905.75782 907.77280

+0.900 +0.317 +4.156 +2.567 +1.368 +5.931 +2.775 +1.058 +0.288

6.1 ± 0.8 50.4 ± 5.4 29.7 ± 4.4 53.9 ± 4.9 24.3 ± 0.4 27.5 ± 7.6 100.0 ± 0.0 86.0 ± 4.4 52.6 ± 1.2

6.5 ± 1.1 45.4 ± 13.9 38.4 ± 4.7 44.3 ± 2.4 15.1 ± 1.7 45.7 ± 1.8 100.0 ± 0.0 70.4 ± 3.8 32.2 ± 2.5

30.7 ± 3.0 100.0 ± 0.0 16.7 ± 2.0 26.7 ± 6.0 11.7 ± 2.9 14.1 ± 1.7 54.3 ± 10.1 46.8 ± 14.4 28.1 ± 11.0

29.5 ± 0.7 100.0 ± 0.0 19.6 ± 2.1 25.9 ± 2.0 9.4 ± 1.4 20.9 ± 2.7 59.6 ± 8.1 47.7 ± 2.3 18.1 ± 0.3

Data are expressed as the mean percentage ± SD. bObtained using a high resolution mass spectrometer (Orbitrap).

Figure 3. EASI(−)−MS of J. curcas L. biodiesel (A) prepared from mechanically extracted oil from the AIC sample and (B) prepared from chemically extracted oil from the AIC sample.

samples (Figure 3B). This behavior has not been observed in oil samples, thus excluding the possibility of greater extraction efficiency of palmitic acid by the solvent. Figure 4 shows the FAME profiles obtained by EASI(+)−MS of the AIC biodiesel sample. As previously observed for TAG, the

In agreement with the GC−FID analysis, the dominant FFA detected by EASI(−)−MS in the form of [FFA − H]− were oleic acid of m/z 281, linoleic acid of m/z 279, stearic acid of m/z 283, and palmitic acid of m/z 255 (Figure 1). In this qualitative analysis using the negative-ion mode, no difference was observed between AIC and JMF samples or between the methods of extraction (Table 1). These observations were confirmed by the multivariate statistical analysis, as will be furthered discussed. Figure 2 shows the EASI(+)−MS profiles of the J. curcas L. oil sample from AIC using mechanical and chemical extractions. Note that TAG (m/z range of 800−1000) are detected mainly as [TAG + Na]+ ions: PLL of m/z 877, PLO of m/z 879, POO of m/z 881, LLL of m/z 901, OLL of m/z 903, OOL of m/z 905, and OOO of m/z 907, with another class of respective minor [TAG + K]+ ions (Figure 2A). This TAG profile was also observed for the JMF samples. Indeed, a very similar TAG profile was obtained for AIC and JMF, regardless of the method of extraction. [DAG + Na]+ ions of m/z 615 (PL) and m/z 641 (OL) were also detected by EASI(+)−MS because these samples are composed of partially hydrolyzed crude oil. Note in Figure 2B, for the oil obtained via chemical extraction, the much higher abundances of ions associated with [DAG + Na]+ compared to [TAG + Na]+ ions. Table 2 shows the relative abundances of the most abundant ions of the spectra. A multivariate statistical analysis to discuss the differences between samples was performed and it will also be furthered discussed. Figure 3 shows EASI(−)−MS profiles of the J. curcas L. biodiesel samples obtained from oil mechanically and chemically extracted. As expected, the FFA found in the biodiesel samples were identical to those obtained for oil samples (Figure 1). The main difference is related to the increase of the relative abundance of the ion of m/z 255 (P) in the chemically extracted

Figure 4. EASI(+)−MS of J. curcas L. biodiesel prepared from mechanically extracted oil from the AIC sample.

FAME profiles were detected mainly in their sodiated forms [FAME + Na]+. Linoleic acid methyl ester ions of m/z 317 predominate in the spectrum, with minor ions from oleic acid methyl ester of m/z 319.31 A series of minor [FAME + K]+ ions are also detected as ions of m/z 333 and 335. Again, a very similar FAME profile was also obtained for AIC and JMF samples, regardless of the method of extraction, as confirmed by the relative abundance of the FAME showed in Table 3. There is no statistically significant difference between the samples [p > 0.05; D

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Table 3. Main FAME and Their Sodium Adduct Relative Abundances Detected by EASI(+)−MS for J. curcas L. Biodiesel Samplesa FAb

[FAME + Na]+ m/z

molecular formulac

exact mass

experimental massc

error (ppm)c

ME AIC

ME JMF

CE AIC

CE JMF

L O

317 319

C19H34O2Na C19H36O2Na

317.24565 319.26130

317.24463 319.26032

−0.472 −0.432

100.0 ± 0.0 19.2 ± 1.9d

100.0 ± 0.0 15.9 ± 3.5d

100.0 ± 0.0 18.6 ± 1.0d

100.0 ± 0.0 23.1 ± 8.0d

a Data are expressed as the mean percentage ± SD. bFatty acid abbreviations: L, linoleic; O, oleic. cObtained using a high resolution mass spectrometer (Orbitrap). dThere is no statistically significant difference between the samples (p > 0.05; one-way ANOVA followed by Bonferroni’s post-hoc test).

Figure 5. PLS-DA scores and VIP plots of normalized spectra obtained after (A) negative ionization of oil and biodiesel samples and (B) positive ionization of chemically and mechanically extracted oil samples. For panel A, the classes refer to mechanically extracted oils (red triangles, A), chemically extracted oils (green plus signs, B), mechanically extracted biodiesels (blue crosses, C), and chemically extracted biodiesels (cyan diamonds, D). The Q2 value was found to be 0.75 for two components. For panel B, the classes refer to mechanically extracted oils (red triangles, A) and chemically extracted oils (green plus signs, B). The Q2 value was found to be 0.95 for two components. VIP plots are shown in the insets for each analysis.

Table 4 summarizes the results of some quality parameters of the J. curcas L. oil and biodiesel samples. The results showed that all characteristics are according to the specification limits established by a biodiesel resolution of the Brazilian National Agency of Petroleum, Natural Gas and Biofuels (ANP).39 The iodine value provides a measure of the tendency of the oil to polymerize, forming engine deposits; hence, it was indeed motivating to find that the iodine values for J. curcas L. biodiesel are even lower than those obtained for pure soybean biodiesel.40 Significantly different results (p < 0.05; unpaired t test with Welch correction) between the mechanical and chemical extractions (AIC and JMF) were observed only for oxidative stability. The biodiesel oxidation stability for the chemical extraction showed higher values than those obtained by mechanical extraction, indicating that some metal or residue could possibly catalyze the oxidation process in such samples. The carbon residue method indicates the tendency of a fuel to produce carbon deposits and is also indicative of excessive amounts of glycerol in the biodiesel sample. Fortunately, the values obtained herein were below the accepted limits. For both extraction processes, there was no indication of glycerol excess in the samples. Although viscosity is an important parameter, it was not assessed in this study. However, all of the chosen parameters were found according to specifications, thus allowing the

one-way analysis of variance (ANOVA) followed by Bonferroni’s post-hoc test]. In addition, to check for sample and extraction method similarities, PLS-DA was performed on oil and biodiesel data acquired in the negative-ion mode (Figure 5A). The score plot shows that the first component can slightly differentiate biodiesel from oil samples and can clearly differentiate the origin of the biodiesel (e.g., if it is a biodiesel originated from chemically or mechanically extracted oil). The second component is related to variability in analysis. The few number of ions observed in the negative-ion mode and the similar fatty acid composition for oil and biodiesel samples reduce the possibilities of improving the achieved differentiation. The ions of m/z 283 and 255 are responsible for the achieved results, as observed in the VIP plot (inset of Figure 5A). When data from Table 2 were analyzed by means of PLS-DA (Figure 5B), oil samples could be clearly differentiated according to their extraction method (component 1). The second component shows the variability in the analysis. Note that the analyzed seeds could not be differentiated. The VIP plot (inset of Figure 5B) shows that the ions of m/z 615 and 641 are representative of chemically extracted samples. This is probably related to a greater efficiency in DAG extraction by the solvent or partial hydrolysis of TAG to DAG during solvent extraction. E

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Energy & Fuels Table 4. Characterization of Physicochemical Parameters of CE and ME of J. curcas L. Oil and Its Biodiesel sample

specific mass (g/cm3)a iodine value (g/100 g)a cloud point (°C)a

oil AIC (CE) oil AIC (ME) oil JMF (CE) oil JMF (ME) biodiesel AIC (CE) biodiesel AIC (ME) biodiesel JMF (CE) biodiesel JMF (ME)

0.91 ± 0.00 0.91 ± 0.01 0.91 ± 0.01 0.91 ± 0.01 0.87 ± 0.01 0.87 ± 0.01 0.87 ± 0.01 0.87 ± 0.01

94.34 ± 0.20 95.60 ± 0.70 100.61 ± 0.04 100.50 ± 0.78 96.25 ± 1.81 96.08 ± 0.95 100.02 ± 0.87 100.27 ± 1.06

3.70 ± 0.10 4.20 ± 0.10 2.86 ± 0.05 3.23 ± 0.12

specification values

ANP 0.85−0.90 ASTM note

ANP note ASTM note

ANP note ASTM note

oxidative stability (h)a carbon residue (%)a filter plugging (°C)a 12.92 ± 0.43 10.60 ± 0.83 11.84 ± 0.99 10.64 ± 0.54 9.26 ± 0.70b 5.11 ± 0.18b 9.25 ± 0.36b 6.6 ± 0.89b ANP 6 ASTM 3

0.25 ± 0.08 0.22 ± 0.08 0.44 ± 0.02 0.37 ± 0.05 0.019 ± 0.001 0.033 ± 0.005 0.01 ± 0.00 0.017 ± 0.009 ANP 0.05 ASTM 0.05

−2.00 ± 0.00 0.23 ± 0.09 −2.00 ± 0.00 −0.90 ± 0.00 ANPc 7−14 ASTMd

a

Values correspond to expanded uncertainty about the mean. bStatistically significant differences (p < 0.05; unpaired t test with Welch correction) between the mechanical (ME) and chemical extractions (CE) for both AIC and JMF. cDependent upon the region and season. dNot part of the ASTM specification (ASTM D6751-12).

coefficient (r2 > 0.99). To evaluate the accuracy of the method for real samples of J. curcas L. biodiesel/diesel Bn blends, two B2 and B4 samples were analyzed by EASI(+)−MS, according to the methodology previously validated for soybean biodiesel.33 EASI results were compared to the conventional methodology, such as infrared (IR), showing values of 2.4 ± 0.05 and 4.2 ± 0.05, respectively. J. curcas L. biodiesel consists mainly of unsaturated FAME and, therefore, is susceptible to oxidation. We have shown the effectiveness of the N,N′-di-sec-butyl-phenylenediamine (Santoflex) as an artificial antioxidant for soybean, sunflower, and canola biodiesels.44 We therefore tested Santoflex and butylated hydroxytoluene (BHT) as antioxidants for J. curcas L. biodiesel. Table 5 shows the measured values for the IP obtained by the

conclusion that this biodiesel has a good quality. In addition, the increase in viscosity is mainly related to the biodiesel oxidation processes during long periods of storage; in this work, all samples used were freshly prepared. The similarities between AIC and JMS biodiesel samples, indicated by the physicochemical parameters in Table 4, were further strengthened by the chemical characterization obtained by EASI−MS. It is important to explore the behavior of biodiesel/diesel blends because the content of biodiesel blended with diesel results in a difference in the engine power performance, which has become common sense.41 Fuel properties of J. curcas L. biodiesel have been analyzed, and the results indicate that B25 has a closer performance to diesel and B100.42 The effect of blending J. curcas L. biodiesel with diesel has also been verified, showing improved oxidation stability.43 In Brazil, biodiesel is also commercialized as biodiesel/petrodiesel blends (Bn). We have demonstrated the use of EASI−MS for quantitation of soybean biodiesel/petrodiesel Bn blends.33 In this study, we therefore tested this methodology to quantify J. curcas L. biodiesel/ petrodiesel Bn blends by considering the possibility of commercialization of this biodiesel. Methyl-10-heptadecenoate (m/z 305) was used as the IS, and the ratio of intensities of the ion peaks m/z 305 (linoleic acid methyl ester) and m/z 305 were used to build the calibration curves (Figure 6).

Table 5. IP (h) Determined by the Rancimat Test for J. curcas L. Biodiesel AIC CE Doped with Santoflex (10 ppm) and BHT (100 ppm)

a

J. curcas L. biodiesel

IP (h)a

without antioxidant with BHT with Santoflex

8.7 ± 0.4 10.8 ± 0.5 48.8 ± 0.6

Values correspond to mean ± SD.

Rancimat for J. curcas L. biodiesel without and with artificial antioxidants. Fortunately, we found that the addition of as little as 10 ppm of the Santoflex and 100 ppm of BHT increase the oxidation stability of the J. curcas biodiesel to the level of compliance with the European standard (EN 14214)45 and the ANP46 in Brazil (6 h at 110 °C). Figure 7A shows the EASI(+)−MS of J. curcas L. biodiesel after 9 h of accelerated oxidation at 110 °C in the presence of air. Note that the ions of m/z 349 and 381, which correspond to the oxidation products (hydroperoxides), are now much more abundant than those in Figure 4. Panels B and C of Figure 7 show the spectra for J. curcas L. biodiesel after accelerated oxidation but now with the addition of as little as 100 ppm of BHT and 10 ppm of Santoflex antioxidants, respectively. Figure 7C shows a very contrasting behavior compared to Figure 7A for J. curcas L. biodiesel oxidation. After 48 h of accelerated oxidation by air at 110 °C, the EASI(+)−MS profile showed little changes for the J. curcas L. biodiesel in the presence of Santoflex.

Figure 6. Calibration curve obtained by EASI(+)−MS data of J. curcas L. biodiesel/petrodiesel Bn blends.

Note in Figure 6 that indeed EASI(+)−MS with a proper IS produced a calibration curve with quite a high correlation F

DOI: 10.1021/ef5023785 Energy Fuels XXXX, XXX, XXX−XXX

Energy & Fuels

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ACKNOWLEDGMENTS The authors are grateful to the Brazilian National Research Council (CNPq) and Coordination for the Improvement of Higher Level or Education Personnel (CAPES) for their financial support. We thank the reviewers for valuable suggestions.

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(1) Trevisani, L.; Fabbri, M.; Negrini, F.; Ribani, P. L. Energy Convers. Manage. 2007, 48, 146−154. (2) Ma, F.; Hanna, M. A. Bioresour. Technol. 1999, 70, 1−15. (3) Singh, S. P.; Singh, D. Renew. Sust. Energ.Rev. 2010, 12, 200−216. (4) Koh, M. Y.; Ghazi, T. I. M. Renew. Sust. Energ.Rev. 2011, 15, 2240− 2251. (5) Devappa, R. K.; Bingham, J.-P.; Khanal, S. K. Ind. Crops Prod. 2013, 49, 211−219. (6) Liu, X.; Li, L.; Li, W.; Lu, D.; Chena, F.; Li, J. Ind. Crops Prod. 2013, 47, 29−32. (7) Meher, L. C.; Churamani, C. P.; Arif, Md.; Ahmed, Z.; Naik, S. N. Renew. Sust. Energ.Rev. 2013, 26, 397−407. (8) Akintayo, E. T. Bioresour. Technol. 2004, 92, 307−310. (9) Oliveira, J. S.; Leite, P. M.; Souza, L. B.; Mello, V. M.; Silva, E. C.; Rubim, J. C.; Meneghetti, S. M. P.; Suarez, P. A. Z. Bioenerg. 2009, 33, 449−453. (10) Wu, Z.; Rodgers, R. P.; Marshall, A. G. J. Agric. Food Chem. 2004, 52, 5322−5328. (11) Eide, I.; Zahlsen, K. Energy Fuels 2007, 21, 3702−3708. (12) Catharino, R. R.; Milagre, H. M. S.; Saraiva, A. S.; Garcia, C. M.; Schuchardt, U.; Eberlin, M. N.; Augusti, R.; Pereira, R. C. L.; Guimarães, M. J. R.; de Sá, G. F.; Caixeiro, J. M. R.; Souza, V. Energy Fuels 2007, 21, 3698−3701. (13) Catharino, R. R.; Haddad, R.; Cabrini, L. G.; Cunha, I. B. S.; Sawaya, A. C. H. F.; Eberlin, M. N. Anal. Chem. 2005, 77, 7429−7433. (14) Saraiva, A. S.; Cabral, E. C.; Eberlin, M. N.; Catharino, R. R. J. Agric. Food Chem. 2009, 57, 4030−4034. (15) Alberici, R. M.; Simas, R. C.; Sanvido, G. B.; Romão, W.; Lalli, P. M.; Benassi, M.; Cunha, I. B. S.; Eberlin, M. N. Anal. Bioanal. Chem. 2010, 398, 265−294. (16) Simas, R. C.; Catharino, R. R.; Cunha, I. B. S.; Cabral, E. C.; Barrera-Arellano, D.; Eberlin, M. N.; Alberici, R. M. Analyst 2010, 135, 735−744. (17) Alberici, R. M.; Simas, R. C.; Souza, V.; de Sá, G. F.; Daroda, R. J.; Eberlin, M. N. Anal. Chim. Acta 2010, 659, 15−22. (18) Fernandes, A. M. A. P.; Eberlin, M. N.; Silva, P. R.; Silva, S. R.; Cunha, V. S.; Daroda, R. J.; Alberici, R. M. Fuel 2014, 128, 99−103. (19) Fernandes, A. M. A. P.; Tega, D. U.; Jara, J. L. P.; Cunha, I. B. S.; de Sá, G. F.; Daroda, R. J.; Eberlin, M. N.; Alberici, R. M. Energy Fuels 2012, 26, 3042−3047. (20) Haddad, R.; Sparrapan, R.; Eberlin, M. N. Rapid Commun. Mass Spectrom. 2006, 20, 2901−2905. (21) Cardoso, K. C.; Da Silva, M. J.; Grimaldi, R.; Stahl, M.; Simas, R. C.; Cunha, I. B. S.; Eberlin, M. N.; Alberici, R. M. J. Am. Oil Chem. Soc. 2012, 89, 67−71. (22) Geris, R.; Santos, N. A. C.; Amaral, B. A.; Maia, I. S.; Castro, V. D.; Carvalho, J. R. M. Quim. Nova 2007, 30, 1369−1373. (23) Batista, L. N.; Silva, V. F.; Fonseca, M. G.; Pissurno, E. C. G.; Daroda, R. J.; Cunha, V. S.; Kunigami, C. N.; de Santa Maria, L. C. Microchem. J. 2013, 106, 17−22. (24) European Committee for Standardization (CEN). European Standard EN 14112:2003. Fatty Acid Methyl Esters (FAME) Determination of Oxidation Stability (Accelerated Oxidation Test); CEN: Brussels, Belgium, 2003. (25) European Committee for Standardization (CEN). European Standard EN 14111:2003. Fat and Oil Derivatives Fatty Acid Methyl Esters (FAME)Determination of Iodine Value; CEN: Brussels, Belgium, 2003. (26) Associaçaõ Brasileira de Normas Técnicas (ABNT). NBR 14065:2013. Petroleum Distillates and Viscous OilsDetermination of Density and Specific Gravity by Digital Densimeter; ABNT: Rio de Janeiro, Brazil, 2013.

Figure 7. EASI(+)−MS of J. curcas L. biodiesel (prepared from chemically extracted oil from the AIC sample) after accelerated oxidation by Rancimat test (A) without antioxidant, (B) with BHT addition (100 ppm), and (C) with Santoflex addition (10 ppm).

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CONCLUSION The overall quality of the J. curcas L. biodiesel was found to be quite similar to that of standard biodiesels made from more expensive and more controversial fresh edible oils. The biodiesels were exhaustively evaluated both at the molecular level via EASI(+)−MS FAME profiles and in terms of overall fuel quality parameters. Therefore, J. curcas L. oil indeed seems to offer quite an attractive feedstock for biodiesel production.

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REFERENCES

AUTHOR INFORMATION

Corresponding Author

*Telephone: +55-19-35213073. E-mail: rmalberici@hotmail. com. Notes

The authors declare no competing financial interest. G

DOI: 10.1021/ef5023785 Energy Fuels XXXX, XXX, XXX−XXX

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Energy & Fuels (27) Associaçaõ Brasileira de Normas Técnicas (ABNT). NBR 15586:2008. Petroleum ProductsDetermination of Carbon Residue MethodMicro Method; ABNT: Rio de Janeiro, Brazil, 2008. (28) Associaçaõ Brasileira de Normas Técnicas (ABNT). NBR 14747:2008. Diesel OilDetermination of Cold Filter Plugging; ABNT: Rio de Janeiro, Brazil, 2008. (29) ASTM International. ASTM D2500-11. Standard Method for Cloud Point of Petroleum Products; ASTM International: West Conshohocken, PA, 2011. (30) European Committee for Standardization (CEN). European Standard EN 14103:2011. Fat and Oil DerivativesFatty Acid Methyl Esters (FAME)Determination of Ester and Linolenic Acid Methyl Ester Contents; CEN: Brussels, Belgium, 2011. (31) Godoy, A. T.; Pereira, G. G.; Ferreira, L. L.; Cunha, I. B. S.; Barrera-Arellano, D.; Daroda, R. J.; Eberlin, M. N.; Alberici, R. M. Energy Fuels 2013, 27, 7455−7459. (32) Fernandes, G. D.; Alberici, R. M.; Pereira, G. G.; Cabral, E. C.; Eberlin, M. N.; Barrera-Arellano, D. Food Chem. 2012, 135, 1855−1860. (33) Cunha, I. B. S.; Fernandes, A. M. A. P.; Tega, D. U.; Simas, R. C.; Nascimento, H. L.; de Sá, G. F.; Daroda, R. J.; Eberlin, M. N.; Alberici, R. M. Energy Fuels 2012, 26, 7018−7022. (34) Xia, J.; Mandal, R.; Sinelnikov, I.; Broadhurst, D.; Wishart, D. S. Nucleic Acids Res. 2012, 40, W127−W133. (35) Achten, W. M. J.; Mathijs, E.; Verchot, L.; Singh, V. P.; Aerts, R.; Muys, B. Biofuels, Bioprod. Biorefin. 2007, 1, 283−291. (36) Becker, K.; Makkar, H. P. S. Lipid Technol. 2008, 20, 104−107. (37) Foidl, N.; Foidl, G.; Sanchez, M.; Mittelbach, M.; Hackel, S. Bioresour. Technol. 1996, 58, 77−82. (38) Gubitz, G. M.; Mittelbach, M.; Trabi, M. Bioresour. Technol. 1999, 67, 73−82. (39) Brazilian National Agency of Petroleum, Natural Gas and Biofuels ́ Brazil, (ANP). Resolução ANP n° 14 de 11/05/2012; ANP: Brasilia, 2012. (40) Alberici, R. M.; Souza, V.; de Sá, G. F.; Morelli, S. R.; Eberlin, M. N.; Daroda, R. J. Bioenergy Res. 2012, 5, 1002−1008. (41) Rakesh Sarin, R.; Sharma, M.; Sinharay, S.; Malhotra, R. K. Fuel 2007, 86, 1365−1371. (42) Hanumantha Rao, Y. V.; Sudheer Voleti, R.; Sitarama Raju, A. V.; Nageswara Reddy, P. Indian J. Sci. Technol. 2009, 2, 43−47. (43) Jain, S.; Sharma, M. P. Fuel 2011, 90, 3014−3020. (44) Alberici, R. M.; Simas, R. C.; Abdelnur, P. V.; Eberlin, M. N.; Souza, V.; de Sá, G. F.; Daroda, R. J. Energy Fuels 2010, 24, 6522−6526. (45) European Committee for Standardization (CEN). European Standard EN 14214. Automotive FuelsFatty Acid Methyl Esters (FAME) for Diesel EnginesRequirements and Test Methods; CEN: Brussels, Belgium, 2003. (46) Brazilian National Agency of Petroleum, Natural Gas and Biofuels (ANP). http://www.anp.gov.br/petro/biodiesel.asp (accessed Sept 2014).

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DOI: 10.1021/ef5023785 Energy Fuels XXXX, XXX, XXX−XXX