A review of kinetic models and reaction conditions of heterogeneous transesterification of vegetable oils.
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\r\n\tComputer graphics are not entirely an original topic, because it defines and solves problems using some already established techniques such as geometry, algebra, optics, and psychology. The geometry provides a framework for describing 2D and 3D space, while the algebraic methods are used for defining and evaluating equality related to the specific space. The science of optics enables the application of the model for the description of the behavior of light, while psychology provides models for visualization and color perception.
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\r\n\t3D computer graphics (or 3D graphics, three-dimensional computer graphics, three-dimensional graphics) is a term describing the different methods of creating and displaying three-dimensional objects by using computer graphics.
\r\n\tThe first types of graphic interpretations were put in the plane (two-dimensional 2D). Requirements for a universal interpretation led to a three-dimensional (3D) interpretation content. From these creations have arisen applied mathematics and information disciplines of graphic interpretation of content - computer graphics. It relies on the principles of Mathematics, Descriptive Geometry, Computer Science and Applied Electronics.
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\r\n\t3D computer graphics or three-dimensional computer graphics use a three-dimensional representation of geometric data (often in terms of the Cartesian coordinate system) that is stored on a computer for the purpose of doing the calculation and creating 2D images. The images that are made can be stored for later use (probably as animation) or can be displayed in real-time.
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\r\n\tObjects within the 3D computer graphics are often called 3D models. Unlike rendered (generated) images, data that are ""tied"" to the model are inside graphic files. The 3D model is a mathematical representation of a random three-dimensional object. The model can be displayed visually as a two-dimensional image through a process called 3D rendering or can be used in non-graphical computer simulations and calculations. With 3D printing, models can be presented in real physical form.
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\r\n\tComputer graphics have remained one of the most interesting areas of modern technology, and it is the area that progresses the fastest. It has become an integral part of both application software, and computer systems in general. Computer graphics is routinely applied in the design of many products, simulators for training, production of music videos and television commercials, in movies, in data analysis, in scientific studies, in medical procedures, and in many other fields.
Biodiesel is a renewable fuel of key importance to meet environmental and economic sustainability. It is produced by transesterification of vegetable oils or animal fats with an alcohol, such as methanol or ethanol, on an alkaline, acid or enzyme catalyst, and it is composed of a mixture with at least 96 wt% of fatty acid methyl or ethyl esters (FAME or FAEE).
A high percentage of the current investigations in the domain of biodiesel production is oriented toward the design of suitable solid catalysts, either with acid or with alkaline properties. Likewise, much emphasis is being placed on research on free or supported enzyme catalysts. Other transesterification methods that are under development include the application of supercritical conditions without the use of catalysts and the use of radiofrequency or ultrasonic assistance.
The development and optimization of biodiesel production processes involve much experimental work, as well as the application of kinetic models that try to describe the process in a more comprehensive and realistic way. Some of the variables that are commonly studied in the development of kinetic models are the reaction temperature, the feedstock composition, including different contents of free fatty acids (FFAs), the alcohol-to-oil molar ratio, the mixing speed and the reaction time. The internal and external mass transfer limitations when using solid catalysts have also been studied.
This chapter deals with the main challenges in the development and application of kinetic models for the transesterification reaction, as well as representative results of current developments in this area.
The development of kinetic models of chemical transformation processes for the production of higher added-value products is a powerful tool for reactor design. The kinetic model is also necessary for the optimization of the complete process, including the separation and heating steps. Thus, the kinetic model must be incorporated into the reactor model and then applied in the process simulation.
Regarding chemical or biochemical transformations in reactors or bioreactors, the kinetic models are of great help in the selection of the most favorable reaction conditions (e.g. temperature, pressure, mixing rate) to maximize the formation of desired products with the least investment of material and the use of economic resources. This also applies to the different biodiesel production processes, including homogeneous, heterogeneous, enzyme catalysis, and so on, which will be addressed in the next sections.
A well-planned experimental study and the subsequent development of a kinetic model are considered one of the most crucial steps in the chemical process development for industrial applications.
Kinetic models may offer different levels of detail and predictive capabilities, as they can take into account mass and heat transfer phenomena, as well as thermodynamic equilibrium. The level of theory for modeling the reactions can go from the use of quantum chemistry to the individual elementary steps up to a series of encompassed reaction steps between pseudo-components (lumped model). The catalyst deactivation, the presence of undesired side reactions, the consideration of inhibition processes and a detailed feedstock composition are among other factors that can be considered to derive more realistic kinetic models and with a higher predictive capacity. A more comprehensive model can give a more significant response and provide more detail on the composition and, therefore, on the quality of the products. Thus, a more robust model can be more useful; however, the number of kinetic parameters can increase significantly. The estimation of these parameters must be performed rigorously in order to generate reliable results.
On the other hand, modeling of chemical reactors is very useful for the simulation and control of the process involved. This requires a previous selection of the kinetic model to be applied. Reactor modeling is used to determine concentration, temperature and pressure profiles, generating valuable information for the scaling-up of the process. The reactor model may include more or less the detail of the variables of interest, being possible to determine temperature and concentration profiles at intraparticle conditions, as in the case of heterogeneous reactors.
The development of kinetic models of biodiesel production processes and their application to simulate and optimize these processes has been investigated and reported by a number of researchers. Portha et al. [1], for example, reduced the excess of ethanol used in the transesterification reaction of oils in a continuous process by using a two-stage continuous heterogeneous catalytic reactor. Their simulation results enabled them to determine that the overall performance of the system could be improved with the use of an inter-stage methanol addition as well as by changing the reaction temperature for the second reactor. In their experimentation with triolein as a model compound, the authors found converting the main part of triolein in the first reactor and converting diglyceride and monoglyceride in the second one to be useful. Their simulations also indicated that a higher temperature in the second reactor was advisable to enhance reaction rates at this stage. They also worked on the optimization of the inlet methanol-to-triolein molar ratio, finding that the use of a molar ratio larger than than 25:1 mol/mol had no further significant impact on the biodiesel yield. Furthermore, by introducing the kinetic model into a reactor model, the authors calculated internal concentration profiles and found that the internal diffusion of triglycerides (TG), diglycerides (DG) and monoglycerides (MG) was the limiting phenomena in the overall transformation.
A kinetic model can also be applied as a strategic tool for obtaining a better understanding of the rates of product formation and the inhibition patterns present in the transformation scheme [2]. A reaction scheme for the biodiesel production, for example, through enzymatic processes, can consider much more reaction steps and thus a higher number of reaction parameters. This certainly introduces an additional complication in the development of a kinetic model, but when this model is solved, it can be used to design a reactor based on enzyme catalysis and ultimately to optimize the process.
In the field of research and process development, the application of kinetic models that are able to accurately simulate the process at different reaction conditions is useful to provide the guidelines for further experimental work, helping in this way to discard potentially unproductive experimental trials. Models can also help to predict the effect of composition on the quality of the product. For example, a model could predict how the FFA or the water content in the feedstock can affect the reaction conversion and therefore the yield and quality of biodiesel.
There is a consensus on the reaction steps involved in the transesterification process of triglycerides, which are indicated in Figure 1. These are the three consecutive and reversible reactions.
Consecutive reversible reaction steps considered in the formation of methyl esters from triglycerides.
In the first reaction, triglyceride (TG) molecule reacts with an alcohol molecule, typically methanol (M) to produce diglyceride (DG) and a fatty acid methyl ester (ME). Then, in the second reaction, diglyceride reacts with alcohol to form monoglyceride (MG) and another molecule of fatty acid ester. In the third reaction, monoglyceride (MG) reacts with alcohol to produce glycerol (G) and a third molecule of fatty acid ester.
When the concentration of FFA present in the oil requires a previous (or simultaneous) stage of esterification, the following reaction that forms one molecule of methyl ester and one molecule of water (W) is considered in the model:
The development of kinetic equations is performed from the reactions taken into account for each particular case. The final form of the kinetic expressions is affected by the nature of the reacting mixture, homogeneous or heterogeneous, the selected alcohol, the alcohol-to-oil molar ratio and the influence of mass transfer effects, among other factors. In the following subsections, representative kinetic models for each type of reaction are discussed.
Most of the work reported on the kinetics of transesterification of oils and fats has been derived from experiments with homogeneous catalysts and mainly with alkaline catalysts.
Freedman et al. [3] carried out the homogeneous transesterification of soybean oil using butanol and methanol and both alkali and acid catalysts, finding that alkaline-catalyzed reactions proceed at considerably faster rates than acid-catalyzed transesterification. The kinetic coefficients reported at 60°C for the former were two to four orders of magnitude higher than the latter. For this reason and because alkaline catalysts are less corrosive to industrial equipment than acid catalysts, most commercial biodiesel processes are conducted with alkaline catalysts. Sodium alkoxides are among the alkaline catalysts that have been used extensively for this reaction [4]. Freedman et al. [3] also found that the reaction with butanol follows a second-order reaction. These authors performed alkaline- and acid-catalyzed experiments using a larger excess of alcohol. From their results with a butanol-to-soybean oil molar ratio of 30:1 mol/mol, they found that the forward reaction followed pseudo-first-order kinetics for both alkaline and acid catalysts, as expected. The kinetic coefficients for the first reaction shown in Figure 1 are higher than those for the second and third reactions. This is valid for the forward and reverse reactions and is a general result reported by different authors for alkaline-catalyzed transesterification [5]. In the case of acid-catalyzed tests, the rate coefficients for the first reaction were lower than those for the second and third reactions for both forward and reverse reactions. This has also been reported by other authors [6]. The activation energies for all the alkaline- and acid-catalyzed transesterifications using both butanol and ethanol ranged from 8000 to 20,000 cal/mol. These results are also in agreement with the activation energies reported by other researchers [5, 6].
Other kinetic models like the one proposed by Gonzalez-Brambila et al. [7] consider the effects of mass transfer phenomena on the transesterification of soybean oil with methanol and NaOH in a batch reactor, using the experimental data from the study [8] and by proposing a mass transfer-kinetic dynamic model. Two liquid phases were considered: a non-polar TG-rich phase and a polar methanol-rich phase, and the reaction was considered to take place only in the interphase of the drops. Besides the six kinetic coefficients derived from Figure 1, the mass transfer coefficient between drops and alcohol phase was evaluated. In this way, the model can not only describe the evolution on time of TG, DG, MG, glycerine, methanol and ester composition but also estimate the reduction of drops’ radii during the reaction, which are relevant data considering that reaction takes place on the drops’ surface.
The use of heterogeneous catalysts presents several advantages over the use of homogeneous catalysts, among which the ones that have been most emphasized include the elimination of the washing section and huge amounts of waste water, reusable catalyst and easier disposal of the spent one, high purity of glycerol and the end product [9]. Hence, several conventional solid bases and acids (with and without promoters/dopants) have been investigated with this purpose. These included different solid acid catalysts such as sulphated zirconia [10], zeolites [11], heteropolyacids [12], ion-exchange resins [13] and sulphonated carbons [14]. Moreover, it has been reported that working under optimal conditions, heterogeneous transesterification can approximate the activity obtained with homogeneous catalysts. For example, Kim et al. [15] used the heterogeneous catalyst Na/NaOH/γ-Al2O3, reaching conversions of 95%, with a methanol-to-oil molar ratio of 9:1 mol/mol at an atmospheric pressure. These results are comparable to those obtained with the conventional homogeneous catalyst (NaOH).
Like homogeneous acid catalysis, when the oil to be fed has a concentration of FFA greater than 3 wt%, an acid solid catalyst that tolerates the presence of FFA and possess activity for both esterification and transesterification to convert FFA and oil to biodiesel should be used.
Normally, the first option to carry out the scaling-up of a continuous heterogeneous transesterification process is the use of a fixed bed reactor (FBR), due to the simplicity of its design and the ease of its operation. However, the effect of the diffusive resistances must be considered in order to obtain a reactor design that meets the expected conversion levels.
The transesterification reactions of oils in a fixed bed reactor (FBR) present different mass transport processes that affect the rate of production of biodiesel. The reaction system has two liquid (L) phases and one solid (S) phase represented by the catalyst. One of the liquid phases is rich in oil, while the other is rich in methanol, or any other alcohol. In this way, the external diffusive resistances associated with the transport of methanol and triglyceride toward the surface of the catalyst must be considered and the intraparticle diffusive resistances as well. The modeling of these complex processes involves the calculation of mass transfer coefficients of the components involved in the chemical reactions. Moreover, as reaction proceeds, the solubility of methanol in the oil-rich phase is increased due to a higher presence of esters, which act as co-solvents for methanol. The formation of monoglycerides and diglycerides increases the solubility of methanol in the oil-rich phase. As this solubility increases, the diffusive resistances at the L-L interface decrease [8], accelerating the transport of the reactants and therefore increasing the reaction rates. A similar effect is observed in the case of feedstock with a high FFA content, giving rise to a greater solubility and ease of transportation of the reactants in the L-L interface and thus allowing higher rates of biodiesel formation. This was confirmed by the results of Bhoi et al. [16], who reported that the rates observed for pure TG were significantly lower than those for a mixture of TG and FFA. They also estimated that for a mixture containing 20 wt% FFA, the rise in solubility was of the order of 1.35–1.5 times the solubility in pure TG. Similar results have also been reported by Singh et al. [17].
The application of a model that considers the mentioned effects in the three consecutive reversible reaction steps shown in Figure 1 is not an easy task, since it requires data on liquid-liquid distribution for reactants and products and the relative proportion of each phase at different reaction conversions.
Bhoi et al. [16] developed a model that incorporates the effect of mass transfer resistances at both L-L and L-S interfaces for the transesterification reaction and simulated an FBR. Experimental data were obtained from two reactors, a spinning basket reactor (SBR) and an FBR and using a catalyst in pellets of a 6-mm diameter and an 8–10-mm length. Higher reaction rates in the reactor free of external diffusive resistances, that is, the SBR, were observed, concluding that the FBR is strongly hampered by external mass transfer resistances. The estimated kinetic parameters with the SBR were observed to be affected by internal diffusive resistances, which were corroborated by an estimated value of the activation energy of 25 kJ/mol, corresponding to the first reaction (forward) shown in Figure 1. Although this reaction was only considered in their kinetics for lower conversions, they were able to estimate the L-L and the L-S mass transfer coefficients. The latter was found to be four to eight times higher. Thus, they concluded that resistance in the L-L interface determined the overall rate of the process.
Bhoi et al. [1] developed a model for an FBR with axial dispersion considering mass transfer limitations in the catalyst as well as dynamic aspects. The reactor was considered to operate isothermally considering that transesterification reactions are almost athermic. The reaction stage consisted of two FBR connected in series and at 50 bar and 175°C. The simulations yielded a conversion of triolein (model feedstock) of 87% with a methanol:triolein ratio of 36:1 mol/mol, over a solid alkaline catalyst. It was found that the kinetic system behaves according to a second-order rate law. Adsorption terms were not included in the developed kinetic expressions. Similar to what has been reported for homogeneous-catalyzed transesterification of triglycerides, the calculation of the kinetic coefficients for the three reactions shown in Figure 1 indicated that the first reaction was the fastest, while the second and third reactions were about one order of magnitude lower.
In an experimental study that considered the adsorption process, Dossin et al. [18] evaluated the intrinsic kinetics of the transesterification of ethyl acetate with methanol over an MgO catalyst. Among the evaluated models, the one that best fitted the experimental data corresponded to an Eley-Rideal (ER) type model, with the adsorption of methanol as the rate-limiting step.
Other promising transesterification methods for producing biodiesel that are gaining more relevance as research progresses are enzyme catalysis and supercritical methanol.
Among the main advantages of using enzymes (free or immobilized) is that they can process variable and low-quality feedstocks, as they are less sensitive to high FFA and water content. Then, enzymes can process FFA and TG in a single reaction step. Moreover, when using enzymes, there is no need for a subsequent washing step. On the other hand, lipases have the disadvantage of being sensitive to high concentrations of methanol, and their implementation is currently more expensive compared with other methods. The mechanism widely accepted for describing enzymatic transesterification corresponds to a double-displacement type or a ping-pong mechanism [19]. This reaction scheme presents a great complexity to be modeled, since the number of kinetic coefficients involved is high, and their experimental determination is a great challenge. Due to this complexity, simplified models are used, which generally do not describe the formation and transformation of di- and monoglycerides, as well as the influence of temperature on the enzyme deactivation and the conversion limits derived from equilibrium. The complexity of the process can further increase if the presence of multiple phases is taken into account when immobilized enzymes are employed. Moreover, stearic effects may have an important impact due to the large size of the glyceride molecules. To promote the fitting of experimental data to kinetic models of the process, simplified models such as the Michaelis-Menten type are used [20], although their predictive capacity is limited generally. Kinetic studies on the enzymatic production of biodiesel have been performed mainly with immobilized lipases, and most of these simplified models consider only irreversible reactions. Firdaus et al. [2] applied a simplification of the ping-pong model that resulted in the evaluation of about 30 rates coefficients, including those corresponding to the reversible steps. This model was later applied to describe the transformation of oil with a liquid lipase from
Catalytic and non-catalytic transesterification using an alcohol at supercritical conditions is another method under intensive investigation. This process has a high potential for both the transesterification of TG and for the esterification of FFA. Conversions reported are commonly greater than 90%, and reaction times are as short as 10 min or less [21]. The high temperatures and pressures required for the application of this technique represent, however, a limitation for its development and application, mainly due to the high energy costs of the process. In recent years, there have been an increasing number of reports in which this process is applied, either with the use of a catalyst or without it. In a recent work [22], the application of simplified kinetic models that describe only the formation of esters and disappearance of triglycerides as a function of conversion has been performed.
Homogeneous catalysis is commonly used during transesterification reaction, and alkaline and acid catalysts are used. The most active catalysts have been reported to be alkaline ones [23].
Two mechanisms are involved in transesterification reaction depending on whether acid or basic catalysts are used.
In the case of alkaline catalysts, the reaction proceeds very fast, hydroxides, alkoxides, and sodium and potassium carbonate being the most commonly used catalysts (Figure 2). When an alkali is used, the first step is the formation of an alkoxide, which is a strong nucleophile that attacks the electrophilic carbon in a carbonyl group of the triglyceride. This attack turns the carbonyl into a tetrahedral intermediate as shown in the second step. Then, the tetrahedral carbon is separated from the intermediate to form an alkyl ester (third step). Deprotonation of catalyst regenerates the alkali, whereas the proton is attached to a diglyceride anion as shown (fourth step). Catalyst can react with another alcohol molecule and the mechanism is repeated until the catalyst reacts once again with an alcohol molecule to produce glycerol and alkyl esters [24].
Alkali-catalyzed reaction mechanism.
When sulphuric or sulphonic acid is used, a very high yield of alkyl esters is obtained. In this case, the reaction mechanism is acid catalyzed. Early research [3] has reported that transesterification of soybean oil with methanol reached almost 100% after 50 h of reaction at 65°C using 1 mol% of sulphuric acid with an alcohol-to-oil molar ratio of 30:1 mol/mol, whereas using ethanol and 1-butanol as alcohols took 18 and 3 h, respectively; however, reaction temperature was higher (78 and 117°C, respectively). Inconvenience such as glycerol recovery due to alcohol in excess is to be expected by which the oil-to-alcohol molar ratio needs to be optimized [24].
Figure 3 shows a schematic reaction mechanism when an acid is used as catalyst, which is valid not only for a monoglyceride but also for di- and triglycerides. Protonation of the carbonyl group is the first stage (I). A carbocation (II) is then formed and undergoes a nucleophilic attack. Alcohol is attached to the tetrahedral intermediate (III), and a new ester (IV) is obtained by glycerol elimination and catalyst regeneration. The carbocation formed in step II is highly reactive by which water must be avoided during reaction because this molecule can act as a nucleophile and form carboxylic acids, which is a competitive reaction [24].
Acid-catalyzed reaction mechanism.
To select the most suitable transesterification reaction pathway, either alkaline or acid, it is necessary to determine firstly the FFA content. This value must be lower than 3 wt% to proceed by the alkaline-catalyzed route without the significant formation of soap. This can lead to an emulsion that makes difficult the biodiesel and glycerol phases separation. Thus, oils with a high FFA content require a two-step process to be converted into biodiesel: (1) the FFAs are converted to fatty acid methyl esters as a pre-treatment with acid and (2) transesterification with basic catalyst is carried out [4, 25]. In this way, both the acid- and alkaline-catalyzed processes are efficiently used.
Since alcohol and triglycerides are immiscible at room temperature, stirring needs to be carried out to enhance the contact between phases so that a perfect mixing is achieved, avoiding mass transfer limitations and performing the reaction under an intrinsic kinetics. This is not so easy to achieve.
Mass transfer limitation studies have been reported and modeled in detail in a continuous tubular reactor at different reaction conditions [26, 27]. According to the authors, there are two steps that need to be addressed: (1) the reaction mixture passes through the mass transfer-determining region (heterogeneous system where methanol is the dispersed phase and the oil is the continuous phase) to (2) the kinetic-determining region (pseudo-homogeneous system in a single phase).
When using methanol, an emulsion is very quickly formed which is then broken down into two phases, that is, an upper phase constituted by methyl esters and a lower one formed by glycerol. When NaOH is used as catalyst, for example, it dissolves into the alcohol and then triglycerides diffuse through this mixture, and so the reaction is initially mass transfer controlled [4].
Transesterification by supercritical conditions is another reported process to reduce the mass transfer limitations. Several reports have discussed different supercritical conditions to carry out transesterification [28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45] ranging in the case of temperature from 270 to 350°C and pressure from 10 to 45 MPa to ensure only one reacting phase, which eliminate the mass transfer limitations; however, an increase in operation cost is to be expected, while high temperature and pressure could enhance the degradation of fatty acids or FAME, which is known to occur above 250°C. Reaction time has also been reported to vary from 4 to 110 min. The alcohol-to-oil molar ratio is also quite high at these conditions, that is, from 20 to 40. At supercritical conditions, alcohol acts as an acid catalyst [29] and FFA and water present in the feed do not affect the transesterification conversion [46].
To further minimize the mass transfer limitations, reactors that enhance the contact between phases can be used. One of these reactors is the so-called oscillatory baffled reactor (OBR) composed of a tube containing equally spaced orifice plate baffles in which the oscillatory flow forms vortices, improving radial mixing and plug flow behavior [47]. Optimal baffle spacing has been previously calculated, and it was found that mass transfer rate depends on this spacing along with oscillation frequency and amplitude [48]. A better contact between phases is obtained with the use of static mixers consisting of motionless elements inside a pipe or a column to create radial mixing between immiscible liquids [49, 50]. A micro-channel reactor also improves the mass and heat transfer because of its high surface area/volume ratio which enhances the yield of methyl esters (above 90% in short reaction time) as reported elsewhere [51]. Cavitation-based reactors use acoustic energy to collapse cavities that increase local temperature and pressure. Cavitation intensifies the mass transfer rate creating local turbulence and reaching a high yield of FAME at room conditions [52]. Other studies have reported a FAME yield higher than 95% at 35°C, with an ultrasound frequency of 40 kHz at 1200 W of power using 1 wt% of KOH as catalyst, a methanol-to-oil molar ratio of 6:1 mol/mol, for 25 min [53].
As mentioned earlier, if FFA or water content is high, then acid-catalyzed transesterification is preferred. In this case, sulphuric, phosphoric, hydrochloric, or sulphonic acids are the most used catalysts. A comparison among HCl and H2SO4 as catalyst was made elsewhere and the latter behaved better at 2.25 M [54]. Sulphuric acid at 0.87 M was used during transesterification of Hevea br
Alkaline catalysts such as sodium alkoxide are very active in short reaction times at low catalyst amount but anhydrous conditions are required. Instead, KOH and NaOH can be used in typical concentrations from 0.4 to 2% w/w of oil [4]. Earlier studies have reported that potassium carbonate (2–3%) as catalyst yielded a high content of methyl esters with minimal soap formation [56]. Encinar et al. [23] used KOH at 0.7% w/w of oil and obtained around 98% of methyl esters. The higher the catalyst concentration, the higher the reaction rate. However, catalyst in excess will turn the separation of products very difficult by which the amount of catalyst must be optimized.
When the methanol and sodium hydroxide solution are immiscible, mixing is necessary to promote the reaction [57]. The initial agitation improves the contact among phases and reduces the mass transfer limitations. Once reaction advances, methyl esters formed act as solvent for reactants and mixing needs to be continued for promoting the reaction rate. Mixing speed was studied by Encinar et al. [23] varying from 500 to 1100 rpm. The optimal mixing speed was stated at 700 rpm, and only a slight increase on the yield of methyl esters was observed above 95%.
Oil concentration in alcohol is low, particularly when methanol is used once transesterification reaction begins. As oil concentration increases in alcohol, the reaction rate is also increased and triglycerides are converted into diglycerides, which subsequently can react in the alcohol phase rather than being dispersed into the oil phase. As reaction progresses, a glycerol layer is separated. To reduce the mass transfer limitations, the use of nonreactive co-solvents to form a single phase is recommended [58]. Co-solvents such as tetrahydrofuran (THF), dimethyl ether and methyl tert-butyl ether (MTBE) have been reported to improve miscibility among alcohol and oil. Previous reports [58] have stated that THF and MTBE behave as good co-solvents, THF being better than MTBE. Using a ratio of 1.25 vol/vol of methanol and keeping the methanol-to-oil molar ratio in 6:1 mol/mol at 23°C, the yield of methyl esters was 95% at 20 min. Other authors have studied the influence of methanol/co-solvent molar ratio in the range of 1:0.5–1:2 mol/mol and different co-solvents such as acetone, diethyl ether, dibutyl ether, methyl tert-butyl ether, diisopropyl ether and tetrahydrofuran [23]. Diethyl ether was the preferred co-solvent in a methanol/co-solvent molar ratio of 1:1 mol/mol.
Acetone was used as co-solvent at 25 wt% using KOH as catalyst at 1 wt% and 4.5:1 mol/mol as methanol-to-oil molar ratio, and a yield of 98% of methyl esters was obtained at room temperature after 30 min [59]. Acetone at 20 wt% as co-solvent has also been reported elsewhere [60]. Other authors used dichlorobenzene and acetone at 10% (vol/vol) in methanol as co-solvents and reducing the reaction time by 60% [61]. THF was used as co-solvent in a methanol/co-solvent molar ratio of 1:1 mol/mol and 0.5 wt% of catalyst along with a methanol-to-oil molar ratio of 4:1 mol/mol, and a yield of 98% of methyl esters was obtained after 10 min at 40°C and 200 rpm [62].
When selecting a suitable co-solvent, one has to take into account that at the end of reaction, it will be removed and if possible it will be reused. Thus, its boiling point needs to be maintained low.
Temperature influences on kinetics and equilibrium of reaction. It diminishes the viscosity of products and improves the mass transfer. At high temperature values, saponification is enhanced, lowering the yield of methyl esters. If methanol is used, the reaction temperature is commonly set at a value lower than its boiling point [63]. The effect of temperature on FAME yield has been studied from 20 to 40°C. If co-solvent is used, then temperature will be lower than its boiling point to avoid vaporization. The authors found that the yield of methyl esters at 30°C was optimal [23]. Some authors have reported temperature values ranging from 50 to 60°C [64]. The use of novel reactors as mentioned earlier is intended to reduce the reaction temperature at near room temperature.
Stoichiometrically, three moles of methanol are required by one mole of triglycerides. Since transesterification is a reversible reaction, the addition of methanol in excess displaces the equilibrium toward products in such a way that triglycerides will be converted into methyl esters, by which commonly methanol-to-triglycerides molar ratio is set to 6:1 mol/mol or higher. Nevertheless, methanol in excess increases the cost of biodiesel production, and therefore its recovery is one of the options used to improve the economy of the process. Some reports have studied the effect of methanol-to-oil molar ratio on FAME yield and have found an increase in the yield of methyl esters from 86 to 95% when increasing the molar ratio from 6:1 to 10:1 mol/mol [65]. When using waste cooking oil as feedstock, a higher methanol-to-oil molar ratio of 16:1 mol/mol decreased the yield of FAME, probably because of a reduced catalyst concentration in the reacting mixture. Thus, the optimal molar ratio was 10:1 mol/mol [65]. In other cases, the optimal alcohol-to-oil molar ratio has been reported to be 9:1 mol/mol that yielded ~94% of methyl esters [23]. This molar ratio is also reported in previous reports [66]; however, depending on the type and quality of the oil, the methanol-to-oil molar ratio must be optimized in each case as in catalyst concentration.
The conversion of triglycerides increases as the reaction time gets longer. In the case of alkaline catalysts, the reaction time is lower than 90 min to reach a maximum yield of methyl esters. As the alcohol and oil mixing starts, their immiscibility slows down the reaction within the first minutes; however, when reactants are well mixed, the reaction proceeds fast [63]. When acid catalysts are used, the reaction time is commonly increased up to several hours as reported before where sulphuric acid in the presence of soybean oil and methanol took 50 h to reach almost 100% of yield of methyl esters [3]. As in the case of methanol-to-oil molar ratio and temperature, the optimal values need to be found for each case depending on the catalyst type and the oil to be used.
The transesterification of triglycerides by heterogeneous catalysis is an alternative way to produce a biofuel that could help to reduce CO2 emissions at reduced production costs, becoming thus competitive with petroleum-based diesel fuel [67, 68, 69]. There are still many areas of opportunity to improve the economy of the process. Heterogeneous transesterification has been shown to reduce the separation operations, the generation of waste and the use of large quantities of water [70]. One of the most difficult challenges is to find a catalyst with comparable activity to that of homogeneous catalysis, that is, at the same pressure and temperature and in which leaching is not present [71].
The kinetics of the transesterification reaction of oils and fats by heterogeneous catalysis is not so well understood as it is for homogeneous catalysis [72]. Most research works on heterogeneous catalysis have been focused on the synthesis and application of catalysts, and only a few deal with kinetic modeling. Among these, the efforts have been put on the use of small solid particles to obtain reaction conditions under an intrinsic kinetics and in which the phenomena of both intraparticle and external mass transfer are negligible.
Thus, most heterogeneous vegetable oil transesterifications have found to follow a pseudo-first-order rate law. For example, Kaur and Ali [73], in their study with 15-Zr/CaO-700 catalyzed methanolysis and ethanolysis of Jatropha curcas L. oil, found that both reactions followed a pseudo-first-order rate law. The negligibility of the transport influences was demonstrated by the Koros-Nowak test. Lukić et al. [74] also found at optimal conditions for the transesterification of sunflower oil a first-order reversible rate law using a ZnO-alumina/silica-supported catalyst and by evaluating both the effects of the calcination temperature and the effects of various supports. A number of kinetic modeling works of heterogeneous transesterification are presented in Table 1.
Oil source and catalyst | Reaction conditions | Kinetic model: rate constant ( | Ref. |
---|---|---|---|
Soybean oil Catalyst: Amberlyst A26-OH basic ion-exchange resin | Molar ratio 10:1, methanol:oil with 5% oleic acid and without acid Agitation speed: 550 rpm Temperature: 50°C | Kinetic model: Eley-Rideal | [72] |
Catalyst: Zr/CaO | Agitation speed: 500 rpm Methanolysis Molar ratio 15:1 methanol:oil Temperature: 65°C Ethanolysis Molar ratio 21:1 ethanol:oil Temperature: 75° C | Kinetic model: Pseudo-first order | [73] |
Sunflower oil Catalyst: ZnO/alumina-silica, 2 wt % | Molar ratio 30:1 methanol:oil Temperature: 200°C Pressure: 37 bar Reaction time: 4 h Catalyst ZnO Al/Si ratio 3/1 Calcination 600 °C, 12 h Catalyst ZnO Al/Si ratio 3/1 Calcination 300 °C, 12 h Catalyst ZnO Al/Si ratio 1/0 Calcination 600°C, 12 h Catalyst ZnO Al/Si ratio 1/0 Calcination 300 °C, 12 h | Kinetic model: First-order, | [74] |
Sunflower oil CaO, 1 wt % Ca(OH)2, 1 wt % CaO·ZnO, 2wt % | Temperature: 60 °C Agitation speed: 900 rpm Molar ratio 6:1, methanol:oil Agitation speed: 900 rpm Molar ratio 6:1, methanol:oil Agitation speed: 300 rpm Molar ratio 10:1, methanol:oil | Kinetic model: Miladinovic model, | [75] |
Sunflower oil Catalyst: Ca(OH)2, 1-10 wt % based on oil weight | Molar ratio 6:1 methanol:oil Reaction time: 5 h Temperature: 60 °C Agitation speed: 900 rpm | Kinetic model: Pseudo-first order. Where | [77] |
Sunflower oil Catalyst: CaO, 1, 2.5 and 10 wt % | Molar ratio 6:1 methanol:oil Temperature: 60 °C Agitation speed: 900 rpm | Kinetic model: Pseudo-first order reaction | [78] |
Canola oil Catalyst: Mg-Co-Al-La HDL, 2 wt% | Molar ratio 16:1 ethanol: oil Reaction time: 5 h Temperature: 413-473 K | Kinetic model: First order | [79] |
Sunflower and waste cooking oil Catalyst: CaO·ZnO 2 wt % | Molar ratio 10:1 methanol:oil Agitation speed: 300 rpm Temperatures range: 60-96 °C With sunflower oil Temperatures: 60 °C 70 °C 84 °C 96 °C With waste cooking oil 60 °C 84 °C 96 °C | Kinetic model: Pseudo-first order Constant ( ( ( ( ( (kmt,TG)AVE = 0.493 min−1 ( | [80] |
Waste cooking oil Catalysts: Heteropoly acid, 10 wt % | Molar ratio 70:1 methanol:oil Agitation speed: 300 rpm Reaction time: 14 h Temperatures: 50 °C 55 °C 60 °C 65 °C 70 °C | Kinetic model: First order | [81] |
Sunflower oil Catalyst: CaO, 1 wt % | Molar ratio 6:1 methanol:oil Agitation speed: 200 rpm Pressure: 1-15 bars Temperature: 60-120 °C Reaction time: 1.5 h Reaction time: 2.5 h Reaction time: 3.5 h Reaction time: 4.5 h Reaction time: 5.5 h | Kinetic model: Pseudo-first order with significant diffusion restrictions at 80 °C | [9] |
A review of kinetic models and reaction conditions of heterogeneous transesterification of vegetable oils.
The heterogeneous catalysis of vegetable oils takes place in a number of steps and in a three-phase system consisting of a solid (heterogeneous catalyst) and two immiscible liquid phases (oil and alcohol, usually methanol or ethanol). To determine the rate-limiting step, a comparison of rates of the different elementary steps should be performed. This has been tried by several researchers by using either the Eley-Rideal (ER) or the Langmuir-Hinshelwood-Hougen-Watson (LHHW) methods.
Jamal et al. [72] have used both ER and LHHW in the transesterification of soybean oil on an Amberlyst A26-OH basic ion-exchange resin and in the presence and absence of free fatty acids. They proposed a four-step mechanism: (1) methanol adsorption by ion exchange on basic resin surface; (2) fatty acid (oleic acid) adsorption by ion exchange on basic resin surface; (3) hydrolysis of tri-, di- and monoglycerides from soybean oil; and (4) transesterification of glycerides (tri-, di- and mono-) with basic resin surface-bound methoxide. By considering the first step as the rate-limiting step, they showed that the ER model describes better the surface interactions occurring on the resin.
Some other authors have developed kinetic models based on first-order rate law. The following three cases show how sunflower methanolysis kinetics has been modeled within two stages, the first one being the initial TG mass transfer limitations and the second one the chemically controlled region.
Tasić et al. [75] have developed a reaction model for the methanolysis of sunflower oil on three calcium-based catalysts: CaO, Ca(OH)2 and CaO·ZnO, by using the chemical kinetics reported by Miladinović et al. [76], in which it is assumed that the methoxide ions are first adsorbed on the active centers and then they react with the liquid phase TG that are close to the active centers. The mass transfer limitations of the methanol adsorption were found to be negligible. Miladinović et al. [76] also used a first-order reaction rate with respect to TG and FAMEs, respectively. Tasić et al. [75] also showed that the TG mass transfer limitation depends on the methanol-to-oil dispersion. When it is not fine enough, the available active surface is small. To reduce that effect, that is, to increase the TG-methanol miscibility, a co-solvent can be added. However, these authors found that FAME can act as a co-solvent, and therefore as it is formed, the interfacial area gets larger, and hence the transfer limitations become smaller.
Stamenković et al. [77], studied the kinetics of the methanolysis of sunflower seed oil at 60°C, using a methanol-to-oil molar ratio of 6:1 mol/mol and different amounts of Ca(OH)2 catalyst. They proposed a pseudo-first-order reaction kinetic model and related the TG mass transfer limitations to the limited available surface area that resulted from the high adsorbed methanol concentration in the first stage of the reaction. Mass transfer limitations were also important when small amounts of catalyst were used (1–2.5 wt%, oil based). When the catalyst was used in amounts greater than 10 wt%, the significant agglomeration of catalyst particles occasioned the limitation of TG mass transfer.
Practically, the entire active surface of the porous granules is internal, and the reaction that takes place inside the pellet consumes reactants and induces internal gradients of concentration and temperature which may be of sufficient magnitude to cause a significant variation of the reaction rate. Thus, the size of the particles of the catalyst affects the mass transfer at both intraparticle and at the interface. A suitable size of particle can be found experimentally so that a reaction rate and the final conversion degree do not depend on it, which is fundamental in kinetic studies to obtain the intrinsic kinetics.
There are few studies on particle size in the production of biodiesel by heterogeneous catalysis. Veljković et al. [78] in their study on sunflower methanolysis with CaO showed that the intraparticle diffusion of reactants from the surface to the active sites was the rate-controlling step; however, when they used catalyst particles in between 3 and 15 μm, they found no influence of the average particle size on the reaction rate and the final conversion, which indicated that the resistance due to intraparticle mass transfer was negligible in this size range.
Li et al. [79] in their study on ethanolysis of canola oil using a lactate dehydrogenase (LDH) oxide catalyst (Mg2CoAl) compared the reaction rates for two different particle sizes, one being greater than 1 mm and another being less than 100 μm, both at the same conditions. In both cases, a reduction in the conversion was found, indicating that there is a resistance to internal mass transfer and therefore an intraparticle diffusion control. However, for both cases, the rates were very similar in between 30 and 90 min, but with a delay of about 15 min for the larger particles. They concluded that the conversion rate was kinetically controlled rather than intraparticle diffusion.
The stirring speed plays an important role in the evaluation of the limitations of external mass transfer, so to corroborate if there are external mass transfer limitations from the reactants to the particle surface, a study of the reaction rate is usually carried out at different agitation speeds. Veljković et al. [78] carried out studies at agitation speeds of 700 and 900 rpm for a methanolysis reaction with 1 wt% catalyst and speeds of 900–1250 rpm with a 10 wt% catalyst, and by using the correlation of Dossin et al. [18], they found that the minimum stirring speed to carry out a perfect mixture and a complete suspension of catalyst particles was 430 rpm for the former and 740 rpm for the latter. They found that agitation speeds of 1250 rpm introduced air inside the reactant mixture. The experimental conditions and values of the kinetic constants are summarized in Table 1 [78].
The effect of temperature on the reaction rate plays also a very important role since the rate constants are temperature-dependent. The temperature can influence transport phenomena in heterogeneous catalysis; Lukić et al. [80], for example, conducted the transesterification of sunflower and waste cooking oil using methanol at temperatures in a range between 60 and 96°C. As catalyst, they used CaOZnO with a methanol-to-oil molar ratio of 10:1 mol/mol. They showed that at relatively low temperatures of 60–70°C and at the start of the reaction for the production of esters, there is a resistance to the mass transfer, but with an increase in the production of methyl esters, the resistance to mass transfer reduced, so that the initial TG mass transfer limits the rate process, and eventually as biodiesel concentration increases, the chemical reaction is the rate-limiting step. For temperatures higher than 84 and 96°C, the resistance to mass transfer is almost negligible, and thus the conversion rate is controlled by the chemical reaction. The reaction rate was expressed by a pseudo-first-order model and corresponding values of the mass transfer coefficients.
In another study [81], a heteropoly acid catalyst was used to carry out the transesterification reaction of waste cooking oil with methanol temperatures in the range of 50–70°C to determine how temperature influences the conversion of TG. The conversion degree had a considerable increase when the temperature increased from 50 to 65°C, in the range of 40% (from 20 to 60%) at 50°C and 57.6% (from 31 to 88.6%) at 65°C. However, above 65°C, the conversion rate decreased, which was claimed to be due to the chemical reactions that occur during the cooking process, as these reactions can generate undesirable components such as free fatty acids that cause a decrease in the conversion of TG and therefore the production of biodiesel.
Methanol is mostly used for transesterification of vegetable oils, mainly to avoid the formation of a stable emulsion between biodiesel and glycerol. In practice, it is better to perform a study at different molar ratios for each specific case of conditions and catalysts. Vujicic et al. [9], for example, used CaO as catalyst to transesterify sunflower oil. An excess of alcohol was observed to influence the reaction kinetics, and the overall reaction rate was found to follow strictly a fourth-order kinetics, since each TG molecule should be converted into glycerol by consecutive reactions, first becoming diglyceride, then monoglyceride and finally glycerol, but when carrying out the reaction with a large alcohol excess, the kinetics was observed to follow a pseudo-first order (Table 1).
Reaction time is very significant in the production of biodiesel by heterogeneous catalysis, since to obtain the same yields as those in homogeneous catalysis sometimes need up to more than five times the time that is carried by homogeneous catalysis. In the abovementioned work carried out by Vujicic et al. [9], the achieved activities at reaction temperatures of 80 and 100°C were significantly affected by the reaction run, and high steady-state conversions were reached after 5.5 and 2.5 h, respectively.
The economic evaluation of biodiesel production is based on general mass and energy balances that can be obtained from process simulation [82]. Among the most common process simulators used for the simulation of biodiesel production are Aspen Plus®, Aspen HYSIS, PRO/II, SuperPro Designer, and VMGsim. These programs can be used to design and optimize a large-scale biodiesel production. Table 2 shows relevant data for different simulation studies. Complimentary numbers can be found elsewhere [83, 84, 85].
Materials | Reactor models | Operation mode | Thermody-namic model | Program | Production size Tonnes/year | Refe-rence | ||
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Feedstock (Model compound) | Catalyst | Transesterification | Esterification | |||||
Rapeseed (triolein) | MgO | Eley-Rideal Pseudo second-order reversible | none | Bach and continuous (slurry) | UNIFAC | Aspen Plus | 100000 | [94] |
Rapeseed (triolein) | KOH/Enzyme | Yield model (96 %) | None | Continuous (CSTR) | Dortmund UNIFAC | Aspen Plus | 8000 | [84] |
Seven kinds of vegetable oils | NaOH | Second order reversible | None | Batch | Dortmund UNIFAC | Aspen Plus | 9125 | [83] |
Cottonseed (pseudo-components) | NaOH | Second order irreversible | None | Continuous/Batch | Dortmund UNIFAC | Aspen HYSYS | 562 (feed) | [95] |
Soybean (triolein) | Nb2O5 | Pseudo homogeneous (hydrolysis) reversible | Pseudo homogeneous | Continuous (Pack bed reactor/ RDC) | Dortmund UNIFAC | Non-commercial computational code | 2134 | [96] |
Soybean (triolein) | Mg(OCH3)2 (heterogeneous) | Second order reversible | None | Continuous (CSTR/RD) | Dortmund UNIFAC | Aspen Plus | 7542 | [97] |
Palm (triolein) | KOH or NaOH | Second-order reversible | Second-order reversible | Continuous (CSTR) | UNIFAC and NRTL | Aspen Plus | 100000 | [98] |
Soybean (trilinolein) | NaOCH3 | Conversion reactor (99%) | None | Continuous | NRTL UNIQUAC | Aspen Plus | 150000 | [99] |
Jatropha (triolein) | NaOH | Conversion rector (98.86%) | None | Continuous (CSTR) | NRTL UNIFAC | Aspen HYSYS | 8000 | [100] |
Waste cooking oil | Tungsten on alumina supported (WAI) | Conversion reactor (96.54%) | Conversion reactor (92.34%) | Membrane reactor | NRTL | Aspen HYSYS | N/A | [101] |
Key features of some simulation studies for biodiesel production.
The typical process simulation procedure involves definition of the components, selection of the thermodynamic model, property estimation, drawing of the flowsheet, definition of chemistry and kinetic models, and the input of units and operation conditions.
Most simulators do not contain all the components present in the transesterification reaction, so that their properties cannot be estimated. Thus, triolein (C57H104O6) is regularly used as a model compound of TG, mainly because it accounts for 40–75 wt% in most used oils for biodiesel production, such as olive, canola, palm and jatropha oils [83, 86], and hence biodiesel is represented by methyl oleate (C19H36O2). When the oil contains FFA that requires an esterification pre-treatment process, oleic acid (C18H34O2) is used as a model compound.
The most recent version of Aspen Plus® (ver. 10) includes most of the TG and methyl esters present in the transesterification reaction, including (tri)ricinoleine, which is the main component in castor oil. The properties of these components are estimated in the simulators. However, some important properties estimated for these components, for example, normal boiling points and vapor pressures, are somehow inconsistent with experimental data and databases, and therefore some researchers choose to update their values from either experimental data [87, 88], contribution methods [89] or from properties databanks such as NIST [83].
The Non-Random Two Liquid (NRTL) or the Universal Quasi Chemical (UNIQUAC) models are the preferred thermodynamic models, mainly because of the presence of highly polar compounds, such as methanol and glycerol. In Aspen Plus, however, the binary NRTL coefficients usually need to be estimated, which is commonly carried out by the UNIFAC LLE model for liquid-liquid equilibrium and Peng-Robinson or SRK equations of state for vapor. The performance of NRTL has been shown to be better than UNIQUAC [90]. These models present different characteristics that make them complimentary [91], and the use of both (UNIQUAC as referenced model) can achieve more reliable simulations.
The Dortmund UNIFAC excess free energy model has also been used for the estimation of activity coefficients [84], as it has been found to provide good fit between estimated and measured methanol-biodiesel and methanol-glycerol vapor-liquid equilibrium data [92]. In this study performed by Kuramochi et al. [92], the Dortmund-UNIFAC was found to represent the best way to model the liquid-vapor equilibrium in the biodiesel process, while UNIFAC-LLE was found to be the best method to model the liquid–liquid equilibrium with methanol, methyl oleate and glycerin mixture and methanol water system. The COSMO-SAC model, included in Aspen Plus, has also been used for VLE calculations in the esterification reactor [93]. The advantages of this method compared to NRTL are that its predictions are based on quantum chemistry, and the parameters required for its use are of molecular and electronic nature, and therefore they will not be affected by temperature changes along the process [93].
The selection of a kinetic model for both the transesterification and esterification reactions is very important for determining the product yield and performance of the equipment. Despite the multiple kinetic models found in the study, as shown in Section 3, a number of simulation studies do not include a detailed kinetic model to simulate the reactors. Instead, the simulation is performed by using a stoichiometric or an equilibrium reactor and using a specific value for the conversion or yield. Different studies for base-catalyzed reaction use a conversion value in between 95 and 99%. Some authors [100] argue that the various kinetics and mechanisms are not clear enough to design methods to follow and hence they prefer to simulate the reactors as conversion reactors.
Similarly, since many kinetic models for transesterification reaction have been obtained for the entire mixture of TG and FFA, the use of triolein in the simulation does not entirely represent the observed kinetic behavior in the reactor. In addition, most kinetic models found in the study have only been derived for one TG as a pseudocomponent. A detailed kinetic, and hence a more realistic simulation, should include triolein, tripalmitin, trilinolein and tristearin, as they account for more than 90 wt% of jatropha, palm, soybean, rapeseed and sunflower oils [84, 102].
Lee et al. [103] have developed a kinetic model based on three TGs, that is, for each component, kinetics parameters have been estimated. This model was used by Garcia et al. [90], who simulated the biodiesel production by considering a feedstock containing four TGs.
Most simulation studies found in literature have been performed at a large-scale process; however, there seems to be a lack of data about industrial performances that are not totally realistic. A more comprehensive and close comparison between real plant operation and process simulation could help to reduce this gap.
Optimization is one of the most quantitative tools in the industrial decision-making process [91]. The purpose of biodiesel production optimization is to find the value of the variables involved in the process that maximizes the profit, minimizes the cost of the process or maximizes the yield of biodiesel, so that the process becomes competitive in the fuel market. The optimization of biodiesel process should start from the optimization of the reaction conditions at a laboratory scale. This is usually performed by running a design of experiments and optimizing the conditions by the use of the surface response methodology (SRM). The model can later be validated at bench or pilot plant scale. Thus, the model can be used in the simulation process as a yield model.
The use of a simulator can also be useful to add different factors that are not present at a laboratory scale, as well as to optimize the operation of the different equipment in the industrial plants by performing a sensitivity analysis. Several optimization studies have been reported in literature, mainly to perform an economic analysis [84, 88], to determine the optimal conditions to maximize the conversion of vegetable oils [104], to perform sensitivity analyst of design parameters and operating conditions to optimize the operation of each step [96], to study the excess methanol recovery in continuous production [105] and to evaluate new process intensification technologies [106], among others.
The goal in the development of heterogeneous catalysis seems to be the development of catalysts with high activity at low temperatures and pressures, being selective, being stable and should not be deactivated by water or leached. The kinetic modeling of the transesterification reaction should include more TG components; this, however, requires a more detailed characterization of both the feedstock and reaction products. These detailed kinetic models should also allow the simulation of TG mixtures or feedstocks such as waste cooking oil. By doing so, a more realistic simulation and optimization of the process could be obtained. As chemical process simulators have been incorporating most of the components in the biodiesel process, it is expected that the estimation of the properties becomes more reliable in these programs and provide more realistic simulated results. There is, however, a need for information on industrial data for the different biodiesel technologies, so that the biodiesel simulation studies can be compared and be validated with industrial data.
Rogelio Sotelo-Boyás and Fernando Trejo-Zárraga gratefully acknowledge the support of the Instituto Politécnico Nacional of Mexico for the development of institutional projects on biofuels research through SIP 20090379-20181723, whose results have contributed to write this chapter. Juan C. Chavarría acknowledges the support of the FSE-2014-01-254667 project for the realization of renewable energy studies, whose results have provided useful information for this work.
Pig is one of the oldest domesticated animals and majority of the breeds are known to have descended from the Eurasian Wild Boar (
The origins of African domestic pig breeds are obscured and highly controversial due to lack of sufficient archaeological and genetic evidence to establish sound hypotheses about how, when and where they were founded. Although
The wild pigs of Africa are the warthog,
The history of pigs in sub-Saharan Africa has been blurred by the importation of very large numbers of European pig breeds into all parts of the continent through a number of ways ranging from undocumented subsistence strategies or colonial agricultural development projects [6]. Thus, the genetic heritage of today’s African pig populations is extremely mixed. Secondly, the history and distribution of pigs in Africa have been substantially affected by the growth and domination of many parts of Africa by Islam. This has led to the disappearance of pigs from a wide swathe of Africa in historic times [6].
\nThe domestic pig, based on historical records and scientific evidence, is thought to have originated from the Eurasian wild boar (
In West Africa, the indigenous pigs are known by several names such as the West African dwarf pig (Nigeria), Ashanti dwarf pig (Ghana), or the bush pig (Togo). The Ashanti Black Forest Dwarf pig of Ghana, commonly called the Ashanti Dwarf Pig for instance, has been shown to have both a European and Asian ancestry, with the pigs differing from the north to the south of the country [18]. Phenotypically, these pigs have been described as having a concave head profile, black coat colour, erect ears that sometimes project backwards and a short cylindrical snout. They are hardy, able to survive under poor management, mostly scavenging for their food and can digest high fibrous matter; they are well adapted to resist heat stroke as well as other harsh environmental conditions and are considered to be less susceptible to many local diseases and parasites; they also have good mothering ability. Average body weight of adult pig is 60 kg, bearing 5–7 piglets [18]. The Nigerian indigenous pig (NIP) is described in a similar manner to the Ghanaian local pig [19, 20]. Eastern African and Southern Africa indigenous pigs have also been described [21, 22].\n
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The Local African Pig Breed of Burkina Faso. Copied from: au-ibar.org\n\n
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The Local African Pig Breed of Burkina Faso. Copied from: au-ibar.org\n\n
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Nigerian Local Pig breed. (Pictures courtesy of Adedeji JA).\n
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Nigerian Local Pig breed on a free range Management system. (Pictures courtesy of Adedeji JA).
\nThe introduction of pigs into Southern Africa is thought to have taken place later than for other regions of the African continent, and this might have occurred through the processes of barter, warfare and migration as there is little historical information on the Southern Africa indigenous pig populations [22]. There are two recognized indigenous pig breed populations in Southern Africa namely: “Kolbroek” and “Windsnyer”. There is however a third group of local pigs referred to as the South African hard-footed pigs which are free ranging scavengers and converters of unutilized household and farm waste [22].\n
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The South African “Kolbroek” breed. Copied from: Farmersweekly.co.za. Photo: \n
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The South African “Windsyner” Pig Breed: Copied from: livestockoftheworld.com\n
\nWhile the Eastern African indigenous pigs are sturdy, dark to light coloured skin, black or white long feet, long narrow snout and a well-developed mane, the Kolbroek pigs are short, with prickled ears, short snout and a squashed face. They are dark black or brown in colour, often striped at birth; docile nature with high disease resistance, and thrives well on a high fibre diet. Windsnyer pigs on the other hand are smaller with bristles that form a distinct mane. The coat colour varies from black, reddish-brown, black and white to spotted. They are narrow-bodied, long-nosed and razor-backed, and are able to survive periods of food scarcity. Other pig breeds described by Swart are the Namibian and the Mozambican pig breeds. The Namibian indigenous pigs are found in the northern communal areas of Namibia, and their origin is unsure but they are thought to be brought from areas around the Mediterranean Sea. They are relatively long, lean-bodied pigs with long snout, with coat colour ranging from mottled brown to black and white. They are well adapted to harsh environments with low maintenance requirements, fertile, and are excellent lard producers [22] The Botswanan indigenous pig breed is found mostly in the southern part of the country called the Tswana. The pig is predominantly black in colour, and well adapted for the climatic conditions of Botswana [17].
\nIndigenous pig breeds are unique to the geographic locations where they are found and possess genetic characteristics which may provide future breeds with production traits that are advantageous for survival [23]. These qualities include their adaptation to harsh environments, resistance to disease and adaptation to harsh production system in developing countries [24]. These advantages are quickly being lost due to the inability to compete with the fast-growing commercial exotic breeds and the resultant indiscriminate cross-breeding of the local with the exotic species which has consequently narrowed the gene pool of the local breeds [25]. Poverty, lack of information on the attributes of local pigs and ill-defined government policies and programmes have been adduced as some of the reasons why local pig breeds are being lost very rapidly [26]. There is therefore the severe danger of losing the local pig biodiversity because of the race to satisfy high production capacity of pigs’ i.e. fast growth and large litter size [23]. Thus, a number of researchers have reported a steady waning of the indigenous pig population in Africa, with some recommending the conservation of the germplasm of valuable genetic resource [24, 27, 28, 29]. In Nigerian, the local pigs (Figure 2b) have been replaced with exotic breeds such as Large White, Landrace, Hampshire and Duroc because of the afore-mentioned advantages [24]. Similarly, the commercial pig industry in Southern Africa has been taken over by exotic pig breeds which were imported to enhance the industry and meet the demand of the market system [22]. Predominant exotic pig breeds in South Africa include the South African Landrace, the Large White, the Duroc and the Pietrain [22]. The Eastern African commercial pig industry as seen in Ugandan, has also been replaced with exotic pig breeds such as Camborough, Landrace and Large White along with their crosses [30]. However, many small producers acknowledge the value of local pigs and they have resolved to conserve them [31]. Thus, it is necessary to work on pig conservation and the development of the family production system that will conserve the genetic potential of African local or indigenous breeds [28, 32].
\nThe indigenous pigs are reservoirs of genes and sources of heterosis, but these variable and valuable traits suited for our particular ecological zone are constantly being threatened by genetic erosion, leading to a progressive loss of genetic diversity [33]. These phenomena are actually related to the implementation of indiscriminate and unsustainable crossbreeding programs which influence the structure and dynamics of the pig populations in Africa. It is therefore imperative to draw attention to the disappearance of the indigenous African pig breeds [6, 16, 25]. However, in view of the diverse roles indigenous pig plays, it entails that there is need for an increased knowledge of the indigenous pig, their characterization and conservation to support sustainable agricultural development and maintain local breeds of pigs which have variable traits suited to a particular ecological zone [34].
\nIn most African countries, the agricultural sector still provides a relatively large share of GDP [35]. Livestock production can contribute to poverty reduction in various ways including increase in food supply, source of income and a means for capital accumulation, employment opportunities and supply inputs and services for crop production. Livestock also represents an important factor for social integration [36]. Pig production has the potential of improving the real per capita income of Sub-Saharan African reported as $688 in 2010 compared $1717 of the rest of the world. Over the past 30 years, GDP growth per capita in SSA has an average of 0.16 percent per year [35]. However, pig production is an important means of livelihood in many parts of Africa, particularly in rural communities [37, 38, 39]. It is increasingly perceived as a source of income generation and poverty reduction.
\nDespite the decline in the use of indigenous breeds and the shift towards more improved, exotic breeds in most part of Africa including South Africa over the years, indigenous pigs in African remain a source of food and income for people farming in rural areas and subsistence-orientated production systems [37, 40, 41]. These indigenous pigs and their crosses are noted for their high potential for subsistence-oriented production systems [37]. Thus, many small-scale rural farmers in various parts of South Africa still keep indigenous pigs [37, 42, 43] probably due to their ability to remain productive even when living in poor sanitary conditions and fed low quality feed. This low input requirement is helpful in low-income rural communities [44].
\nIn 1998, Nigeria was estimated to have 4.86 million pigs, followed by Uganda (1.55 million), South Africa (1.54 million), Cameroon (1.35 million), and the Democratic Republic of Congo (1 million) as the top five pig populations in Africa [45]. This has grown in the last two decades, as presently Nigeria is estimated to have over 7.5 million pigs, Malawi 6.3 million, Uganda 2.7 million, Angola 2.6 million, Burkina Faso 2.5 million, Madagascar 1.7 million and Mozambique 1.6 [46]. Presently, Africa is estimated to have over 40 million pigs [46]. In many African countries, particularly tropic regions, most of the pigs is kept by smallholders in rural area (51). Uganda, for instance has 2.3 million pigs being kept by one million households for consumption and translates into cash in times of emergencies [47]. Pig enterprise has been reported to be a profitable enterprise that should be encouraged and embarked upon [48]. More often than not, pig farming is combined with crop farming. A pig possesses a large caecum, and its manure is rich in nutrients which make it good source of organic fertilizers for crops and can also be recycled into livestock feeds. Besides having main production systems like extensive, semi-intensive and intensive system; there are also subsistence-oriented households and market-oriented households which look to pig production for different reasons [37]. Pigs also can contribute positively to the empowerment of women and enhance their equal participation in local markets [49].
\nIn recent times, commercial pig production under intensive system of management is becoming more popular because of the favourable return on investments. Owing to increasing human population and demand of meat source, pork production has scaled up with a developing pig value chain which gradually established over time. This chain includes several stakeholders like input suppliers, middlemen, traders, transporters and butchers who play vital roles in the economy of communities, regions and countries where pig production is thriving. Farmers are also able to enter at different phases of the production chain as breeders (selling piglets), pig fatteners (selling live or slaughtered pigs), or both. The feed supply input is exemplified in local feed mill production for pig feed as seen in Uganda [49].
\nPigs are largely slaughtered for home consumption, during funerals and cultural ceremonies [50] Pig production has been reported to be a dependable source of income for livelihood activities like school fees, income and consumption in Uganda [51, 52] medical bills, fertilizer purchase, and debt recovery. In Congo pig farming was for cash [53], in Ghana it was for consumption, savings, wealth/status, breeding and manure [54], while in South Africa pigs were seen as a substitute for savings [55]. In Cameroun and Congo, it was considered as an emergency fund [44, 53], and sales were done during festivities, and when demand was high. In Nigeria it was kept for income and consumption [56]. In Namibia, and Kenya pig keeping is for income and consumption [57] while it was for cash in Botswana [58] and South Africa [59].
\nThe impact of diseases in pigs can also result in huge economic consequences for farmers’ livelihoods and income generation both at household level, community level and regional level. The impact of diseases results in losses of income to the farmers, and possible closure of market. No country is yet to export pork meat in Africa, however reasonable trade is known to occur within regions. Such examples can be seen between Nigeria and Benin in West Africa [39] and between Uganda and Kenya in East Africa [60].
\nPig production system across Africa is dominated by small-holder pig owners mostly in rural areas with poor farm infrastructure and limited biosecurity [61, 62, 63]. The production system in Africa is faced by many constraints, with marketing being a limiting factor to the expansion of pig populations in Africa. Pig marketing in Africa is mainly dominated by sales of live pigs through auctions by farmer, traders or middlemen [40, 56]. Sales of these live pigs involved movement to various destination evading ante-mortem inspections and congregation at the point of sale, thus leading to spread of infectious diseases [40]. These small holders pig farmers do not have access to high value markets and the market they patronize are generally exploitative, collusive and economically inefficient [64]. High value markets are only limited to big commercial pig farms that supplies pork to supermarkets and companies [61], while the main channels of marketing pigs in many African countries are through auctions at live pig markets, slaughtering facilities and direct sales to individuals [56, 65, 66]. These trade/marketing practices also have huge concomitant influence on the breeding programs as better price value are gotten for improved exotic breed in comparison to indigenous breeds of pigs.
\nAnother marketing-associated limiting factor to small holder’s pig farmers is having good value for their animals, because pigs are considered more or less as a single-product animal in most pig producing areas in Africa unlike cattle, sheep and goats [64]. This is because pork is the only end product of the production system, as other by-products like lard, hair etc. are not utilized.
\nLive pig markets are generally categorized into three: primary/collection markets; secondary/regrouping markets and terminal market, with many actors (farmers, traders, assemblers and brokers) within each market performing different functions or roles along the marketing chain [56]. The practices in some countries where pigs sold passes through two or more middlemen before eventually reaching the market or consumer makes such pig to become highly expensive to the consumer [56, 67]. While some farmers may sell directly to other farmers without using the middlemen, others farmers in several African countries sells their pigs in the local community or neighbourhood at low prices [17, 50, 53, 58, 59, 65, 67, 68], as most of the famers especially in South Africa could not gain entrée into sustainable markets due to lack of information, knowledge and skills on the selling price of pig [65, 68]. In some African countries the middle men purchase the pigs from farmers at poor prices and sell to traders; at pig slaughter houses or pork serving centres’ in order to escape taxes at the slaughter slab [51], while in Botswana, the main pig market for pig farmers are the local meat processors and butcheries [69, 70] and the common marketing chain involves “farm–abattoir–butchery or processing plants and the end products were distributed to shopping malls [61]. In Nigeria, sales are either in cash or credit depending on relationship between the buyers and traders, as well as on size, health status, body score, season and festivals at the time of sales [56].
\nIt has been reported that a solid relationship existed between auctions and prevailing market price of pigs as high pig populations at auctions show that the market prices are good [65]. Others have however observed that pig and pork were generally more expensive in dry season (September to April) when the Fulani herdsmen migrate to the south (causing a temporal shortage of beef) and also due to Christmas and Easter festivities in December and April respectively [56]. Therefore, in order to improve price and access to market, there is need to investing in market infrastructure, organizing pig farmers into cooperative groups, and develop other products from pigs as part of value chain addition. Furthermore, government policies aimed at improving prices of pigs/pork and access to high value market for small holder’s farmers particularly farmers rearing indigenous pigs should be put in place.
\nPig wholesaling and retailing is assumed to be oligopolistic leading to higher marketing margin for the traders through incorporation of gain market power and control of market price paid by consumers since only a few handles the bulk of the trade and majority of the farmers are also traders operating in the same market with majority of them controlling both production and marketing decisions [56].
\nSecondly, standardization/grading of animals and adequate price information are absent in the markets and creates problem/difficult for the traders in many African countries [43, 52, 56, 59, 65, 67, 68, 71]. In addition, there are lack of price harmonization among the farmers since no templates exists to standardize transactions even on live pig-weight estimate [68], which in turn forced pig farmers to consent to any amount middle men offered them [67]. This has resulted in farmers having an irregular income because they regularly sell their pigs at poor prices as observed in Kenya, Tanzania and South Africa [41, 65, 67, 71, 72].
\nThirdly, marketing of pigs and their products in many African countries is poor and not organized and is generally accompanied by seasonal variations in market price due to poor demand [38, 40, 41, 51, 52, 56, 59, 61, 65, 67, 68, 70, 73, 74, 75, 76, 77, 78, 79].
\nFourthly, marketing in Africa countries is also dominated by inadequate equipment/infrastructure, slaughter facility, lack of refrigeration/storage facilities and poor hygiene [52, 56, 61, 65, 67, 70, 71, 79, 80]. There was limited processing ability due to poor electricity supply [51, 52, 74, 81, 82]. Thus, to avoid condemnation at abattoirs [40] and spoilage, farmers are forced to sell their pigs at informal markets and at poor prices. This has been reported in South Africa [40, 43, 68, 73], Kenya [67] and Tanzania [41]. Consequently, majority of the farmers in South Africa reported that they sold to any willing buyer due to lack of stable market [73].
\nFifthly, few wholesalers are usually involved in the transaction compared to retailers [56] because of insufficient funds and credit facilities as reported in Kenya [38] and Nigeria [56, 78, 83]. Moreover, lack of funds affected pig production and marketing especially due to high cost of transportation faced by the traders in Botswana and Nigeria [56, 79, 84]. In some instances, the problem is exaggerated due to increase in the price of petroleum and spare parts of vehicles [56, 70, 71, 85]. This is because majority of the traders in most African countries including Uganda do not own vehicles for transportation and thus engage the services of other transporters [66]. Hence both live pigs and pig carcasses are transported in trucks, buses, roof of saloon cars, bicycles and motorbikes openly while pigs from neighbouring villages are trekked directly to the markets in Nigeria (motorbike transportation of pigs in Quan-Pan LGA of Plateau state, Nigeria - Figure 2a) [56, 86] and Kenya [74]. The method of transporting pig/pig products can spread diseases including African swine fever and foot and mouth disease etc. which comes with severe economic consequences [82].
\nHerd Health Management of pigs just like in other livestock involves all the farm practices that promotes health, improve productivity and prevent diseases in animals for the benefit of all stakeholders in the industry, while at the same time not sacrificing animal welfare, food safety, public health and environmental sustainability [87]. Traditionally, the essence of herd health is to control or eliminate diseases and management inefficiencies that may impact on welfare or limit swine productivity. This is achieved by ensuring comprehensive husbandry management systems that includes breeding, biosecurity and environmental management, nutrition management, parasite control, vaccination, adequate risk monitoring and assessment in conjunction with best farming practices in a practical and economically feasible way [88]. Health management of Swine in Africa is dependent on the type of husbandry or production system being employed by the farmer. Three major management systems are obtainable in most developing countries of Africa, and they include:
\nThe free-range (scavenging) system which is the oldest and traditional method of rearing pigs in most parts of the world is mostly obtained in rural areas where resources (feeds and capital) are limited but with ample land resources necessary for wandering animals (Figure 1a). It involves households keeping a small number (1–3) of pigs which can roam about and scavenge for food and water, with occasional provision of kitchen wastes, and farm by-products. Pigs are rarely sheltered and there is no investment on feed or veterinary services [74]. The unrestricted roaming often leads to indiscriminate mating, with high probability of inbreeding leading to poor quality offspring. Local pig breeds are suitable for this system because they have high resistance to diseases and can manage with low-quality feed therefore, disease control in this system is quite minimal since little or no investment and management are needed [89]. In several African countries where the free-range traditional system of pig production has been characterized, its hallmark includes high mortality rate due to diseases, minimal health care, slow growth rate due to poor feed conversion, low off take, low reproductive rates, lack of supplementary feeding, and lack of proper housing [90, 91].
\n(a) Free-ranging village pig, Langtang, Nigeria. (b) Semi-intensively kept pigs, Shendam, Nigeria. (c) Intensive piglets in a farrowing pen in Jos-south, Nigeria (d) Backyard pig farm, Wukari, Nigeria. (Pictures courtesy of Adedeji JA).
The semi-intensive system involves the restriction of pigs to a limited space (Figure 1b and 1d), with the provision of feed (kitchen wastes and agricultural by-products), water and veterinary services. Periodically, the pigs are allowed into a larger area to exercise, graze, and wallow, such that some classes of pigs are kept outside the pig shelters, e.g. boars and sows stay within a perimeter fence where water, feeds and shade are provided [70].
\nThe intensive system of farming is characterised by complete housing of pigs and provision of complete diets (Figure 1c). In this system, pigs are shifted from one pen to another according to the production stage, until they reach market weight [70]. This management system is practised in large-scale commercial systems that are characterized by improved breeds, use of commercial concentrates for feeding and proper housing with sophisticated equipment and biosafety measures [33]. In certain parts of Africa especially the urban areas where land resources are minimal due to explosion of human population and urbanization, pig farmers tend to adopt the intensive and semi-intensive systems of production [91].
\nThe most prevalent and endemic disease responsible for outbreaks in many pig producing areas of Africa is the African swine fever, a viral disease that spreads rapidly and is associated with high morbidity and mortality [92, 93]. Other known infectious diseases that have been recorded includes, but not limited to swine erysipelas, brucellosis, exudative dermatitis (greasy pig), respiratory diseases, swine dysentery, mastitis, and porcine parvovirus. Parasitic diseases in the form of Helminthosis (Strongylid parasites,
Diseases and poor herd-health management practices are the major challenges to efficient management and profitable swine production in developing countries of the world [96]. In terms of disease control and herd health management in most pig producing areas of Africa, government and private veterinarians are usually available to provide disease diagnosis and treatment services. However, the level of acceptance of such services from farmers varies especially among smallholder farmers. In preventing swine diseases, having a herd health plan usually help to minimize disease incidence, thus most farmers depend on the provision of adequate housing, good husbandry and nutrition, hygiene, and ventilation [97].
\nVaccination is a major focus of disease prevention and herd-health management in pig production. Vaccines in use in a few African countries against production limiting diseases of pigs includes but not limited to Erysipelas,
While pig farmers in many African countries are scaling up their businesses from backyard to commercial enterprises due to increased population growth and demand for complementary source of animal protein, many are confronted with a number of challenges ranging from high feed costs that are prohibiting their progress, transboundary diseases and inadequate extension and veterinary service, poor breeding stock, unorganized marketing and inadequate slaughter facilities. Another challenge is the religious sentiments in some part of Africa towards pigs and pork products [38, 67, 74]. Despite these challenges pig farming and pork are gradually gaining acceptance in Africa. However, for production to be raised, these challenges need to be addressed individually at farm level and collectively by stakeholders through collaborative efforts.
\nEfficient and profitable pig production has been on the decline in Africa irrespective of the benefits derived from pig farming due to disease as observed in Nigeria [29, 78], Senegal [100], Kenya [67, 74] Congo [53], Southern Africa [37, 101], Botswana [61], Uganda [51, 52, 102], Tanzania [103], and Cameroon [80]. Livestock diseases forms one of the key threats to the livestock industry and specifically pig farming since diseases that affect livestock reduce productivity [104]. Livestock diseases including pig disease represent a major constraint to profitable production and have devastating impacts upon the industry leading to losses in hundreds of millions of dollars every year in Sub-Saharan Africa [105, 106]. Important pig diseases especially in Nigeria include: African swine fever, foot-and-mouth disease, brucellosis, Trypanosomosis, babesiosis, eperythrozoonosis, helminthosis, coccidiosis and other parasitoses (reviewed in [106]). These diseases impact negatively on production by affecting feed conversion efficiency, reproduction and growth rates as well as causing piglet and adult mortalities [106]. There is also the risk of zoonosis associated with some of the pig diseases. In general, a disease control strategy that can provide for the sustainability and expansion of the pig production capacity [106] is necessary in Africa.
\nHigh piglet and pig mortality rates has been reported in many African countries [32, 37, 38, 53, 58, 68, 69, 73, 74, 78, 83, 91, 103, 107, 108, 109]. These piglet mortalities affects both exotic and indigenous breeds, and were largely attributed to low birth weights and diseases such as septicaemia and colisepticaemia [101, 106] or high pre-weaning mortalities have been associated with crushing and chilling which are indication of inadequate husbandry management practices when farrowing pen with heating facilities are not provided [61, 69]. In addition, starvation, agalactiae and stress have also been reported to cause pre-weaning mortality [101]. Therefore, strategies that can provide adequate neonatal health and prevention of infertility and abortions in herds are paramount and appropriate initiative for growth of the pig population [106].
\nMost animal production activities in Africa are located in rural areas or remote areas that are inaccessible to proper veterinary services, while those that are accessible grapple with high cost of drugs and veterinary services that may be prohibitive. Thus, the farmers are forced to resort to easily available quacks that can wreak havoc on their animals due to wrong diagnosis and the prescriptions of wrong drug for treating diseases, or the use of expired vaccines, fake and sub-standard drugs [105, 110]. In addition, poor veterinary services were also reported among small scale farmers due to lack of skilled veterinarians or inadequate Vet staff. Sometimes the access by farmers to veterinarians is often limited by poor infrastructure including road/transport system as observed in many African countries including Nigeria, Kenya, Uganda, Tanzania, Cameroon, and Ethiopia [38, 67, 71, 74, 80, 83, 102, 103, 107, 111].
\nMajor production constraints including high cost of drugs, veterinary services and labour encountered by pig producers in many Africa including Nigeria, Kenya, Senegal, Congo, South Africa, Uganda and Angola have been reported [29, 32, 38, 53, 54, 73, 83, 86, 100]. Similarly, limited vaccination and biosecurity or public health preventive measures with little or no treatments of sick pigs have been reported in some African countries among small-scale pig farmers [17, 38, 40, 41, 42, 68, 71, 75, 76, 80, 111].
\nThe extension system and services in Africa is also poor and ineffective and extension networks are weak. Farmers did not know veterinarians existed as observed in Tanzania [103], Ethiopia [111], Kenya [38, 67, 71], Botswana [61, 70], South Africa [17, 42, 59] and Nigeria [112]. In addition, extension staff are not sufficiently trained and equipped to offer excellent service to pig farmers as observed in Botswana [61, 70] and South Africa [40]. Poor relationship between small scale farmers and animal health technicians have also been reported in many African countries [53, 67, 73, 102], thus depriving them of the opportunities to access health services for their animals. There is therefore the need for governments of most African countries to standardize and subsidize veterinary services to farmers [105].
\nSome farmers lacked knowledge of veterinary services, as they did not know they could contact veterinarians to offer veterinary services for their animals in South Africa [40, 52, 68, 73] and Kenya [67]. While some of the farmers were misinformed over the effectiveness of some veterinary treatments and vaccines in Congo [53] and South Africa [65]. However, others believe that indigenous pigs can’t fall sick especially with intestinal parasites as reported in South Africa [17] and Kenya [38], and thus do no need treatment. Similarly, farmers lacked knowledge on pig diseases and their identification in Kenya [67, 74].
\nThe lack of basic knowledge on pig management practices was observed among famers, thus such farmers resort to traditional pig farming system which are archaic and unproductive. Pigs were seen under poor management system, with some either roaming freely, tethered or kept in poor and improper housing most of the year, while some are penned during the rainy season and sheltered only in the night. This was done in order to keep the cost of input of production low as observed in many African countries [29, 37, 38, 68, 73, 81, 102, 111, 113, 114, 115, 116]. Free range pigs also serve as sources of neighbour’s conflicts due to their destructive behaviour on farmlands [78], which in extreme cases leads to the shootings or salt poisoning of pigs [67]. Tether wounds were commonly observed on the neck and leg of pigs which is a welfare worry as farmers lacked the knowledge to tie proper knots and do not regularly rotate tethers to different sites on the pig’s body as reported in Kenya [38].
\nThe farmers are faced by high cost of production inputs including building materials, hence farmers use poor building material for pig housing as observed in Senegal [100], Nigeria [29, 83, 116], Uganda [52, 102], South Africa [68, 73], Cameroon [80], Botswana [61], Kenya [38] and Ghana [117]. High cost of pigs and piglets was also common challenges among small scale farmers as reported in Nigeria [78, 86], hence shortage of piglets has been observed in some African countries like Kenya [67]. Due to the poor or lack of infrastructure, small scale farmers allow their pigs to roam, thus confound deworming of pigs and also expose pigs to increased risk of diseases and infections, theft and pilferage [37, 40, 41, 73, 74, 102, 113].
\nGood and nutritious feeds are essential for growth, body maintenance and productivity, but animal feeds which are nutritive and essential for productivity are not readily available and where they are, they are not easily affordable for an average farmer [105]. In pig production, feeds which are mostly made up of maize and soya beans account for approximately 88% of the cost of production [69]. However, most African countries and the farmers do not produce enough of these cereals to meet the demands of the pig farmers. Thus, feed manufacturing companies depends more on imported raw materials to meet their customer’s needs [61], thus making their finished product expensive, and since farmers are into animal production for profit, the high cost of feeds make production unsustainable.
\nHigh feed cost is observed or reported in many African countries [31, 51, 52, 65, 68, 71, 73, 75, 103, 107, 108, 113]. Unbalanced diets were also given to pigs in many African countries which adds to their slow growth and causes a reduced pig performances [29, 40, 41, 51, 53, 54, 61, 70, 71, 73, 77, 78, 79, 80, 81, 83, 111, 117].
\nFeeding of swill/kitchen wastes/leftovers to pigs by small- holder farmers is commonly reported across Africa as a substitute to commercial feeds and to reduce the cost of production [42, 53, 57, 68, 80, 111]. Inadequate feeding was commonly practiced in dry season, in Kenya [38] and South Africa [17, 73]. Swill generally consists of restaurant waste and kitchen scraps [43, 44, 59, 75]. However, feeding such feed is associated with poor growth and depressed economic gain [43], and predispose pigs to infection and diseases [43]. The feeding of swill has been associated with disease occurrence especially, FMD and ASF [102].
\nSome African pig industry like Uganda largely depend on indigenous breeds of pigs [52] however the challenges across Africa include lack of good quality breeding stock [38, 40, 51, 68, 71, 74, 75, 76, 81, 82, 86].
\nFarmers reported poor reproductive performance across various regions of Africa [38, 58, 68, 107]. This is confounded by the fact that most of the farmers do not have boars and are thus forced to source for boars in neighbouring towns [37, 38, 40, 41, 51, 86, 118] or buy auctioned boars to service their sows which promotes the spread of diseases [43, 51, 68, 73, 107] and promotes Inbreeding. Inbreeding causes depression, and a weakening of genetic pools [40, 73], loss in heterozygosity and increases homozygosity which results in increased lethal genes that increase embryonic death, mummified foetuses etc. [61]. Lending of boars also causes break in biosecurity measures and promotes the spread of parasites and diseases [41, 73, 99, 107, 108]. Moreover, breeding is not controlled as the farmers had no set purposes; it is just carried out randomly [117].
\nThe farmers also found it difficult to access credit facility or institutional/government loans as reported in Nigeria [79, 112], Uganda [52], Kenya [67], Botswana [61] and South Africa [73]. Hence most of the farms could not enlarge but existed under small scale [67, 86]. Water and electricity are also lacking and limited in some locations as seen in Uganda [52], Botswana [70] and Nigeria [79] as such small-holders do not have the finance to provide their own sources of water and electricity. Lack of Land and sufficient space for pig farming was observed by some studies in Nigeria [29, 79], Kenya [67] Uganda [52], Botswana [61, 70], and South Africa [40, 75].
\nSocial and religious beliefs are among the constraints to pig production in Africa due to the fact that pigs are not readily accepted by most communities because of cultural, spiritual problems and religious reasons which renders it a taboo for pork to be eaten by some individuals [29, 38, 67, 78, 100, 111].
\n\n
Inbreeding should be decreased and controlled breeding should be encouraged [42].
Biosafety should be encouraged to control diseases such as African swine fever, FMD, Porcine cysticercosis etc. and farmers should be trained on diseases control [17].
Feeding practices should be improved [81].
Management system, and housing should be upgraded and pig confinement be emphasized. Government can design model pig houses and make them available to farmers [67, 81].
Record keeping should be emphasized among farmers [54] and producers, middlemen, traders and slaughter men for pork safety and traceability in Africa [38, 67].
Encouraging farmers to form cooperatives/pig farmers association in order to obtain capital/loans.
Small scale farmers and extension workers should be trained on husbandry practices [68, 102].
Government should provide physical infrastructure in the market and abattoirs and provide slaughter slabs with shades and portable water and adequate drainage facilities [79] and traders should provide cold stores in the market for meat storage [56].
Government should give farmers credit facilities in order to enable them expand their pig farms [119, 120, 121, 122, 123, 124].
Our study had the limitations of not being a structured research but most of the materials and relevant records were sourced from the following data base; Pubmed, Google scholar, Google, Ajol, Hindawi, text books, internet explorer, and NCDI Data base. Hence there might be some literature that we may not have been able to access or some records that have not been published.
\n(a) Transportation of pigs Quan-Pan LGA. (b) Local Nigerian Pig breed (Courtesy, Adedeji AJ).
The authors declare no conflict of interest.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. 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Generally, the phytochemical constituents of plants fall into two categories based on their role in basic metabolic processes, namely primary and secondary metabolites. Primary plant metabolites are involved in basic life functions; therefore, they are more or less similar in all living cells. On the other hand, secondary plant metabolites are products of subsidiary pathways as the shikimic acid pathway. In the course of studying, the medicinal effect of herbals is oriented towards the secondary plant metabolites. Secondary plant metabolites played an important role in alleviating several aliments in the traditional medicine and folk uses. In modern medicine, they provided lead compounds for the production of medications for treating various diseases from migraine up to cancer. Secondary plant metabolites are classified according to their chemical structures into various classes. 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The traditional healer provides health care services based on culture, religious background, knowledge, attitudes, and beliefs that are prevalent in his community. Illness is regarded as having both natural and supernatural causes and thus must be treated by both physical and spiritual means, using divination, incantations, animal sacrifice, exorcism, and herbs. Herbal medicine is the cornerstone of traditional medicine but may include minerals and animal parts. The adjustment is ok, but may be replaced with –‘ Herbal medicine was once termed primitive by western medicine but through scientific investigations there is a better understanding of its therapeutic activities such that many pharmaceuticals have been modeled on phytochemicals derived from it. Major obstacles to the use of African medicinal plants are their poor quality control and safety. Traditional medical practices are still shrouded with much secrecy, with few reports or documentations of adverse reactions. However, the future of African traditional medicine is bright if viewed in the context of service provision, increase of health care coverage, economic potential, and poverty reduction. Formal recognition and integration of traditional medicine into conventional medicine will hold much promise for the future.",book:{id:"6302",slug:"herbal-medicine",title:"Herbal Medicine",fullTitle:"Herbal Medicine"},signatures:"Ezekwesili-Ofili Josephine Ozioma and Okaka Antoinette Nwamaka\nChinwe",authors:[{id:"191264",title:"Prof.",name:"Josephine",middleName:"Ozioma",surname:"Ezekwesili-Ofili",slug:"josephine-ezekwesili-ofili",fullName:"Josephine Ezekwesili-Ofili"},{id:"211585",title:"Prof.",name:"Antoinette",middleName:null,surname:"Okaka",slug:"antoinette-okaka",fullName:"Antoinette Okaka"}]},{id:"54028",doi:"10.5772/67291",title:"Chemical Composition and Biological Activities of Mentha Species",slug:"chemical-composition-and-biological-activities-of-mentha-species",totalDownloads:7474,totalCrossrefCites:13,totalDimensionsCites:46,abstract:"The genus Mentha L. (Lamiaceae) is distributed all over the world and can be found in many environments. Mentha species, one of the world’s oldest and most popular herbs, are widely used in cooking, in cosmetics, and as alternative or complementary therapy, mainly for the treatment of gastrointestinal disorders like flatulence, indigestion, nausea, vomiting, anorexia, and ulcerative colitis. Furthermore, it is well documented that the essential oil and extracts of Mentha species possess antimicrobial, fungicidal, antiviral, insecticidal, and antioxidant properties. The economic importance of mints is also evident; mint oil and its constituents and derivatives are used as flavoring agents throughout the world in food, pharmaceutical, herbal, perfumery, and flavoring industry. To provide a scientific basis for their traditional uses, several studies have been conducted to determine the chemical composition of mints and assess their biological activities. This chapter describes the therapeutic effects and uses of Mentha species and their constituents, particularly essential oils and phenolic compounds; some additional biological activities will also be considered.",book:{id:"5612",slug:"aromatic-and-medicinal-plants-back-to-nature",title:"Aromatic and Medicinal Plants",fullTitle:"Aromatic and Medicinal Plants - Back to Nature"},signatures:"Fatiha Brahmi, Madani Khodir, Chibane Mohamed and Duez Pierre",authors:[{id:"193281",title:"Dr.",name:"Fatiha",middleName:null,surname:"Brahmi",slug:"fatiha-brahmi",fullName:"Fatiha Brahmi"},{id:"199693",title:"Prof.",name:"Khodir",middleName:null,surname:"Madani",slug:"khodir-madani",fullName:"Khodir Madani"},{id:"199694",title:"Prof.",name:"Pierre",middleName:null,surname:"Duez",slug:"pierre-duez",fullName:"Pierre Duez"},{id:"203738",title:"Prof.",name:"Mohamed",middleName:null,surname:"Chibane",slug:"mohamed-chibane",fullName:"Mohamed Chibane"}]},{id:"58270",doi:"10.5772/intechopen.72437",title:"Toxicity and Safety Implications of Herbal Medicines Used in Africa",slug:"toxicity-and-safety-implications-of-herbal-medicines-used-in-africa",totalDownloads:3376,totalCrossrefCites:16,totalDimensionsCites:39,abstract:"The use of herbal medicines has seen a great upsurge globally. In developing countries, many patronize them largely due to cultural acceptability, availability and cost. In developed countries, they are used because they are natural and therefore assumed to be safer than allopathic medicines. In recent times, however, there has been a growing concern about their safety. This has created a situation of ambivalence in discussions regarding their use. Some medicinal plants are intrinsically toxic by virtue of their constituents and can cause adverse reactions if inappropriately used. Other factors such as herb-drug interactions, lack of adherence to good manufacturing practice (GMP), poor regulatory measures and adulteration may also lead to adverse events in their use. Many in vivo tests on aqueous extracts largely support the safety of herbal medicines, whereas most in vitro tests on isolated single cells mostly with extracts other than aqueous ones show contrary results and thus continue the debate on herbal medicine safety. It is expected that toxicity studies concerning herbal medicine should reflect their traditional use to allow for rational discussions regarding their safety for their beneficial use. While various attempts continue to establish the safety of various herbal medicines in man, their cautious and responsible use is required.",book:{id:"6302",slug:"herbal-medicine",title:"Herbal Medicine",fullTitle:"Herbal Medicine"},signatures:"Merlin L.K. Mensah, Gustav Komlaga, Arnold D. Forkuo, Caleb\nFirempong, Alexander K. Anning and Rita A. Dickson",authors:[{id:"190435",title:"Dr.",name:"Caleb",middleName:null,surname:"Firempong",slug:"caleb-firempong",fullName:"Caleb Firempong"},{id:"212111",title:"Dr.",name:"Gustav",middleName:null,surname:"Komlaga",slug:"gustav-komlaga",fullName:"Gustav Komlaga"},{id:"217045",title:"Dr.",name:"Arnold Forkuo",middleName:null,surname:"Donkor",slug:"arnold-forkuo-donkor",fullName:"Arnold Forkuo Donkor"},{id:"217049",title:"Prof.",name:"Merlin Lincoln Kwao",middleName:null,surname:"Mensah",slug:"merlin-lincoln-kwao-mensah",fullName:"Merlin Lincoln Kwao Mensah"},{id:"217488",title:"Dr.",name:"Alexander K.",middleName:null,surname:"Anning",slug:"alexander-k.-anning",fullName:"Alexander K. Anning"},{id:"223959",title:"Prof.",name:"Akosua Rita",middleName:null,surname:"Dickson",slug:"akosua-rita-dickson",fullName:"Akosua Rita Dickson"}]},{id:"26489",doi:"10.5772/28224",title:"Alternative and Traditional Medicines Systems in Pakistan: History, Regulation, Trends, Usefulness, Challenges, Prospects and Limitations",slug:"alternative-and-traditional-medicines-systems-in-pakistan-history-regulation-trends-usefulness-chall",totalDownloads:9199,totalCrossrefCites:9,totalDimensionsCites:21,abstract:null,book:{id:"542",slug:"a-compendium-of-essays-on-alternative-therapy",title:"A Compendium of Essays on Alternative Therapy",fullTitle:"A Compendium of Essays on Alternative Therapy"},signatures:"Shahzad Hussain, Farnaz Malik, Nadeem Khalid, Muhammad Abdul Qayyum and Humayun Riaz",authors:[{id:"73162",title:"Dr.",name:"Shahzad",middleName:null,surname:"Hussain",slug:"shahzad-hussain",fullName:"Shahzad Hussain"},{id:"82266",title:"Dr.",name:"Farnaz",middleName:null,surname:"Malik",slug:"farnaz-malik",fullName:"Farnaz Malik"},{id:"124185",title:"Dr.",name:"Humayun",middleName:null,surname:"Riaz",slug:"humayun-riaz",fullName:"Humayun Riaz"},{id:"124186",title:"Mr.",name:"Muhammad Abdul",middleName:null,surname:"Qayyum",slug:"muhammad-abdul-qayyum",fullName:"Muhammad Abdul Qayyum"},{id:"125340",title:"Mr.",name:"Nadeem",middleName:null,surname:"Khalid",slug:"nadeem-khalid",fullName:"Nadeem Khalid"}]}],mostDownloadedChaptersLast30Days:[{id:"64851",title:"Herbal Medicines in African Traditional Medicine",slug:"herbal-medicines-in-african-traditional-medicine",totalDownloads:14207,totalCrossrefCites:30,totalDimensionsCites:52,abstract:"African traditional medicine is a form of holistic health care system organized into three levels of specialty, namely divination, spiritualism, and herbalism. The traditional healer provides health care services based on culture, religious background, knowledge, attitudes, and beliefs that are prevalent in his community. Illness is regarded as having both natural and supernatural causes and thus must be treated by both physical and spiritual means, using divination, incantations, animal sacrifice, exorcism, and herbs. Herbal medicine is the cornerstone of traditional medicine but may include minerals and animal parts. The adjustment is ok, but may be replaced with –‘ Herbal medicine was once termed primitive by western medicine but through scientific investigations there is a better understanding of its therapeutic activities such that many pharmaceuticals have been modeled on phytochemicals derived from it. Major obstacles to the use of African medicinal plants are their poor quality control and safety. Traditional medical practices are still shrouded with much secrecy, with few reports or documentations of adverse reactions. However, the future of African traditional medicine is bright if viewed in the context of service provision, increase of health care coverage, economic potential, and poverty reduction. Formal recognition and integration of traditional medicine into conventional medicine will hold much promise for the future.",book:{id:"6302",slug:"herbal-medicine",title:"Herbal Medicine",fullTitle:"Herbal Medicine"},signatures:"Ezekwesili-Ofili Josephine Ozioma and Okaka Antoinette Nwamaka\nChinwe",authors:[{id:"191264",title:"Prof.",name:"Josephine",middleName:"Ozioma",surname:"Ezekwesili-Ofili",slug:"josephine-ezekwesili-ofili",fullName:"Josephine Ezekwesili-Ofili"},{id:"211585",title:"Prof.",name:"Antoinette",middleName:null,surname:"Okaka",slug:"antoinette-okaka",fullName:"Antoinette Okaka"}]},{id:"61866",title:"Plants Secondary Metabolites: The Key Drivers of the Pharmacological Actions of Medicinal Plants",slug:"plants-secondary-metabolites-the-key-drivers-of-the-pharmacological-actions-of-medicinal-plants",totalDownloads:8875,totalCrossrefCites:56,totalDimensionsCites:140,abstract:"The vast and versatile pharmacological effects of medicinal plants are basically dependent on their phytochemical constituents. Generally, the phytochemical constituents of plants fall into two categories based on their role in basic metabolic processes, namely primary and secondary metabolites. Primary plant metabolites are involved in basic life functions; therefore, they are more or less similar in all living cells. On the other hand, secondary plant metabolites are products of subsidiary pathways as the shikimic acid pathway. In the course of studying, the medicinal effect of herbals is oriented towards the secondary plant metabolites. Secondary plant metabolites played an important role in alleviating several aliments in the traditional medicine and folk uses. In modern medicine, they provided lead compounds for the production of medications for treating various diseases from migraine up to cancer. Secondary plant metabolites are classified according to their chemical structures into various classes. In this chapter, we will be presenting various classes of secondary plant metabolites, their distribution in different plant families and their important medicinal uses.",book:{id:"6302",slug:"herbal-medicine",title:"Herbal Medicine",fullTitle:"Herbal Medicine"},signatures:"Rehab A. Hussein and Amira A. El-Anssary",authors:[{id:"212117",title:"Dr.",name:"Rehab",middleName:null,surname:"Hussein",slug:"rehab-hussein",fullName:"Rehab Hussein"},{id:"221140",title:"Dr.",name:"Amira",middleName:null,surname:"El-Anssary",slug:"amira-el-anssary",fullName:"Amira El-Anssary"}]},{id:"77433",title:"Extraction of Bioactive Compounds from Medicinal Plants and Herbs",slug:"extraction-of-bioactive-compounds-from-medicinal-plants-and-herbs",totalDownloads:1266,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"Human beings have relied on herbs and medicinal plants as sources of food and remedy from time immemorial. Bioactive compounds from plants are currently the subject of much research interest, but their extraction as part of phytochemical and/or biological investigations present specific challenges. Herbalists or scientists have developed many protocols of extraction of bioactive ingredients to ensure the effectiveness and the efficacy of crude drugs that were used to get relief from sickness. With the advent of new leads from plants such as morphine, quinine, taxol, artemisinin, and alkaloids from Voacanga species, a lot of attention is paid to the mode of extraction of active phytochemicals to limit the cost linked to the synthesis and isolation. Thus, the extraction of active compounds from plants needs appropriate extraction methods and techniques that provide bioactive ingredients-rich extracts and fractions. The extraction procedures, therefore, play a critical role in the yield, the nature of phytochemical content, etc. This chapter aims to present, describe, and compare extraction procedures of bioactive compounds from herbs and medicinal plants.",book:{id:"10356",slug:"natural-medicinal-plants",title:"Natural Medicinal Plants",fullTitle:"Natural Medicinal Plants"},signatures:"Fongang Fotsing Yannick Stéphane, Bankeu Kezetas Jean Jules, Gaber El-Saber Batiha, Iftikhar Ali and Lenta Ndjakou Bruno",authors:[{id:"224515",title:"Dr.",name:"Fongang Fotsing",middleName:null,surname:"Yannick Stéphane",slug:"fongang-fotsing-yannick-stephane",fullName:"Fongang Fotsing Yannick Stéphane"},{id:"227816",title:"Dr.",name:"Bankeu Kezetas",middleName:null,surname:"Jean Jules",slug:"bankeu-kezetas-jean-jules",fullName:"Bankeu Kezetas Jean Jules"},{id:"227817",title:"Prof.",name:"Lenta Ndjakou",middleName:null,surname:"Bruno",slug:"lenta-ndjakou-bruno",fullName:"Lenta Ndjakou Bruno"},{id:"349790",title:"Prof.",name:"Gaber",middleName:null,surname:"El-Saber Batiha",slug:"gaber-el-saber-batiha",fullName:"Gaber El-Saber Batiha"},{id:"357350",title:"Dr.",name:"Iftikhar",middleName:null,surname:"Ali",slug:"iftikhar-ali",fullName:"Iftikhar Ali"}]},{id:"26491",title:"Homeopathy: Treatment of Cancer with the Banerji Protocols",slug:"homeopathy-treatment-of-cancer-with-the-banerji-protocols",totalDownloads:54048,totalCrossrefCites:1,totalDimensionsCites:2,abstract:null,book:{id:"542",slug:"a-compendium-of-essays-on-alternative-therapy",title:"A Compendium of Essays on Alternative Therapy",fullTitle:"A Compendium of Essays on Alternative Therapy"},signatures:"Prasanta Banerji and Pratip Banerji",authors:[{id:"79939",title:"Dr",name:"Prasanta",middleName:null,surname:"Banerji",slug:"prasanta-banerji",fullName:"Prasanta Banerji"},{id:"79943",title:"Dr.",name:"Pratip",middleName:null,surname:"Banerji",slug:"pratip-banerji",fullName:"Pratip Banerji"}]},{id:"54028",title:"Chemical Composition and Biological Activities of Mentha Species",slug:"chemical-composition-and-biological-activities-of-mentha-species",totalDownloads:7474,totalCrossrefCites:13,totalDimensionsCites:46,abstract:"The genus Mentha L. (Lamiaceae) is distributed all over the world and can be found in many environments. Mentha species, one of the world’s oldest and most popular herbs, are widely used in cooking, in cosmetics, and as alternative or complementary therapy, mainly for the treatment of gastrointestinal disorders like flatulence, indigestion, nausea, vomiting, anorexia, and ulcerative colitis. Furthermore, it is well documented that the essential oil and extracts of Mentha species possess antimicrobial, fungicidal, antiviral, insecticidal, and antioxidant properties. The economic importance of mints is also evident; mint oil and its constituents and derivatives are used as flavoring agents throughout the world in food, pharmaceutical, herbal, perfumery, and flavoring industry. To provide a scientific basis for their traditional uses, several studies have been conducted to determine the chemical composition of mints and assess their biological activities. This chapter describes the therapeutic effects and uses of Mentha species and their constituents, particularly essential oils and phenolic compounds; some additional biological activities will also be considered.",book:{id:"5612",slug:"aromatic-and-medicinal-plants-back-to-nature",title:"Aromatic and Medicinal Plants",fullTitle:"Aromatic and Medicinal Plants - Back to Nature"},signatures:"Fatiha Brahmi, Madani Khodir, Chibane Mohamed and Duez Pierre",authors:[{id:"193281",title:"Dr.",name:"Fatiha",middleName:null,surname:"Brahmi",slug:"fatiha-brahmi",fullName:"Fatiha Brahmi"},{id:"199693",title:"Prof.",name:"Khodir",middleName:null,surname:"Madani",slug:"khodir-madani",fullName:"Khodir Madani"},{id:"199694",title:"Prof.",name:"Pierre",middleName:null,surname:"Duez",slug:"pierre-duez",fullName:"Pierre Duez"},{id:"203738",title:"Prof.",name:"Mohamed",middleName:null,surname:"Chibane",slug:"mohamed-chibane",fullName:"Mohamed Chibane"}]}],onlineFirstChaptersFilter:{topicId:"991",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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Dr. Şentürk serves as the editorial board member of several international journals.",institutionString:"Ağrı İbrahim Çeçen University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Ağrı İbrahim Çeçen University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}],selectedSeries:{id:"11",title:"Biochemistry"},selectedSubseries:{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,series:{id:"11",title:"Biochemistry"}}},seriesLanding:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"June 29th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:318,numberOfPublishedBooks:32,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/52199",hash:"",query:{},params:{id:"52199"},fullPath:"/profiles/52199",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()