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.
- Materials and methods
- 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.
- Results and discussion
- Experimental results
- 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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