Abstract
Temperature, time and particle size effects on Irvingia gabonensis kernel oil (IGKO) yield, as well as the kinetics and thermodynamics parameters were investigated. Highest oil yield of 68.80 % (by weight) was obtained at 55 °C, 150 min., and 0.5 mm. Evaluated physicochemical properties of IGKO indicated that viscosity, acidity, dielectric strength, flash and pour points were 19.37 mm2s-1, 5.18 mg KOHg-1, 25.83 KV, 285 °C, and 17 °C, respectively, suggesting its feasibility as transformer fluid upon further treatment. Of the pseudo second order (PSO) and hyperbolic kinetic models studied, the former gave better fit to the experimental data. ∆H, ∆S and ∆G values of IGKO extraction at 0.5 mm and 328 K were, 251.81 KJ/mol, 1.08 KJ/mol and -105.49 KJ/mol, respectively, indicating the endothermic, irreversible and spontaneous nature of the process. Kinetic model equations that describe the process were successfully developed for both models based on the process parameters.
Keywords: Solvent extraction; Irvingia gabonensis ; Kinetics; Thermodynamics; modeling
Introduction
The searches for suitable alternative to petroleum have increased in recent years. This is attributed to human-induced global climate change, depleted petroleum reserve and more recently the drop in the global crude oil price. In Nigeria, prior to the commencement of crude oil exploration and production in February 1958 by Shell British Petroleum at Oloibiri and Afam oil fields in Port Harcourt; agriculture was the main stay of the economy [1-2]. As a result of these, especially the drop in the global crude oil, Nigerian government have introduced measures and polices that are geared towards the diversification of the economy, with special attention given to agricultural development. This government initiative has led to the development of the agricultural sectors that is aimed at achieving food security, industrial utilization of its products, job creation, as well as products processing for export purposes. The aftermath of this is the massive planting of economic trees, oil seeds and nuts etc. [3] that could serve as source of biodegradable oil for petroleum substitution. Some of such oil seeds and nuts include but not limited to Irvingia gabonensis (IG), soya bean, palm trees, Jatropha curcas , groundnut, Terminalia catappa L etc.
Irvingia gabonensis otherwise known as wild bush mango or “Ogbono” in south eastern part of Nigeria is a member of the Simarubaceae family [4]. It is an economic tree with its origin traced to most tropical forest of West and Central Africa [5]. In West Africa, Irvingia gabonensis is seen as the most important tree being encouraged for domestication [6-7]. Thus, it has attracted the attention of the World Agroforestry Centre (formerly the International Centre for Research in Agroforestry, ICRAF), together with its partners, thereby making it their choice tree in their agroforestry tree domestication programme [7-8]. Seasonally (between April to July), Irvingia gabonensis tree produces lots of edible fruits with limited consumption of the fresh fruits [5]. However, there is greater utilization of the kernel. As a result of this, it is a common practice to split the fruit into two using cutlass, in other to remove the split cotyledon (kernel) with knife. Thereafter, the flashy mesocarp is discarded to rot, while the kernel is used for number of purposes [9].
Over the years, researches on Irvingia gabonensis kernel (IGK) have mainly been on its nutritional and medicinal applications, as well as the used of the milled kernels as condiment in soup as thickener, due to its rich fat and protein content [10-12]. Medicinally, it is used in body weight reduction of obese persons [13], with little attention to its industrial applications. However, its kernels have been found to have local industrial application, as it is used in the making of local soap, due its high oil content [14]. Previously, researches have shown that IGK exhibits very high oil content which ranges between 60% and 69.76%. Hence, makes it’s industrially utilization very attractive [11, 15-17]. Never the less, few researches have been conducted on the possible application of Irvingia gabonensiskernels oil (IGKO) industrially for biodiesel production [15]. Therefore, there is need to extend the utilization of IGKO in the production of transformer oil (TO), since to the best knowledge of the authors, no published work have been recorded in this direction [18].
Prior to the use of vegetable oil like IGKO for industrial applications, there is need for the oil to be extracted from the seeds/kernels. In other to achieve this goal, the choice of extraction method becomes very important [19]. Several extraction methods exist. Some of these methods are solvent extraction, sonication-assisted extraction; microwave-assisted extraction, supercritical fluid extraction, accelerated solvent extraction etc [20]. However, solvent extraction method using soxhlet extractor was adopted in this study because of its simplicity, high oil yield and oil quality associated with the method [20-21]. Solvent extraction method has been utilized severally for extraction of oil from fruits, seeds and nuts. Some of such fruits, seeds and nuts include Hazelnut (Corylus avellana L. ) [22],Maclura pomifera (Rafin.) Schneider seed [23], Prunus armeniaca L . [24], Sacha inchi (Plukenetia volubilis ) seeds [25], coconut waste [26]. Similarly, Irvingia gabonensisis not left out, as solvent extraction methods have been utilized to extract oil from it [11,15]. It is important to state that in solvent extraction, the knowledge of the kinetic of oil extraction is of paramount importance. This is because it assists in the determination of the highest oil yield within the studied time intervals [27]. In other words, the need carry out extensive study on the kinetics of oil extraction from Irvingia gabonensis seed kernels.
Previously, researchers have carried out studies on the kinetics of oil extraction from seeds, and nuts. For instance, oil extraction kinetics have been applied to the extraction of oil from Jatropha curcas[28], sunflower seeds [29-30], fluted pumpkin seed [31], coconut waste [26], Neem seed (Azadirachta indica A. Juss ) [32] and Prunus persica [33]. It is therefore very necessary to study the kinetics of oil extraction process of different varieties of seed or nut. This is because from literature, it has been established that the ease of extraction of oil from seed/nuts varies [34]. Therefore, the study of the kinetics of oil extraction fromIrvingia gabonensis kernels becomes very important, since to the best of knowledge of the authors, there haven’t been any published work in that regard.
It is worth knowing that during oil extraction process, the extraction rate (the rate at which equilibrium is attained) is influenced by factors like, solute and solvent diffusion capacity, size, shape, internal structure of seeds particles (matrix), and the dissolution rate of the solvent on the oil soluble substances (solute) [21]. In other words, the kinetics of Irvingia gabonensis kernel oil (IGKO) extraction consists of the releasing of oil from porous or cellular matrices, into the solvent through the process of mass transfer mechanisms. This oil (solute) linked to the solid matrix of the kernel particles by either physical or chemical forces must be transported to the solvent phase by dissolution process [35]. For this to occur, three important steps have to be taken into consideration: (1) solvent penetration into the seed matrix (tissue), (2) intercellular miscella formation, and (3) extracted oil diffusion into the exterior miscella [27]. In other words, mathematical modeling of oil extraction kinetics from seeds and nuts is an activity of great importance. This is due to its economic benefits to industries. In the light of this and other benefits, it is necessary to develop models for extraction process based on the process parameters. In order to achieve this, the estimated process parameters, needs to be used in the development of the model that considers the phase behavior, state of equilibrium, solubility, diffusion and dissolution of the process [35-36]. Several models have been used by researchers in the study of oil extraction kinetics process for oil seeds like, olive cake [37], sunflower [38-39], rapeseed (canola) [27].
However, while extraction kinetics has been extensively studied by many researchers, there is limited or no studies in the literature on that of oil extraction kinetics and thermodynamics of Irvingia gabonensiskernels oil extraction. Therefore, the objectives of this study were to study the influence of process parameters of temperature, time, and particle size on IGK oil yield, as well as to fit the obtained experimental data into two closely related extraction kinetic models (hyperbolic and pseudo second order), so as to determine the model that best fit the experimental kinetic data. Also, the kinetic models of the extraction processes under different process parameters were established for predicting the extraction processes. Additionally, the coefficient of determination (R2) and for statistical error analysis functions [root mean square (RMS), the average relative error (ARE%) and the standard error of estimation (SEE)], were used to study the fitting of the extraction kinetics models to the experimentally obtained kinetics data. Furthermore, Arrhenius equation was used to evaluate the effect of extraction temperature on the kinetic models. The thermodynamic parameters of oil extraction fromIrvingia gabonensis kernels were also evaluated. Furthermore, the physicochemical characterization of the IGKO was carried with the aim of evaluating its potentiality as base fluid for transformer oil production. Finally, Fourier Transform Infrared (FTIR) was afterwards used to ascertain the functional groups present in the IGKO.
  1. Materials and methods
  2. Sample collection and preparation
Irvingia gabonensis kernels (IGK) were procured from Nkwo-Agu market, Umuaga in Udi Local Government Area, Enugu State, Nigeria. They were oven dried at temperature of 60 °C for 12 h. Thereafter, the dried samples were milled using manual grinder. They were then sieved with different sieve sizes to obtain five different average particle sizes (0.5, 1.0, 1.5, 2.0 and 2.5 mm). The ground samples were sealed and stored until they were ready for use.
Solvent extraction experiment using Soxhlet extractor
15 g of dried milled IGK powder of a particular particle size was packed in a thimble of the soxhlet extractor. The extractor was then filled with 150 ml of n-hexane. The experiments were performed at five different temperatures (35, 40, 45, 50, and 55 °C) and at five different extraction times (30, 60, 90, 120, and 150 min) for each particular average particle size (0.5, 1.0, 1.5, 2.0 and 2.5 mm). The extraction temperature was measured using an electronic thermometer (± 0.1°C, Hanna HI-9063), while the time was measured using a stop watch. The oil yield was calculated using AOAC method no. 920.85 [40] using automatic soxhlet apparatus (Soxtec 2050 FOSS, Denmark) in line with manufacturer manual guidelines. After each extraction process, the solvent was removed at 60 °C using rotary evaporator (model N- 1000S-W, EYELA, Tokyo, Japan). The extraction done under every set of conditions was performed three times and the average value recorded. The oil yield of IGK was calculated using equation (1).
\(\%\ Yield\ =\ \frac{weight\ of\ oil\ extracted\ (g)}{weight\ of\ sample\ (g)}\ \times 100\ \%\)(1)
Kinetics
The analysis and design of extraction processes needs relevant kinetic data since it is the most important information to be used to understand the extraction process. In order to obtain these kinetic data, experiments were carried out at temperatures (35, 40, 45, 50, and 55 °C) and at extraction times (30, 60, 90, 120, and 150 min) for each particular particle size (0.5, 1.0, 1.5, 2.0 and 2.5 mm) as stated earlier. Thereafter, the obtained experimental kinetics data were fitted to hyperbolic and pseudo second order models.
Hyperbolic model
Hyperbolic model has been applied in food engineering science as peleg’s model in equation (2).
\(c\ =\ c_{0}\ +\ \frac{t}{K_{1}\ +\ K_{2}t}\) (2)
Where K1 is the model rate constant, K2is the model capacity constant, c is the concentration of solute in the extraction solvent at any time (g L-1) and c0 is the initial concentration of the solute in the sample particle (g m-3) and is usually equal to zero.
Therefore, the extraction curves (% oil yield vs. time) exhibits similar sharp as the sorption curves (moisture content vs. time) proposed by peleg. Hence, the feasibility of using the same mathematical model proposed by peleg [41] to describe the kinetics of oil extraction from Irvingia gabonensis kernels.
However, in this case, the extraction rate at the very beginning C1 (min-1) and constant related to maximum extraction yield C2 (min-1) were taken into consideration [19]. Thus, the hyperbolic model used to describe the oil extraction from Irvingia gabonensis kernels is expressed as in equation (3).
\(\overset{\overline{}}{y}\ =\ \frac{C_{1}t}{1\ +\ C_{2}t}\) (3)
Recently, equation (3) has been used to model the extraction of resinoid from aerial parts of St. John’s wort (Hypericum perforatum L. ) [19], extraction of protopine from Fumaria officinalis L.[42], as well as in the extraction of total polyphenols from grapes [43]. Equation (3) results from a second order rate law as could be seen in equation (4). As such, it is important to state that peleg’s model [41] and pseudo second-order integrated rate law, equation (4), are both hyperbolic equations [44].
\(C_{t}\ =\ \frac{C_{t}^{2}\text{kt}}{1\ +\ C_{s}\text{kt}}\) (4)
Where \(C_{t}^{2}k\) and \(Csk\) in equation (4) are equivalent to C1 and C2 respectively in equation (3). k is the second order extraction rate constant while Ctand Cs are the concentrations of oil in the solution at any time t and at saturation, respectively (g L-1).
From equation (3), it is important to state that the extraction is first-order at the very onset, and drops to zero-order in the latter phase of the extraction process. As such, when C2t<< 1, equation (3) reduces to equation (5).
\(\overset{\overline{}}{y}\ \approx\ C_{1}t\) (5)
And when t → s, the equilibrium is reached\(\left(y_{i}\ =\ y_{e}\right)\), so
\({y\overline{}}_{e}\ =\ \frac{y_{e}}{y_{0}}\ =\ \frac{C_{1}}{C_{2}}\)(6)
Hence, C1 is a constant that is related to the rate of extraction at the beginning, while the ratio C1/C2, the peleg capacity constant which is related to the maximum of extraction yield, is the equilibrium concentration of the extracted oil.
When equation (3) is linearized, equation (7) is obtained.
\(\frac{1}{y\overline{}}\ =\ \frac{1}{C_{1}}\ \times\ \frac{1}{t}\ +\ \frac{C_{2}}{C_{1}}\)(7)
The plot of 1/y̅ (that is 1/yield) against 1/t, gives intercept as C2/C1 and slope as 1/C1.
Pseudo second-order model
The second-order rate law had been used over the years to model solvent extraction of a number of substances from plants, leaves, seeds and nuts [45-46]. Extraction kinetic models that are based on a second-order rate law are usually used in both conventional and non-conventional extractions [45-46]. It provides a suitable illustration of solid-liquid extraction process as such it was applied to describe the kinetics of oil extraction from Irvingia gabonensis kernels.
For a second-order rate law, the rate of dissolution of the oil contained in the solid to solution can be described by equation (8).
\(\frac{dC_{t}}{\text{dt}}\ =k\ \left(C_{s}\ -\ C_{t}\right)^{2}\)(8)\(=k\ \left(Cs\ -Ct\right)2\)
Where:
\(\frac{dC_{s}}{\text{dt}}\ =the\ extraction\ rate\ \left(\text{g\ }L^{-1}\ \min^{-1}\right)\)
k = the second-order extraction rate constant (L g-1min-1)
Cs = the extraction capacity (concentration of oil at saturation in g L-1)
Ct = y̅ = the concentration of oil in the solution at any time (g L-1), t (min)
By taking the initial and boundary condition t = 0 to t = t and Ct = 0 to Ct=Ct, the integrated rate law for pseudo second-order extraction was obtained as equation (9).
\(C_{t}\ =\ \frac{C_{t}^{2}\text{kt}}{1\ +\ C_{s}\text{kt}}\) (9)
The linearized form of equation (9) is equation (10).
\(\frac{C_{t}}{t}\ =\ \frac{1}{\left(\frac{1}{KC_{s}^{2}}\right)\left(\frac{t}{C_{s}}\right)}\)(10)
This can be further linearized in the form of equation (11).
\(\frac{t}{C_{t}}\ =\ \frac{1}{KC_{s}^{2}}\ +\ \frac{t}{C_{s}}\)(11)
Thus, as t approaches 0, the initial extraction rate, h, is written as in equation (12).
\(h\ =KC_{s}^{2}\) (12)
When equation (10) is rearranged, the concentration of oil at any time can be obtained, equation (13).
\(C_{t}\ =\ \frac{t}{\frac{1}{h}\ +\ \frac{t}{C_{s}}}\) (13)
The initial extraction rate, h, the extraction capacity, Cs and the pseudo second order extraction, k, can be calculated experimentally by plotting t/Ct vs t where by Cs and k are determined from the intercept and slope of the linear plot, respectively.
Temperature effects
Arrhenius equation was used in evaluating the effect of temperature of extraction on the kinetic models. That is, it was used to describe the relationship between extraction rate constant (k) and temperature (T). Equation (14) shows the Arrhenius equation.
\(Ln\ k\ =Ln\ k_{0}\ +\ \left(-\ \frac{E_{a}}{R}\ \times\ \frac{1}{T}\right)\)(14)
Rearranging the above equation (14), results to equation (15).
\(k\ =\ k_{0}e^{\frac{-E_{a}}{\text{RT}}}\) (15)
Equation (15) can also be re-written in the form shown in equation (16). When this is done, the unit of Ea is written as (KJ mol-1).
\(k\ =\ k_{0}\exp\left(-\ \frac{1000E_{a}}{\text{RT}}\right)\) (16)
Where k0 is the pre-exponential factor for extraction rate constant (Lg-1 min-1), Ea represents the activation energy of extraction (J mol-1). R is the ideal gas constant (8.314 J mol-1 K-1), T is the temperature of extraction (K). The pre-exponential factor, k0 and the activation energy, Ea can be determined using the natural logarithm of Eq. (15). The plot of Ln (k) against 1000/T was used to calculate k0 and Ea.
Thermodynamic parameters
The thermodynamic parameters enthalpy change (ΔH) and entropy change (ΔS), for the extraction of oil from Irvingia gabonensis kernels were calculated using Van’t Hoff equation (17).
\(Ln\ K\ =\ -\ \frac{H}{\text{RT}}\ +\ \frac{S}{R}\) (17)
Equation (17) can be re-written to include the Gibbs free energy change in the form of equation (18).
\(Ln\ K\ =\ \frac{G}{\text{RT}}\ =\ -\ \frac{H}{\text{RT}}\ +\ \frac{S}{R}\)(18)
The Gibbs free energy change was calculated using equation (19).
\(G\ =\ H\ -T\bullet S\) (19)
\(K\ =\ \frac{Y_{T}}{Y_{u}}\ =\ \frac{m_{L}}{m_{S}}\) (20)
Where K is equilibrium constant, YT is the yield of oil at temperature T, Yu is the percentage of the un-extracted oil, mL is amount of IGK in liquid at equilibrium temperature T, ms is amount of IGK in solid at equilibrium temperature T, R is gas constant (8.314J/mol K), while ΔH (kJ/mol), ΔS (kJ/mol), and ΔG (kJ/mol) are enthalpy, entropy and Gibbs free energy, respectively.
Statistical Analysis
The degree at which the models studied statistically represent the data obtained experimentally were by the evaluation of correlation coefficient (R2) using equation (21), the root mean square (RMS) [19], the average relative error (ARE%) [47] and the standard error of estimation (SEE) [47]. The error functions were computed using the expressions in equations (22), (23) and (24) for RMS, ARE and SEE, respectively.
\(R^{2}\ =\ \frac{\sum_{N=1}^{N}\left({y\overline{}}_{\exp}\ -\ {y\overline{}}_{\text{cal}}\right)^{2}}{\sum_{N=1}^{N}\left({y\overline{}}_{\exp}\ -\ {y\overline{}}_{\text{cal}}\right)^{2}}\)(21)
\(RMS\ =\ \sqrt{\frac{1}{N}\ \sum_{i\ =1}^{N}\left(\frac{{y\overline{}}_{\exp}\ -\ {y\overline{}}_{\text{cal}}}{{y\overline{}}_{\exp}}\right)^{2}}\)(22)
\(ARE\ =\ \frac{100}{N}\ \times\ \sum\frac{|\ x\ -y\ |}{x}\)(23)
\(SEE\ =\ \sqrt{\frac{\sum\left(x\ -y\right)^{2}}{\text{dt}}}\)(24)
Where N is the number of experimental data points. y̅caland y̅exp are the calculated and experimental values, respectively, in equations 22. Similarly, x and y are experimental and calculated values, respectively in equations 23 and 24.
Physicochemical properties of Irvingia gabonensiskernels oil (IGKO)
IGKO was characterized after it was extracted. The oil density (AOAC 985.19), iodine value (AOAC 993.20) and acid value (AOAC 969.17), were determined according to AOAC official technique [48]. On the other hand, the viscosity and dielectric strength were measured according to ASTM D445, [49] and IEC 60156, [50] standard methods, respectively. The oil samples were tested three times and the average value taken.
Fourier transform infrared spectroscopy (FTIR) analysis
The FTIR analysis of the IG oil sample was carried out using Scientific Infrared Spectrophotometer Model 530.
  1. Results and discussion
  2. Experimental results
  3. Effect of temperature
Temperature of extraction is one of the most essential parameter in extraction process. This is because of the very high sensitivity of the chemical constituent of plants, seeds, nuts, kernels and leaves to heat. Solute solubility, as well as the diffusion coefficient, increases with the increase in the extraction temperature, as such, influencing the extraction process [51].
The effect of temperature on extraction rate of oil from IGK has been studied over temperatures range of 35 – 55 °C, keeping the particle size constant at particle sizes (0.5, 1.0, 1.5, 2.0 and 2.5 mm), in each case [Fig. 1 (a – e)]. It could be observed that increase in temperature from 35 to 55 °C, resulted in the increase of the oil extraction yield irrespective of the solute particle size. This could be attributed to the increase in diffusion of oil with decrease in its viscosity as the temperatures increased [26,52]. Similarly, the mass transfer coefficient of the process also increased with temperature thereby affecting diffusion [26].
Fig. 1(a – e) shows the extraction of oil from IGK using soxhlet extractor operated at maximum time of 150 mins. It could be seen that the rate of extraction was fast at the beginning of the process, and gradually reduces. This was due to the dissolution of free oil from the surface of the IGK when exposed to the fresh solvent, thereby leading to quick oil extraction. This leads to fast increase in the rate of extraction. This was in agreement with the findings of Sulaiman et al. [26] and Sayyar et al. [53] for the extraction of solid coconut waste and jatropha seeds oils, respectively.
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