Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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1. Introduction
Superalloys are operated in industrial environments containing corrosive species such as sulfur, chlorine- or carbon-containing compounds, water vapor, alkali and alkaline-earth metal salts, or ashes such as vanadates [1,2]. At elevated temperatures, such compounds cause a wide range of attack types on most metallic alloys such as oxidation, carburization, sulfidation, hot corrosion, or a combination of different mechanisms [3,4]. But even in air the oxidation resistance of nickel- and cobalt-based superalloys is not sufficient for continuous operation above 1000°C [5]. Oxide scales grow too fast and the subsurface zone of the alloys is changed and loses its mechanical strength [6-8]. Despite these limitations, advances and improvements of industrial technology have led to more efficient processes and more powerful engines with increased operation temperatures, and the alloys used for their construction are pushed toward the applicable limit even as far as mechanical properties are concerned, such as fatigue, tensile strength, and creep resistance [9]. Therefore higher additions of alloying elements for corrosion protection such as Cr, Al, or Si cannot be used as they either lead to embrittlement or lower the melting point and therefore the creep strength at the high target temperatures [10,11]. The only way is to apply high-temperature coatings to face aggressive corrosive high-temperature atmospheres and make processes possible which could not be operated efficiently and reliably without such coatings.
Diffusion- and metal-based overlay coatings are both used to protect a system from oxidation and corrosion [12]. Such coatings are designed to avoid direct contact between the base metal alloy and a hot gas carrying detrimental species by growing a thin, self-healing oxide scale in situ.
Besides oxidation and corrosion protection, the other major factor affecting the overall life of substrates at high temperatures are heat-flux effects. Nickel- and cobalt-based alloys are employed in gas temperatures up to 1400°C [13]. Without proper protection, the temperatures could easily induce softening or even reach the melting point of the alloys. The employed materials are the actual major constraints that determine the maximum gas temperatures in many processes of today’s aircraft as well as energy conversion industry. Without cooling and protection by coatings, the efficiency and speed of jet engines would also be limited to a very low level. In these cases, only a combination of two coatings allows operation; a so-called bond coat (the bond coat belongs to the class of diffusion or overlay coatings, which are discussed in detail below) in combination with a ceramic layer on top to form a thermal barrier coating system. The ceramic layer also reduces the attack indirectly by lowering the metal surface temperature and thus decelerates the degradation of the metallic coating and substrate underneath.
Figure 1.
Schematic sketches of the general configuration of the three different types of coatings used for high-temperature applications (from left to right): diffusion coatings, metal overlay coatings, and thermal barrier coatings
Only by combining one of the different types of coatings schematically shown in Figure 1 with a load-carrying superalloy underneath, safe operation over a reasonable lifetime can be ensured. In operation the coatings must be able to sustain certain mechanical and thermo-mechanical loads as well as erosion on top of the oxidative or corrosive attack. Ideally, the durability or lifetime of protective coatings for parts such as turbine blades or vanes matches that of the aging processes of the substrate underneath. However, since all coatings are more or less thin films, the mechanical lifetime of the substrate is often longer than the period of coating degradation at high temperature. Therefore, after a certain time in service, the coatings residues are stripped and the coatings are remanufactured several times during the lifetime of the blades [14].
2. Requirements for protective coatings at high temperatures
Unlike aqueous corrosion conditions at low temperatures, where usually either an anodic protection is applied or even very thin barrier coatings can protect from degradation by separating an electrolyte from the material, high-temperature degradation processes are controlled by transport processes in or through coatings via diffusion. High temperatures are especially demanding because all metals tend to become thermodynamically stable in their oxidized form or tend to react with other gas components such as nitrogen, carbon, or sulfur. For example, even highly corrosion-resistant platinum suffers from significant oxidative degradation above 1000°C in air [15]. Which corrosion products form in an environment depends on the partial pressure or activity of different potential reaction partners in the atmosphere. The idea behind all oxidation- and corrosion-resistant coatings is to create a reservoir of scale-forming elements from which a thermodynamically stable, slow growing, adherent scale can be formed, consisting of corrosion products, usually thermally grown oxide on the surface. An overview of the requirements for coatings for high temperatures is provided in Table 1.
\n\t\t
\n\t\t
\n\t\t\t
• Slow-growing, thermodynamically stable scale formation and high concentration of the scale-forming elements • Thermal stability, no detrimental phase changes • Erosion resistance • Good adhesion • Low interdiffusion of the substrate • Mechanical compatibility: similar modulus and thermal expansion to avoid stresses at the interface • No crack initiation, not too brittle • Good processability • Low price
\n\t\t
\n\t
Table 1.
Requirements for high-temperature coatings
Even with stable protective oxide scales, the service conditions will usually create flaws such as cracks in the scale. Most important is the self-healing potential or ability for reformation, properties which for example a pure ceramic coating cannot provide. In Figure 2 a pure ceramic coating is compared with a thermally grown oxide scale that builds up in situ. In the first case, if a crack occurs, the atmosphere can attack the metal below, which cannot protect itself. Ceramics also always possess a certain porosity and cannot prevent the gas from reaching the metal below, which means they offer no effective long-term corrosion protection. Ceramic coatings are therefore almost exclusively used to lower substrate temperatures and in combination with one additional coating of the diffusion or metallic overlay type which can form slow-growing oxides. Diffusion or overlay coatings possess a sufficient reservoir of protective elements underneath the scale to allow the reformation of the protective scale many times before the reservoir of the protective elements is depleted.
Figure 2.
Comparison between a ceramic coating without self-healing properties (a) and a reservoir coating that allows the reestablishing of the protective scale in case of local failure (b)
The potentially protective elements, which qualify for scale formation, must form thermodynamically more stable corrosion products than the main elements in the superalloy such as nickel or cobalt. The graph in Figure 3 is a simplified Ellingham-Richardson Diagram that shows the standard free energy of oxide formation as a function of the temperature. Generally, for scale formation on nickel- or cobalt-based alloys, elements with a very high affinity to oxygen such as aluminum, chromium, or silicon are important, but also titanium or tantalum would theoretically qualify. The drawback for example in the case of titanium is that it allows fast oxygen diffusion through its oxide scales, which have high growth rates even at moderate temperatures. Additionally, they often tend to spall off easily.
Figure 3.
Simplified Ellingham-Richardson Diagram
Figure 4.
Parabolic weight gain of ideal scale growth
So not only the criterion of thermodynamically preferred reaction has to be fulfilled, the scales also have to be slow-growing. Only scales that form a dense and stable crystal lattice effectively limit diffusion and guarantee a slow growth and weight gain as shown in Figure 4. From the curve, the growth rate constant kp of the thermally growing oxide can be determined according to the function:
(Δm)n=kptE1
where Δm is the weight gain per surface area of the metal [g/cm2], t is the exposure time [s], and n is the rate exponent. If the scale is protective, stable, and adherent, the value of n is usually close to 2 and the weight gain shows a parabolic diffusion-controlled behavior. The diffusion is generated by the anion and cation concentration gradient in the scale. The speed of diffusion is determined by the crystallographic structure of the oxide, the defect structure, and the microstructure, for example grain size and grain boundary distribution. In most cases, the faster diffusing species is a metallic cation, but anion diffusion is also possible [16], for example it is predominant in silica formers in a wide range of temperatures. Figure 5 shows the parabolic rate constants at 1000°C normalized to the behavior of slow-growing alumina for nickel, chromium, and silicon. It can be seen that Cr, Al, and Si offer much slower growth rates than the base metal nickel. Cobalt is not included in the diagram since its oxidation rate is even ten times higher than that of nickel.
Figure 5.
Parabolic rate constants of Fe, Co, Ni, Cr, Si, and Al oxide formers at 1000°C; data from [17] as kp (g2cm-4s-2)
Further requirements derive from the mechanical interaction of the scale with the coating underneath. During formation growth stresses occur due to the volume change, when a scale is formed by including elements from the environment such as oxygen. As a first hint on the stresses, the classical approach of Pilling and Bedworth from 1923 can be used, according to which the Pilling-Bedworth Ratio is defined as:
PBRmetal=VolumeofoxideVolumeofmetalE2
It must be higher than 1 in order to guarantee a continuous scale formation, as ceramic scales are highly prone to failure by tensile stresses. On the other hand, it must not be too high either, because when high compressive stresses occur they also induce failure by cracking and buckling of the scales. In Table 2 the values of different oxides on pure metals are shown.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tOxide\n\t\t\t
\n\t\t\t
MgO
\n\t\t\t
Al2O3
\n\t\t\t
ZrO2
\n\t\t\t
NiO
\n\t\t\t
TiO2
\n\t\t\t
CoO
\n\t\t\t
Cr2O3
\n\t\t\t
Ta2O5
\n\t\t\t
Nb2O5
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tPBR\n\t\t\t
\n\t\t\t
0.81
\n\t\t\t
1.28
\n\t\t\t
1.56
\n\t\t\t
1.65
\n\t\t\t
1.75
\n\t\t\t
1.86
\n\t\t\t
2.07
\n\t\t\t
2.5
\n\t\t\t
2.68
\n\t\t
\n\t
Table 2.
Pilling-Bedworth Ratio of different oxides on pure metals [18]
It should be noted that the PBRs of alloys are not the same as those of pure metals, so for example the PBR of an alumina scale growing on intermetallics from the Ni-Al system is significantly different to the PBR of pure Al (Table 3). So the alloy system on which an oxide grows at high temperature must be considered as well.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tα-Al2O3 on\n\t\t\t
\n\t\t\t
Ni3Al
\n\t\t\t
NiAl
\n\t\t\t
NiAl3
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tPBR\n\t\t\t
\n\t\t\t
1.71-1.88
\n\t\t\t
1.64-1.78
\n\t\t\t
1.48-1.57
\n\t\t
\n\t
Table 3.
Pilling-Bedworth Ratio of α-Al2O3 on different intermetallic aluminides [19]
After formation of the scales, the occurring stresses are dominated by the mismatch in the thermal expansion coefficients between the ceramic scale, the coating, and the alloy beneath.
When the mismatch is too high, for example with silica scales on nickel- or cobalt-based alloys, extensive cracking occurs during cyclic exposure, providing less protection than alumina and chromia, oxides which have a higher thermal expansion coefficient closer to that of the alloys underneath [20,21]. Still, even alumina or chromia scales suffer some cracking in service, but coatings for high temperatures are designed to allow self-healing of the scales.
As already mentioned, such high-temperature coating systems can be classified as diffusion coatings or overlay coatings. Ceramic thermal barrier coatings also fall into the category of overlay coatings, but these will be covered separately.
3. Diffusion coatings
Diffusion coatings are based on the enrichment of protective metallic elements close to the surface by diffusion from a reservoir outside. As for all diffusion processes, the parameters time, temperature, and phase composition are critical. The process conditions have to be optimized for each material because the phase composition and the microstructural evolution of diffusion coatings depend highly on the substrate which is coated. Figure 6 illustrates the general idea of diffusion coatings. A reservoir with a very high concentration of the element that should be enriched is created at the surface either in the gas phase or in a solid/liquid state. Due to the concentration gradient at high temperatures, elements start to diffuse into the substrate, and elements of the alloy have a tendency to diffuse outward. Depending on which process is faster, the inward or outward diffusion process is more pronounced. In both cases these processes eventually achieve the aim of changing the composition close to the surface by enrichment with the elements from the diffusion reservoir.
Figure 6.
Principle of diffusion coatings manufacturing
Several different manufacturing methods have been developed for diffusion coatings. Figure 7 gives an overview of the most important procedures. These include pack cementation, which can be done in-pack or out-of-pack (also called above the pack, which resembles the chemical vapor deposition (CVD) processes). Other processing techniques include slurry-reaction coatings, galvanic and metal foil coatings, or a hot-dipping process in a metal melt. They all have in common that a reservoir of the diffusing metal is first applied to the surface and later diffused via heat treatment.
Figure 7.
Different methods to produce diffusion coatings
3.1. Pack cementation processes
As early as in 1914 the first “pack cementation” process was reported by Allison and Hawkins [22]. They diffused aluminum into iron and steel, but the process did not receive much attention up to the 1950s. Since then, pack cementation with chromium has been widely used to enhance the corrosion behavior of low-alloyed steels [23]. In the 1970s, the aluminizing process for nickel-based alloys became popular, especially in the aircraft industry. Today more than 80% of stage 1 airfoils are coated with aluminum diffusion coatings [12], most of them by the pack cementation process. It falls into the category of chemical vapor processes and is carried out at high temperatures (600-1200°C) in an inert gas atmosphere, in vacuum, or under reducing conditions. The the powder pack is composed of an inert filler (usually Al2O3), a halogen-carrying compound as an activator, and a metallic powder of the elements to be enriched. In the 1990s, with a better theoretical understanding of the processes, co-deposition of more than one element at a time became possible and was first developed for Al in combination with Cr [24-28] to improve the corrosion behavior when sulfur is part of the hot gas. Recently, investigations have been focusing on the modification of aluminide scales by co-diffusion with reactive elements such as Y, Ce, or Hf [29,30]. Small amounts of these elements are known to improve scale adhesion [31]. Platinum modification can also be beneficial under certain conditions since it facilitates the formation of stable alumina scales. Pt has to be galvanically applied and interdiffused before aluminum is enriched via pack cementation [32]. Silicon can also be added to the aluminide coating. Similar to chromium, it enhances the resistance against sulfur-carrying gases [33]. However, its application is usually limited to small amounts because silicon bears the risk of forming low-melting phases in nickel- or cobalt-based systems [34].
In industrial applications, the reaction is conducted in tightly sealed containers in which the components are placed. The parts can either be embedded in the reactive powder mixture (“in pack”) or suspended “out-of-pack” (also called “above the pack”). In both cases either an inert or a reducing atmosphere is used. The entire container is heated to 100-200 °C to remove any residual moisture and oxygen. In the following step it is heated to the actual process temperature, which depends on the diffusing elements and on the substrates. For superalloys the temperature typically lies in the range of 900-1100°C. The holding time is dependent on the particular system and usually varies between 1 and 10 h. The optimized parameters must be evaluated for each system, usually with the help of thermodynamic calculation programs to investigate the temperature and activity of the different metal halogens which carry diffusion metals to the surface [35,36]. If the activities of the diffusing metal halides at the surface are too high, brittle phases occur frequently; if their activities are too low, too little diffusion takes place [37].
Figure 8.
Major steps during the pack cementation process [38]
Figure 8 summarizes the major steps of the classical pack cementation process. Metal halides are formed and transported via the gas phase to the surface of the component to be coated, where the halide interacts with the sample surface and dissociates into the metal and the halogen anion. The metal atom diffuses into the substrate surface zone. The formation of the coating resembles that of diffusion couples, and the driving force for the interdiffusion is the activity or concentration gradient between the environment (which contains the diffusing elements such as Al) and the surface of the components [29]. After releasing the metal at the surface, the halogen reacts with new metal atoms from the powder to keep the process continuously alive. In any case, halogens (most common are chlorine and fluorine, but bromine or iodine can also be used) serve as an activator. The contents of activator and metallic powder determine the activity of metallic halogens and therefore the amount of metal which can react at the surface. The activator is added in the form of compounds such as NH3Cl, AlF3, or as HCl gas. The metallic powder, for example Al, can be used as pure element powder but also in an alloy form with nickel or chromium, for example CrAl powder, to lower its activity.
In any case, at the surface several intermetallic phases form according to their thermodynamic stability and local phase composition. Typical intermetallic phases that can form within the substrate metals by aluminization are CoAl3, Co2Al5, or CoAl in cobalt-based alloys and NiAl3, Ni2Al3, NiAl, or Ni3Al in nickel-based alloys. As mentioned earlier, the formation of the phases at the surface is controlled by the activity (the powder composition and activator), the temperature, and the duration of the process. Goward and Boone [39] classified diffusion coatings into low- and high-activity coatings, based on observations on nickel-based alloys. A “high activity” pack structure is usually observed in pack cementation processes at lower temperatures in combination with a high aluminum activity at the surface. In this case, Ni2Al3 is formed by inward diffusion of aluminum as the dominant mechanism and the diffusion of Ni is rather low. Additionally, in aluminum-rich phases the diffusion of aluminum is favored, even in aluminum-rich NiAl. With lower Al content, its mobility decreases as well. After a high-activity process, Ni2Al3 is present at the surface, while closer to the coating–substrate interface aluminides less rich in aluminum can be found. Ni2Al3 coatings usually require a second heat treatment to transform the rather brittle phase into the desired NiAl phase. Instead, if a lower activity is used in the pack in combination with a higher temperature, Ni diffusion is faster and NiAl forms directly. As a result, these coatings grow by outward diffusion and elements of the substrate that have little solubility in the NiAl phase such as refractory metals are enriched in the substrate close to the interface as part of the so-called interdiffusion zone. In Figure 9, a high-activity coating is compared with a low-activity coating on a nickel-based superalloy.
Figure 9.
Comparison of a high-activity coating (left) with a low-activity coating (right) on a nickel-based superalloy substrate (PWA 1484)
Such coatings can be applied even inside of pipes. In this case, the tube is filled with the powder mixture and then sealed at the ends. The tube represents both the container and the part to be coated. This is an industrially established technique for huge components such as 15-m-long furnace tubes [40]. After the coating process, in case of “in pack,” sometimes inert particles from the ceramic filler remain on the surface and must be removed. If the parts have small holes or channels, these can even be blocked by residues of the inert filler. To avoid such drawbacks, turbine blades and vanes are usually coated by using the “out of pack” technique. In all cases the huge advantage is that, since it is a gas phase process, complete coverage of the surface can be ensured.
3.2. Slurry coatings
Compared with the pack cementation process, slurry coatings were developed much later in the 1970s and 1980s [39,41]. Although the processing and formation mechanisms are totally different, they offer similar microstructure and features as coatings that were applied by pack cementation. In Figure 10, the diffusion layers obtained with these two different coating methods are shown for a nickel-based alloy (CM247). The coating on the left was produced by the pack cementation described in detail above. The other coating was achieved via the slurry aluminizing route. After 1000 h of exposure in air at 1050°C, diffusion layers of both coatings look very similar and are still protective.
Figure 10.
Diffusion coatings on a CM 247 nickel-based alloy after exposure in air at 1000°C for 1050 h. The left coating was applied by the slurry process (slurry composition: 40% Al, polyvinyl alcohol, water), the coating on the right via pack cementation (powder mixture: 5% Al, 1% NH4Cl, rest Al2O3, 1000°C, 1 h in Ar/5% H2)
Thus, the slurry route represents an interesting alternative for many systems or components, especially since slurry systems can be applied on components via common immersion, painting, or spraying methods, which is a big advantage for large parts. The slurries usually contain a metal powder, sometimes an activator, and either an organic, water-based binder or chromium-phosphate acidic binder [42,43]. Water-based activator-free systems are preferred nowadays, as the use of chromium-phosphates or halogen activators is hazardous and toxic. When the coating is applied, it also has to be heat-treated. In a first step, organic binders are burnt-out in the temperature range of 300-450°C and subsequently the metal powder reacts and diffuses into the substrate at higher temperatures between 600 and 1100°C [44]. In contrast to the pack cementation process no gas phase is present. Instead, above the melting point metallic melt from the metal powder wets the substrate and reacts via a combustion synthesis (exothermic formation of intermetallics) mechanism, which is extremely fast [44]. In the beginning of the process aluminum-rich phases are formed that usually require further heat-treatment so that the layers can be converted into the desired NiAl or CoAl phases (similar as for pack cementation low-activity coatings). Modification of coatings applied by this slurry technique with other elements such as chromium and silicon is also possible by alloying with aluminum particles used for the slurry or by mixing two metallic powders. Most recently, even low-activity coatings have been manufactured by the slurry technique in one step, as described in detail elsewhere [43].
Figure 7 shows an overview of application methods for diffusion coatings, including aluminum foil, galvanic or dip coatings, whose formation mechanisms can be compared to slurry coatings where a certain amount of aluminum is directly deposited on the surface and heat-treated. However, since it is much more difficult to apply homogeneous layers, such techniques are hardly used compared with the slurry technique.
4. Overlay coatings
4.1. MCrAlY-coatings
In contrast to diffusion coatings, no elements of the substrate are incorporated in overlay coatings. Therefore, such coatings offer the possibility to apply totally different compositions compared to the base materials, and their properties can be perfectly optimized to fulfill the requirements listed in Table 1, such as being corrosion-resistant as well as mechanically and thermally compatible with the substrate. Although this flexibility allows a wide range of compositions, almost all systems for superalloys are based on a general MCrAlY composition and contain usually more than four elements with M = Co or Ni or a mixture of them plus aluminum, chromium, and an element from the group of the reactive elements such as Yttrium (MCrAlY is the common term for such types of coatings and Y stands for Yttrium) [12]. One requirement is an Al content of 10-12 wt%, which is less than in the diffusion coatings. However, a higher chromium content favors alumina formation and makes such systems reliable alumina formers. The still rather high amount of aluminum in MCrAlY coatings for superalloys forms intermetallic phases, but in this case only the β-NiAl or CoAl phase is present in the coatings. In contrast to the diffusion coatings, such phases are surrounded by a metallic nickel- or cobalt-based gamma solid solution matrix. The resulting two-phase microstructure β+γ (see Figure 11, left) increases the ductility of the coating over purely intermetallic coatings and thereby gives higher thermal fatigue resistance.
Figure 11.
NiCoCrAlY coating on nickel-based superalloy; on the left a light microscopy picture after manufacturing after application [45], on the right a MCrAlY oxidized for 500 h at 1050°C in air is shown. Close to the surface the β-precipitates are dissolved and at the interface interdiffusion and interdiffusionpores (Kirkendall-pores) can be seen
One other advantage over diffusion coatings is the significant amount of Cr in the MCrAlY coatings, which enhances the corrosion and oxidation resistance. Regarding only oxidation resistance, NiCrAlY shows the best protection, but when sulfur is present in the gas, Co-based MCrAlY systems have a higher resistance. Additionally, NiCrAlY shows a phase transition above 1000°C. Therefore, usually well-balanced NiCoCrAlY or CoNiCrAlY compositions are used in industrial applications, also depending on the type of superalloy. Besides the major elements, these systems are enhanced by the addition (<1%) of reactive elements (RE) such as yttrium, cerium, lanthanum, hafnium, or zirconium. The addition of rhenium was also shown to be beneficial [46,47].
When employed at high temperatures, the coatings degrade mainly by Al depletion due to both oxide formation and interdiffusion with the substrate. The beginning of the β dissolution is already visible close to the surface and at the interface to the superalloy after 500 h at 1050°C as shown in Figure 11, right. Similar to diffusion coatings, this aluminum depletion alters the microstructure, as visible close to the surface and at the interface to the substrate. When the β-phase is totally dissolved, the coating quickly loses its protective properties. Compared to diffusion coatings, the composition and performance is optimized, but the manufacturing of overlay coatings is much more expensive. Overlay coatings are produced by one of the following processes: Physical vapor deposition (PVD) process, thermal spraying process, or overlay welding (also called cladding). For MCrAlY overlay coatings, mainly thermal spray processes or rarely PVD processes are used.
Thermal spraying processes are a group of surface coating processes in which a spray material is partly or fully melted inside of a spray gun (electrical arc discharge is usually used as the source of energy) and accelerated toward the surface of the component to be coated in the form of micrometer-size particles. The resulting coatings are formed by the accumulation of numerous sprayed particles. Adhesion occurs primarily due to a mechanical interlocking with the surface roughness of the substrate, while metallurgical processes hardly take place and a subsequent heat treatment is required. When MCrAlY powders are sprayed in the molten state, aluminum and chromium are likely to oxidize “in-flight.” Therefore, only the following three thermal spray methods are commonly used to coat superalloys with MCrAlYs: Low pressure plasma (LPPS), vacuum plasma (VPS), and high velocity oxyfuel (HVOF) spraying. Atmospheric plasma spraying (APS) is only used for the application of zirconia thermal barrier coatings for turbine blades, as discussed later. For plasma spray processes an anode and a cathode are incorporated into a spray gun producing an electric arc to ionize the operating gas. The dissociation and ionization produces heat that allows melting and spraying even refractory elements or ceramics. Several gases can be used, but typically one of the following is chosen: argon, hydrogen, helium, or their mixtures. When the powder is injected in the plasma jet, it is melted by the high temperature of the plasma torch and also propelled toward the substrate. Because of the required low pressure or inert atmosphere for MCrAlYs, the effort and cost for this process is high. High-speed processes such a high-velocity oxy-fuel spraying (HVOF) are much more efficient and have earned high industrial acceptance. By increasing the particle velocity during spraying, unwanted oxidation reactions can also be minimized without the requirement of operating in vacuum [48]. Furthermore, due to the high deformation during the solidification process in the HVOF process, very low porosities can be achieved (<1%). Another option is Physical Vapor Deposition (PVD) processes [12,49]. PVD processes are conducted in high vacuum to avoid reactions between the metal atoms and the process gas. In order to transform the coating material into the gas phase, generally two methods are employed: heating until high vapor pressures occur; or bombardment with high energetic electrons or ions to release atoms from the target. For the components of high temperature coatings, which usually have high evaporation temperatures, the second method is preferred. Various modifications of this method exist, but the electron beam heating is the most well-established one. Concentrated electron beam rays induce a high energy density on the surface of the target so that locally extremely high temperatures occur and even refractory alloys or ceramic material can be evaporated. In order to apply alloys such as MCrAlY coatings, it is important to note that the partial pressures of the different elements are very different. The composition of the melt bath or of the master alloy has to be adapted with respect to the difference in the vapor pressures during the coating process. It can be calculated, but it must be considered that they change even during the process. Especially in the beginning of the coating process, the parameters are far from equilibrium and therefore cannot produce the desired composition. For metallic alloys, different elements have to be added during the process to regulate and adapt the master alloys in a way that the manufactured coating always has the right composition. Secondly, the achieved microstructure is highly textured, with elongated grains oriented perpendicular to the surface of the substrate. This microstructure and process is of highest technical relevance for two-component ceramic yttrium oxide-zirconium oxide layers, serving as thermal barrier top coats for superalloys.
4.2. Thermal barrier coatings
Thermal barrier coatings (TBC) are used to reduce the heat flow into the metal below in order to reduce oxidation rates and to protect it from thermal softening and accelerated creep. The main application of these systems is in stationary gas and aircraft turbines. Modern TBC systems decrease the temperature load in the superalloys beneath by 200°C, or vice versa allow an increase in operating temperature in that range to improve the turbine efficiency. TBCs consist of a combination of a bond coat which can be either a MCrAlY overlay coating or a diffusion layer with a ceramic top coat. A schematic TBC system is given in Figure 12. It shows the temperature gradient and the typical configuration on a superalloy used, e.g., as a turbine blade.
Figure 12.
Different layers of a thermal barrier system and the typical temperature gradient
All classical TBC systems, which have been developed and improved throughout the last 30 years, rely on a partially stabilized zirconia as ceramic top coat, which offers a very good combination of necessary properties [46]. Zirconia was chosen because of its low thermal conductivity in combination with a rather high thermal expansion coefficient closer to metals than that of most other ceramics [50]. In addition, it is compatible with the thermally grown alumina oxides (TGO) scales on top of the bond coat. One challenge is that ZrO is allotropic and shows three phase modifications (Figure 13).
Figure 13.
Phase diagram of ZrO2-Y2O3 showing the allotropy of zirconia and the technically used range in which the tetragonal lattice modification remains stable
Especially the phase transformation from tetragonal to monoclinic at about 1170°C that goes along with a volume change of about 3-9% would induce detrimental cracks. This phase transformation can be suppressed by adding oxides of Yttirum, Cer, Magnesium, Niobium, or Calcium [51]. In Figure 13, the impact of yttrium addition on the phase formation is shown. In commercial technical systems, about 8 % YO1.5 is added to receive metastable partially stabilized tetragonal zirconia and suppress detrimental phase transformations. Another modification that is technically used is MgO-stabilized zirconia, which requires about 20-25 wt.% MgO. This zirconia slowly destabilizes above about 1000°C and can only be used for components of diesel engines and not in turbines. Any phase destabilization or an increased sintering behavior at higher temperatures determines the upper temperature limit of the application of zirconia, because it destroys the necessary porous structure and induces cracks. Such limitations trigger the investigation of other ceramics for even higher-temperature applications than the systems today allow. Especially several ziconates with a low thermal conductivity are looked at, of which the most promising candidate is gadolinium zirconate. Such coatings are developed as a two-layer ceramic system with classical zirconia under the novel ceramics [52]. Due to the fact that ceramics are prone to tensile strains, the microstructure has to be designed carefully in order to allow at least a certain strain tolerance. The ceramic layers today are either manufactured via atmospheric plasma spraying (APS) or electron beam physical vapor deposition (EB-PVD). In both cases, a certain strain tolerance is achieved by adjusting the microstructure [53].
Figure 14.
Comparison of TBC systems with APS-sprayed zirconia and EB-PVD zirconia top layers showing the different morphology of the ceramic coating on top of a sprayed MCrAlY bond coat on the left and a pack cementated bond coat on the right
In Figure 14, on the left the APS-sprayed microstructure is schematically shown. It possesses a pancake-like structure. The strain tolerance is created by a heavily intertwined network of fine cracks. This network separates the ceramic coating into “segmented flakes” providing a higher tolerance upon strain application through the temperature gradient or difference in thermal expansion to the material below. EB-PVD (Figure 13 on the right) coatings always exhibit the typical columnar structure. This method has the big advantage that, during the EB-PVD process, the crystals of the scales grow epitactically and perpendicular to the surface. The ceramic columns are separated from each other by small gaps, providing an exceptional tolerance to deleterious tensile strains parallel to the surface. These coatings are preferentially used for aircraft turbine blades, while for stationary turbine blades or aircraft nozzle parts often APS coatings are employed, which can be produced at lower cost. One drawback of EB-PVD zirconia top coats is that they are sensitive to calcium-magnesia-alumina silicates (CMAS) attack [54]. CMAS can derive from the use of turbines in sandy desert areas or when volcanic ash enters a turbine. The CMAS melt in the heat chamber and are deposited on the turbine blades. When they penetrate into the TBC, they cause failure and spallation. Other factors with an influence on the lifetime are hot corrosion mechanisms by sulfur, calcium, or vanadium deposits on the coatings that can reduce the lifetime [55], often by reacting with the stabilizers (e.g., yttrium), thereby destroying the resistance against phase transformation of the zirconia. When the ceramic scale remains intact, in service an alumina scale grows slowly under the zirconia ceramic. This thermally grown oxide scale (TGO) must not exceed about 3 µm in thickness to guarantee mechanical integrity and avoid spallation [56].
5. Outlook
By using diffusion coatings, overlay coatings, and ceramic top coats for high temperatures, the otherwise often very short lifetime of unprotected materials can be enhanced and makes processes and applications possible for which otherwise no material is available. At the same time, high-temperature processes have been constantly changing due to changes in fuel or operating conditions, and the thermal operation limit of superalloys has continuously increased over the years. In the future, even systems such as molybdenum-based alloys might become interesting with a thermal application potential well above the nickel- and cobalt-based superalloys of today [9]. Such developments induce also a strong driving force to further develop high-temperature coating systems in order to keep pace with such increased operating conditions, and to allow efficient and reliable operation of metallic high-temperature materials.
\n',keywords:"Diffusion coatings, MCrAlYs, TBC",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/49100.pdf",chapterXML:"https://mts.intechopen.com/source/xml/49100.xml",downloadPdfUrl:"/chapter/pdf-download/49100",previewPdfUrl:"/chapter/pdf-preview/49100",totalDownloads:3469,totalViews:1074,totalCrossrefCites:5,totalDimensionsCites:15,totalAltmetricsMentions:0,impactScore:5,impactScorePercentile:93,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"November 3rd 2014",dateReviewed:"July 1st 2015",datePrePublished:null,datePublished:"November 25th 2015",dateFinished:"September 10th 2015",readingETA:"0",abstract:"High-temperature coatings for superalloys can be divided into three categories: Two of them, diffusion and overlay coatings, are both used to protect a system from oxidation and corrosion. The third type, thermal barrier coatings, protects the substrate from thermal degradation.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/49100",risUrl:"/chapter/ris/49100",book:{id:"4615",slug:"superalloys"},signatures:"Mathias C. Galetz",authors:[{id:"174362",title:"Dr.",name:"Mathias",middleName:null,surname:"Galetz",fullName:"Mathias Galetz",slug:"mathias-galetz",email:"galetz@dechema.de",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Requirements for protective coatings at high temperatures",level:"1"},{id:"sec_3",title:"3. Diffusion coatings",level:"1"},{id:"sec_3_2",title:"3.1. Pack cementation processes",level:"2"},{id:"sec_4_2",title:"3.2. Slurry coatings",level:"2"},{id:"sec_6",title:"4. Overlay coatings",level:"1"},{id:"sec_6_2",title:"4.1. MCrAlY-coatings",level:"2"},{id:"sec_7_2",title:"4.2. 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Materials for Advanced Power Engineering: Proceedings of the 6th Liege Conference, Part III. Kluwer Academic Publishers; 1998, p. 977-996.'},{id:"B54",body:'N. Chellah, M.-H. Vidal-Sétif, C. Petitjean, P.-J. Panteix, C. Rapin, and M. Vilasi. 8th International Symposium on High-Temperature Corrosion and Protection of Materials, 2012.'},{id:"B55",body:'B. Bordenet, W. König, G. Witz, and H.-P. Bossmann. 8th International Symposium on High-Temperature Corrosion and Protection of Materials, 2012.'},{id:"B56",body:'H.E. Evans. Oxidation failure of TBC systems: An assessment of mechanisms, Surf Coatings Technol. 206 (2011) 1512-1521.'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Mathias C. Galetz",address:"galetz@dechema.de",affiliation:'
DECHEMA-Forschungsinstitut, High Temperature Materials, Frankfurt am Main, Germany
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1. Introduction
The current climate change is a consequence of the increased content of atmospheric CO2, CH4, N2O, and particulate matter, which raised in 1.2°C (2018) the surface air temperature [1]. This warming climate change has impacted the hydrological cycle inducing a Hadley cell expansion and poleward movements of the jet stream, making dry areas becoming drier and wet areas became wetter [1]. This effect has been observed mainly in countries situated between 30 degrees latitude south and 30-degree latitude north (Hardly cell) and correspond very well with the reported literature by these countries to counteracts or diminish the drought effect on farming activities [2, 3, 4, 5]. Among these detrimental effects, desertification is defined as the effects of constant dry or persistent drought on fertile lands, making them desert and unsuitable for agricultural activities.
Farming land is a limited resource and climate change is reducing it, due to the desertification of rural areas usually used for agricultural purposes [6]. This devastating impact requires mitigation actions to prevent the advance of poverty in farming communities, the food shortage, and the loss of farming land [5, 6]. In this sense, is necessary to take action and start goat breeding plans in places with advanced desertification conditions that threaten the goat farming activity and their rural communities. One of these actions has been the migration of Pastoral activities to livestock production to sustain the goat farming in lands hardly affected by desertification [5]. This adaptation involves changes in the feed resources, the growth of forage resistance to desert or arid conditions but with good nourish properties, and the improvements in goat management to reduce the heat stress and sustain the goat milk and milk derivatives such as Cheese, and Yogurt [2, 5, 7].
Fortunately, the solution to sustaining goat farming activities is the goat itself. Among livestock animals, the goat is the best candidate to sustain farming activities in desert or arid zones [3, 8]. This is because domestic goat (C. hircus) is originally from the middle east and then was diversifying and habitat diverse places in Europe, Asia, and North Africa, to finally arrives in America and Australia by the European conquers [9, 10, 11]. C. hircus species has three genetic lineages. The first lineage A is present in diverse goat types across many continents and started at >200,000 years ago (YA), a long period before the beginning of goat domestication estimated around 9,000–13,000 YA according to fossil evidence [12]. While the lineage B and C started immediately after goat domestication and expanded around 10,000 YA to South and West Asia [12]. Regarding the descendant of lineage A, there is a weak cluster geographically marked (around 10%), suggesting that most of them have been widespread across the globe due to their natural migration with the human population across human history [10, 13]. That suggests domestic goat has a genetic diversity across the globe, being a huge source of diverse goat types with different adaptation traits to improve milk production in different local environments and resist climate change in rural places with limited resources [3, 14].
This chapter will discuss goat diversity and its potential in developing high milk production in desert zones. The unsuccessful experiences of not-desert dairy goats introduced in desert zones will be commented on, and the advantage of desert goats as well. Besides, the unexplored creole goats will be commented as an unexplored goat type with a valuable genetic patrimony to adapt to harsher conditions. Finally, taking advantage of all advances in genomics and molecular markers to follow goat milk production, will be discussed how these tools have been used and which are their potential to assist crossbreeding plan to improve goat milk production in areas affected by desertification.
2. Methodology
The literature analysis was done using google scholar and keywords such as; dry, desert, milk production, goat, farming, casein among other related words. Those studies performed on countries with hot, arid, or desert zones were considered for analysis and others studies from other countries that not belong to dry or desert areas were added to enrich the discussion.
2.1 Comparison of Milk Yield in Diverse Goat Types
Table 1 is a comparative and normalized analysis of milk yield per day for diverse goat species that inhabit hot, desert, or arid zones was performed. Not all these studies have reported the same milk yield parameter in terms of kg of milk per day. For those studies with a reported total lactation yield, the total milk yield was divided by the lactation period to obtain the milk yield in kg/day. In cases of total or daily milk, the yield was reported in liters, the conversion to kg was performed using the goat milk density of 1,11285 kg/l. That value comes as the average of the milk density considered in a range of 0.9917 to 1.2324 kg/l according to the report by Gabas et al. [29].
3.1 Milk production by dairy goat naturally not adapted for arid or drought zones
Dairy goats like Saanen (Sweden), Toggenburg (Sweden), Alpine (France), and Anglo-Nubian (England) have a remarkable high milk yield under extensive breeding conditions producing between 600 to 1000 kg of milk per lactation period and extraordinarily exception until 3000 kg of milk as described for a Toggenburg goat animal in 1997 [16, 30]. Therefore, seems common sense to introduce any of these dairy goats in arid zones to promote goat milk production. However, this naive approach does not always have succeed. Common dairy goats are naturally adapted to live in moistening and cold environments with plenty of food and water covering all their metabolic demands. While in dry or arid zones they have a limited food resources and dry conditions that do not satisfy their metabolic demand for high milk production [31].
Common dairy goats introduced in tropical or desert environments have a low milk yield barely producing. 200 L and 80 L, respectively [16, 22, 32, 33], as a consequence of the heat stress condition and changes in their cellular metabolism and immune response [22, 33, 34, 35, 36, 37]. Dairy goats under heat stress conditions reduce their food intake between 22 and 35% and their milk production between 3 and 10% with a reduced content of lipids, proteins, and lactose [35]. In Trinidad and Tobago, Saanen goats were introduced to improve local goat milk production but this initiative never prospered because the animals never were able to adapt to their arid conditions, manifesting detrimental thermoregulation, reduced prolificacy, and low kidding interval [38]. In a similar situation, local farmers from Tanzania imported Saanen, Toggenburg, and Norwegian goats to start dairy goat farming, and they reached a maximum milk yield of 1.2 kg per day, which was three times less than the expected 3.5 kg per day for Saanen and Toggenburg and the half of expected 2.3 kg for Norwegian goats [17]. These authors also noted that dairy goats had a low birth rate of 64%, while in a cool and moist environment the Saanen goat has an 81% of birth rate (Figure 1) [39], concluding that new breeding schemes must be planned to support a more productive goat farming activity [17].
Figure 1.
Milk production of Saanen goat in different environments.
Another interesting experience was took place in the Atacama Desert in Northern Chile. This place is one of the driest deserts in the world with less than 5 mm of rainwater per year, and comprise the Pampa of Tamarugal as an agricultural area with a protected forest placed at its core [40, 41, 42]. Underground of this Pampa of Tamarugal there is a water basin that sustains these agricultural activities and its forest, which have trees with deep roots to reach this water source [43, 44]. However, even with this water and food supplies available, the high temperatures and low moisture may induce heat stress on dairy goats affecting their milk yield (Figure 1). That explains the low milk yield observed in Saanen goats introduced in this Pampa in 2008–2009 by local ranchers within a regional strategy to improve goat milk production in local communities [33]. They include a low number of animals and in consequence, their statistics is not strong enough, but still this study worth its analysis.
They perform a crossbreeding between Saanen goat using one male and ten females, and another crossbreeding with one creole male and six Saanen females. In the first crossbreeding group they had seven pregnant goats and one of them had a spontaneous abortus, while the second crossbreeding group had four pregnant goats and any spontaneous abortus. Unexpectedly, all pregnant goats of the first group ended their gestation period delivering twins of the same gender or different genders. While the second group had only one pregnant goat that delivered twins of the same gender [33]. Usually, Saanen has a 22–45% of goat’s twins birth rates according to the doe age [39], so these unexpected results might be linked to some genetic traits present in the male Saanen [45], although this observation was unexplored by the authors [33].
The litter size observation is relevant because could be considered as a predictive value for milk yield. In Alpine goats with twins or triplets offspring produced on average 32 kg more milk than singletons goats [46]. Similarly, a study performed in the United Kingdom demonstrated that Saanen goat with single birth, during its first, second, and third lactation period produced at the 50 days a total of 143, 150, and 91 kg of milk, respectively. While twin birth goats produced 156, 205, and 216 kg of milk in the same period [47]. That constitutes an increment of 37% and 137% regarding the singleton milk yield during the second and third lactation periods.
From that perspective, for Olave et al., the high amount of twin birth observed in their study would auspice a high milk yield in that study group. However, they reported an opposite result. The maximum milk yield was 1,8 L of milk at day 10, decreasing the milk production at 1 L at 50 days and then 0.5 L until 100 days of lactation. Although the authors [17] did not determine the average total milk yield per goat, their graphic suggests a total milk production of around 60 L at day 50. Considering a milk density of 1.112 kg per mm3 [29], the authors probably produced around 66.7 kg of total milk at day 50, which is around 46% less than the expected for a Saanen goat only the 32% of the expected production for a mother goat with twin birth rate at the second lactation period [47].
In summary, the study of Olave et al. [33] is interesting because demonstrates that the introduction of common dairy goats in desert zones, even under a controlled condition with plenty of food and water, finally is hardly affected by the low moisture and high temperatures reducing their milk yield. Therefore, seems do not recommendable to introduce common dairy goats in desert zones, unless a high investment in technology would be endorsed to adapt the desert environment for a more moisture and cool husbandry. Although this investment could be afforded by developed countries, for smallholder from developing countries [48, 49] cheaper alternatives are needed, being important to explore new crossbreeding programs with native and dairy goats without major changes in goat farming.
3.2 Milk production by dairy goat adapted to arid or drought zones
In arid or desert zones, native goats have been well adapted to produce high-quality milk under limited supply conditions. In Israel, the black Bedouin goat that habitat at the desert of Negev (Figure 2), can produce between 0.95 to 1.561 kg of milk per day during the first lactation period in goats of 1–2 biological years (Table 1), and until 1.640 kg per day in older goats of 3–7 biological years [50]. This goat produces quality milk with a stable content of protein, fat, and lactose in 3.5%, 5.5%, and 5%, respectively, until the fourth lactation period [15]. Therefore, this goat is a highly efficient livestock animal that produces high-quality milk under desert conditions [51].
Figure 2.
Distribution of desert and creole goats with the potential to boost milk production in desertified areas. The map represents the land and ocean temperatures departures for average Dec 2020 with respect to a 1981–2010 base period (map from National Center for environmental information, GHCNM v4 0.1.20210105.qfe). The maps shows the habitat of selected goat breed that habitat to hot area in the Middle East, India and northern Chile. The goat breeds are: 1, northern Chilean Creole goat; 2, Barki goat; 3, Zarabi goat; 4, black Bedouin goat; 5, Ardi goat; 6, Kutchi goat; 7, Beetal goat; 8, Jamunapari goat.
Black Bedouin goat has a better adapted physiological response for dryness conditions than Saanen goat. The Bedouin goat can adapt its feed intake from 63.9 g/kg to 52.0 g/kg after 3 days of dehydration, while for the Saanen goat the same adaptation involves a more extensive feed intake reduction from 95.0 to 55.3 g/kg in the same period [52]. In other words, Bedouin goat is already adapated for goat farming under low consumption of nutrients and waters in heat stress envirnments, reaching a basal physiological condition without stress. Meanwhile, for Saanen goats, there is a higher gap between the standard food and water demands under milk farming production, and a basal physiological state under heat stress conditions, being more physiologically stressfull for this dairy goat. Curiously, both Bedouin and Saanen goats were able of reaches the same water and food intake rate after three days of dryness [52]. In consequence, the black Bedouin goat tolerates much better the heat stress and constitutes a better race option for goat farming in arid and desert zones [53].
Black Bedouin (Dhaiwi), Sahrawi (Desert) and Jordanian Damascus (Shami) goats are from Jordan (Figure 2), and like many other goats of the middle east have a common genetic origin [54]. Black Bedouin, Sharawi and Ardi goats belong to the same phylogenetic cluster according to genetic studies based on the polymorphisms of 17 microsatellite [54]. Curiously, the Ardi goat does not belong to the Jordan Country but to the Kingdom of Saudi Arabia (KSA), the nearby country (Figure 2). This goat is capable of regulating its hearth beat, corporal temperature, and diverse hormones like cortisol, triiodothyronine, and thyroxin according to the season (winter or summer), showing its evolutionary adaptation traits to live in hot and dry environments [55]. Consequently, the Ardi goat is considered the best animal for goat farming across all KAS, supporting harsher conditions, limited feed nutrition, and still give enough meat and milk to sustain economically to local farmers [56]. For that reason has been included in a national breeding program to spread its genetic trait on the herd of goat farmers across the KAS to increase the meat and milk productivity and decrease the national poverty rate [56]. The Ardi goat has a milk yield production of around 225 kg for milk yield [57], and within a crossbreeding plan with Damascus goat, they have produced a hybrid offspring capable of produce until 514.19 kg for milk yield and better milk quality in term of fats and proteins content than the Ardi and Damascus goats by itself, suggesting a good opportunity to improve the herd genetic background and increase the milk production among goat ranchers [57].
Egypt is another country of the middle east, and its coast harbor the Barki goat (Figure 2), which has evolved to live in arid zones [18]. Its genome possesses genes related to thermotolerance, body size, energy metabolism, digestive and nervous system, and immune response [18]. In a study with a lactation period of 16 weeks, the Barki and Zarabi goats have a low milk yield of around 0.7 kg/day of milk and 1.0 kg/day, in comparison with the 1.3 kg/day produced by Damascus Breed (Table 1) [58]. The crossbreeding between Zaraibi or Damascus male with Barki Dam produced an offspring that increased the milk yield to an equal or similar value of Zarabi and Damascus parental goats (Table 1) [58]. This improvement may be related to the polymorphism of the β-lactoglobulin gene [57], a molecular marker for milk production [19]. In this genotype the alleles most related to milk production in decreasing order are; A > B > C > D. Therefore, goats with A or B genotypes will produce more milk than those with C or D genotype. For example, in Damascus goat the most frequent polymorphism is AC (33%), BD(25%), BB(17%) and AA(17%), while in Zarabi goat is mainly BD(73%) and a reduced population of AC(27%), and for Barki goats is BD (73%) [59]. Therefore, using molecular markers to select those parents with A or B genotype and then identify in the offspring those with AA, BB or AB genotype, could help to adders crossbreeding strategies between Barki and Zaraibi or Damascus goats to improve the genetic background of the selected herd keeping only those kids with the AA genotype for milk production, shown in Figure 3.
Figure 3.
Example of a crossbreeding strategy assisted by β-lactoglobulin molecular markers.
Another interesting dairy goat from dryer zones is the Indian Beetal goat (Figure 2). Its lactation curve showed a milk yield of 1.2–1.3 kg/day according to the parity and doe age [60], and its milk has been used for yogurt production with good sensory and nutritional characteristics [20]. The Beetal goat, together with Kutchi and Jamunapari breeds are classified among the more productive dairy goats in India (Figure 2) [16] and considered a useful multipurpose goat for tropical and dry environments [34, 61]. Regarding the crossbreeding strategies, the crossbreed between Barbari and Beetal goat produced an offspring more productive than their parents [62]. The Barbari goat produced 0.886 kg for milk yield, meanwhile, the Barbari x Beetal crossed goat produced 1,045 kg for milk yield (Table 1) [63]. In the same way, a crossbreed between Beetal with Saanen or Alpine goats produced offspring with the same milk yield as Saanen and Alpine goats in tropical environments (291.4 kg vs. 303.1 kg), but with a shorter lactation period (230 days vs. 248.2 days) [22] (Table 1). That improvement was an advantage for local farmers because involve the same milk production but in a shortened period.
In other desert areas, the crossbreeding experiences using parental desert goat breeds and non-desert dairy goats have given different results. However, these studies have shown inconsistency in the parity, milking frequency per day, feed conditions, lactation stage, and environmental factors, making it difficult to do a fair comparative analysis between them. For example, in Sudan, the crossbred Saanen-Nubian goat produced 1.2 L (≈ 1.3 kg) per day and with only one milking per day (Table 1), with limited food, and during the second lactation period [21], while in a similar experience applying the same crossbreeding strategy (Saanen-Nubian) had an offspring able of produced 2.55 kg for daily milk yield during the second lactation period and increasing to 3.37 kg for milk yield in the third lactation period [23]. In this last study, the pure parental Saanen and Nubian breed animals produced 0.67 and 0.73 kg of milk daily, evidencing the detrimental effect of the heat stress on their milk production, and suggesting that the off spring have acquired the best adaptative traits from their Saanen and Namibia goat parental to produce high milk yield in the desert and arid conditions.
Another good experience was reported for a crossbreeding between the Sahelian and Anglo-Nubian goats. The offspring produced 1.37 kg milk per day, while the Sahelian goats only produce 0.74 kg/day, half of the hybrid milk production. Besides, this hybrid crossbred goat increased their milk quality from 4.7% to 5.8% for total lipids concentration and from 3.9% to 4.1% for total protein contents [64]. On the contrary, in Iran, the crossbreeding between local goat Mamasani and Saanen breed had a progeny able to produce 1.31 kg of milk per day, the double volume produced by the local Mamasani goat (0.65 kg per day) (Table 1). However, this progeny produced low-quality milk with reduced fat-protein contents, changing the expected 4.8% to 4.1% of fat and protein contents from 3.9% to 3.6%, respectively [24]. In Albania, the crossbreed goat between Alpine and local goats produced 30% more milk than native goats, but still was half of the milk yield of the Alpine breed and the milk quality was not evaluated [25].
In consequence, a great diversity of goat breeds well adapted for arid and desert zones are good candidates for crossbreeding plans addressed to improve the goal milk yield of the herd. However, each crossbreeding plan has to be meticulously planned and executed because diverse experiences have shown different results, some of them very successfully but others barely succeed.
3.3 The creole goats in dairy goat farming; an unexplored type
Creole goats arrives with the colonizers and was adapted to the local environment across the centuries. Genetic studies based on the polymorphism of microsatellite markers were done on goats located across the American continent and their results show that creole goat comes from Iberia and Africa and are geographically clustered [65, 66]. Their origin started in Veracruz (Mexico) and goes in three directions; to the North, to Central America passing through Panama and to the Vice Kingdom of Peru, and then to Argentina [67]. Meanwhile, the Portuguese introduced the goat in Brazil, explaining this particular genetic cluster differentiated from the rest of America [65, 66].
The Creole geographical cluster has a low diversity due to the inbreed tendency among farmers that introduced goats during the 19th century to increase the goat farming production according to European breeding programs [65]. Nevertheless, between geographically groups their different origin and admixture with different parental populations contribute to producing a high significant genetic distance among Creole groups (distance 0.16), compared with the genetic distance observed between Iberian Groups (0.05) and African groups (0.11) [66]. This genetic distance also reflects the differences regarding the adaptation against different geographic environmental conditions such as dry, hot, wet, or moisture places, selecting a goat breed well adapted to local conditions [65, 66]. Therefore, these Creole goats represent an underestimated genetic patrimony that changes according to the geographic distribution and with the threat to be lost due to the transboundary practices that replace the creole goat with common dairy goats in modern goat farming practices [66].
In Northern Chile in desert and arid zones the creole goats (Figure 2) were introduced by Spanish conquers during the XVI century and used with multi-purpose uses [68]. Throughout Chilean history, these goats were admixed with others breeds without any record and breeding plan, raising a broad diversity among Chilean creole goats [69]. In desert and arid zones, the Chilean creole goats are a robust animal, resistant to diseases, and adapted to pastoring with longer walks distances until reach the foods [69]. However, they have low milk yield of 0.2–0.9 kg/day in comparison with the milk production by Saanen goat of 1.0–2.3 kg/day under the same husbandry conditions, and the crossbreeding between Saanem and creole goats had an offspring able to produce 0.6–1.6 kg/day improving the genetic background of Chilean creole goats (Table 1) [70]. In the same way, the indigenous goats that live in Nigeria such as Sahel, Red Sokoto, and West African Dwarf have low milk yield between 0.3–0.5 kg/day (Table 1) being historically breeding for multi-purpose [26, 49]. For that reason, the creole or native goats are usually prejudged as low milk producers but without any serious studies that determine the milk yield under intensive breeding conditions.
In Greece, Italy, and India, genetics studies using molecular markers on casein genes as genetic markers for milk production, found a good potentiality for milk production in creole goats, proposing an affordable alternative for local goat farming [27, 71]. In Mexico, a study demonstrated that the milk yield of creole goats changes from 0.65 kg/day to 1.14 kg/day just moving from pasturing farming to stalled management and improved diet [72]. Thus, the potential of native and creole goats in dry local areas is still an unexplored field, and more studies about their milk yield under intensive husbandry conditions in desert and arid zones is still pending.
4. Goat milk quality
4.1 Benefits of goat Milk
Milk is a supplementary food from livestock animals like cows, goats, donkeys, and other mammals, and also is considered a rich source of carbohydrates, lipids, proteins, vitamins, minerals, and immune defense factors [28]. Cow milk is the most demanded by consumers, but goat milk has better nutritional properties enriched in vitamin A, riboflavin, growth factors, and lipids of short-chain such as; capric, caproic, and caprylic acids [28]. These lipids have better dissolution properties for serum cholesterol preventing coronary disease, cystic fibrosis, and gallstone, and can reduce body weight by promoting lipid oxidation, reducing lipogenesis, and increasing the synthesis of ketonic bodies [73]. Finally, goat milk is easily digested because has more dispersive bulbs and is recommended for milk allergic individuals for their reduced content or even lacks α-casein protein [28, 74].
4.2 Goat Milk quality
The goat milk quality is expressed in terms of sanitary, dietetic, nutritional, and technological properties, and evaluated according to their gustative, rheological, gastronomic, and hedonic features [75]. In general, the milk quality is determined according to the content of protein, lipid, and carbohydrates, among other parameters, and these concentrations are crucial for cheese production. The cheese yield depends on the protein content, while the texture, fineness, flavor, taste, and nutritional value is depending on the content of fatty acids and lipo-vitamins [75]. Environmental stress can affect the goat milk quality that finally affects the cheese quality. Saanen goats exposed to heat stress have low-quality milk with a low content of fat, protein, non-fat dry matter, and lactose [37]. However, with just a few adjustments the milk quality can be improved. The lipid profile can be modified according to the diet contents and management procedures, but protein concentration is more dependable on goat genetic background [46, 75, 76, 77, 78]. In a study with Saanen goats, the milk quality was improved after the introduction of a diet based on stoned olive cake silage modified with a lipid profile [79]. Meanwhile, in Creole goat, a new integral diet (1 kg) increases in 6% the protein and lactose content and 200% the milk volume [72]. Alpine goat fed with a diet based on alfalfa hay with different quality plus concentrates pellets did not change the total protein or casein milk concentration but modified the lipids and lactose concentration according to the diet used [80].
These fluctuations in the milk protein and lipid concentration according to diets used may be explained in terms of the relationship between the doe and the kid. In general, proteins are crucial for kid nutrition and their milk concentration remains constant adjusting protein synthesis according to the food intake rate [81]. Meanwhile, lipid content and lipid profile are dependable on gene expression and metabolic activity, and are controlled by metabolic precursors and hormones added to diets or promoted by nutritional factors that modified the rumen microflora activity [82]. In fact, the goat lipids metabolism is more complex than expected. A recent study about gene expression in mammary gland cells during a diet improvement demonstrated that lipid profiles change according to the gene expression of the protein associated with goat metabolism and protein transport, instead of genes directly related to lipids synthesis [83]. This observation encourages to do more studies to understand these correlations and the links among lipid metabolism, genetic polymorphism, and diet composition, and how this can affect the milk lipid content.
5. Molecular markers for dairy goats
5.1 General characteristic of domestic goats
The domestic goat is a livestock animal with attractive properties. A comparative genomic study reveals major differences between domestic goat breeds and their ancestor C. aegagrus, related to coat color, which is more uniform in domestic goats, and genes linked to the immune system, behavior, and reproduction, which are features related to domestication practices [84]. In another study, the complete genome annotation of a female Yunnan black goat using whole-genome optical mapping methodology found common characteristics with cattle, but more efficiency for milk secretion in goats, due to the presence of genes related to Prolactin hormone and its metabolism. Besides, an expansion in genes related to the olfactory receptor gene subfamilies was observed in goats and linked to the historical selection of a broad spectrum of forage during the expansion of goat farming. Finally, another remarkable fact is that the goat immune system has a Major Histocompatibility Complex (MHC) highly conserved with sheep and humans, suggesting an interesting animal model for immunological studies [85].
Transcriptomics analysis reveals interesting traits in goat breed for goat farming activities. In the Inner Mongolia Cashmere goats, the transcriptomic analysis reveals the expression of genes related to keratin and keratin-associated proteins of the primary and secondary hair follicles tissue that were directly associated with the goat hair phenotype [85]. Later, a gene knockout by CRISP/Cas9 technology produced modified Cashmere goats that express long secondary hair [86]. In Alpine goats, a similar transcriptomic study but using a cow microarray (there was no goat genome array available at that time) identified the gene expression associated with the animal response against food deprivation. Under this food poor condition, the milk yield was reduced to 16%, and the lactose, protein, and lipids concentration was reduced to 10%, 25%, and 45%, respectively [36]. These changes provoke a downregulation of many genes in the mammary gland cells, and some of them corresponded to casein genes, cell proliferation gene, and estrogen receptor gene, among others [36]. In this way, was possible to associate the gene expression with milk production, although still needs to be confirmed with other studies. Currently, there is a wide technology accessible to afford this challenge like those used to produce transgenic goats to synthesize human lysozyme or spider web protein and released through the milk [87, 88]. Therefore, the technology is available for improvements in goat milk production to move forward goat farming activity to produce a high volume of milk with high quality in arid and desert zones.
5.2 αS1, αS2, β, and Κ-casein polymorphism
The most abundant milk proteins are: αs1(CSN1S1), αs2 (CSN1S2), β (CSN2) and κ-casein (CSN3), β-lactoglobulin (BLG), and α-lactalbumin (LALBA) and they represent 95% of the total protein content in ruminant milk [89]. These proteins are encoded on chromosome 6 in a segment of 250 kbps [90], have different post-translation modification [91], and their milk concentration changes according to the gene expression of these casein genes [92].
These casein genes have a polymorphism within the same breed [93] and among diverse breeds [27, 90], and this biodiversity might impact the goat milk quality and milk properties in term of their role with the immune system, nutritional quality, and as raw material to produce other products derived from milk [91].
The most stronger correlation between casein polymorphism and milk quality has been described for the αS1-casein gene [89, 94, 95]. This gene has 18 alleles (represented as a capital letter) and is phenotypically grouped as “strong” with a milk yield of 3,6 g/L (A, B1, B2, B3, B4, C, H, L, M), “intermediate” with milk yield of 1.6 g/L (E, I), “weak” with milk yield of 0.6 g/L (F, G), and “null” because did not synthesize the αS1-casein protein (N, O1, O2, ON) [94, 95]. In the Sicilian goat breed Girgentana and Argentata dell etna, the “strong” alleles were identified as homozygote or heterozygote with null allele [27]. In Spanish goats, the most predominant alleles were B and E, while other goats showed different heterozygosity; Murciana-Granadina (B, E), Malagueña (E), Payoya (B, E), Canaria-Palmera (A, B), Canaria-Majorera (B, E, D + O), and Canaria-Tinerfeña (B, E, D + O) [96]. In the Malagueña goat breed, the BB genotype produces 6.94 g/L, meanwhile, EE phenotype produces 4.58 g/L [96]. In Girgentana goats, the genotypes AA not only produce more casein protein in milk (43.4 g/day) than FF genotype (25.4 g/day) but also more milk volume (1.419 kg of milk per day) than the FF (1.014 kg of milk per day) after improvements in diet nutrition [97].
Saanen and Alpine goats with the AF genotype produced more αS1-casein protein in milk than the FF genotype (4.26 g/L vs. 1.21 g/L) [98]. Meanwhile, in another study on dairy French Saanen and Alpine goats, the αS1-casein polymorphism predicted the fat and protein content but was influenced by the goat gender [99]. The authors also found that almost 65% of the Saanen goats studied were AA and AE genotypes, being biallelic for the αS1-casein gene [94]. Future studies that apply molecular techniques like PCR to identify αS1-casein polymorphism in Saanen goats, may validate the biallelic tendency, and impulse improvements in milk goat farming through selective crossbreeding strategies [99].
In the West Africa goats such as; Borno, Red Sokoto, and West African Dwarf Cameroon the most frequent alleles found are B and B′, while in the Nigerian Dwarf breed was the A, B, and B′ alleles [100]. Thus, the natural segregation for high milk production by goat farmers has promoted the dominance of certain strong and intermedia alleles in the goat herd.
Polymorphism in αs2-casein have seven alleles with three different gene expression levels: A, B, C, E and F, associated with a high expression of αs2-casein (2.5 kg/l); D allele with moderate expression (1.25 kg/l) and O (null) allele with no expression and undetected αs2-casein content [101, 102], but still inducing an allergic reaction for those people immune sensitive to milk casein proteins [103].
Variations in the β-casein gene (CSN2) locus involves ten alleles with different gene expression. Alleles A, A1, C1, E, O, O′, D, F, C, and B that has been identified from the cDNA analysis, using MS analysis, and from the electrophoretic pattern [104]. The C and F alleles are associated with low concentration or traces of β-casein protein in milk due to mutation that makes an unstable mRNA that finally reduces the protein content [104]. In consequence, this milk with low content of casein is the best option to produce infant milk formula for those kids with restricted acces to milk products due to their cow milk allergies [105].
In the case of the kappa-casein gene (CSN3), up to 21 allelic variants has been described, and according to their isoelectric point they are separated into two groups, AIEF (A, B, B´, B´´, C, C´, F, G, H, I, J, L,) and BIEF (D, E, K, M, N, O, P, Q, and R) [106]. This last group shows differences in their milk protein content according to the genotype, and the BB alleles are those with higher content of casein in the goat milk with a 2.98% [107]. In the Murciano-Granadina goat, the BB genotype had an effect on the rennet coagulation time evidencing the important role of Κ-casein in cheese production [104]. Therefore, these reports evidence the importance in identify the Κ-casein genotype in the herd to find the best goats for goat cheese production.
5.3 Single nucleotide polymorphism
The genetic polymorphism of genes related to protein content in goat milk is not only limited to casein genes. The molecular technique denominated KAS PCR (Kompetitive Allele Specific PCR) was applied on 40 genes previously identifies as molecular markers and includes; caseins genes, genes related to the immune systems, growth, proliferation, and milk production [108]. The study analyzes 48 single nucleotide polymorphisms (SNP) present across these 40 genes encoded in the genome of Alpine and Saanen goats. The study found 13 polymorphic SNPs and 4 of them were directly associated with the protein, fat, and lactose milk content. These 4 SNPs encode two interleukins receptors (Il1RN, IL15RA), one suppressor of cytokine signaling (SOC3), and a growth hormone-releasing hormone receptor (GHRHR) [108]. In this way, these casein genes and other molecular markers are currently used to study milk yield in dairy goats.
The SNPs technology consists in analyze a single nucleotide change (transition or transversion) present in a small region of selected loci in both chromosomes to identify a genotype classified as homo or heterozygous [109]. The uses of SNPs analysis in conjunction with massive sequencing or arrays technologies allow analyze hundreds or even thousands of polymorphic genes and correlated them with a specific phenotype [109]. The SNPs analysis has been successfully used in collaboration with the International Goat Genome Consortium (www.goatgenome.org) and the data reported by diverse researchers in the field have been able of creating a 52 K SNP CHIP that detects more than 50,000 SNPs in diverse goats breed [110]. The CHIP was constructed using diverse breeds as references, including milk representative types such as Saanen, Alpine, LaMancha, and Toggenburg breed, and as a meat representative to Boer and Rangeland breed, and as milk-meat representative to Nubian goat breed. Thus, the CHIP technology can be applied to diverse goat breeds, including mixed-breed [111, 112]. The CHIP allows the understanding of genetic diversity among goat breeds and their relationship with a specific productive trait [111]. In South Africa for instance, a study used the 52 K CHIP to analyzes genetically the most local representative breeds and correlated them with their adaptation characteristic to different environments. That study identified many SNPs associated with the geographical distribution and physiological adaptation to local environments [113]. A total of 205 pathways were identified after the analysis of 474 adaptive genes with significant SNPs classification. The temperature was a selective environmental factor for the most adaptive animal, and several genes linked to heat stress responses, circadian rhythms, and vascular smooth contraction were involved in this natural selection [114]. That describes a more efficient metabolism to adsorbed nutrients from food with low nutritional value, and efficient use of water sources, reducing the water loss released through the urine and feces [114]. Besides, these goats encoded genes related to better resistance against disease in comparison with other non-desert goats [114]. All these features are consistent with previous physiological studies on the goat that habitat in desert zones [31]. For example, a goat adapted for harsh environments has a small body with a high efficient metabolism rate and a functional rumen adapted to obtain a high amount of nutrients from low-grade nutritional foods [31]. Also, a desert goat can perform a high efficient nitrogen recycling system and water recycling system, allowing survival for long periods with limited sources of water and foods [31, 115]. In consequence, although for a traditional goat farmer a desert goat could look smaller and thinner than a highly efficient dairy goat, they still can produce high-quality milk under restricted diet conditions. This is important because dairy goats well adapted to arid and desert zones will not require expensive investments in farming management to improve their milk yield. The achievement of this goal supported by molecular makers and techniques currently available, would allow to afford the next challenge for goat farming in arid and desert zones, to produce high volume of high-quality milk in a current climate change scenario.
6. Conclusion
In conclusion, goats are extraordinary farming animals capable of being productive under harsher conditions, because the origin of this species comes from the middle east, a place with limited conditions to sustain life. The expansive goat dispersion across the globe associated with human migration along the centuries has generated a genetical richness superior to any other livestock farming animals, allowing its uses as a multi-purpose animal. Taking advantage of this biological diversity and current knowledge about goat physiology and genomic expression, today is possible to create crossbreeding plan that introduces goats bred from the Middle East, India, or even creole goat to produce hybrid offspring well adapted to dry or drought environments and still produce a high volume of high-quality milk. The advances and discovery of new molecular markers associated with milk yield can support breeding plan through the selection of the best parents and offspring to improve the herd genetic background and overcome the nutritional deficiency and heat stress conditions to produce high-quality milk in lands affected by desertification and without major changes in the goat farming management conditions.
Acknowledgments
The authors acknowledge to the doctoral program of Agricultura para Ambientes Áridos y Desérticos of Faculty of Renewable Natural Resources, Arturo Prat University. Juan Scopinich-Cisternas is financed by a doctoral scholarship from this doctoral program.
Conflict of interest
The authors declare no conflict of interest.
\n',keywords:"goat type, lactation, mating, Creole, molecular markers, crossbreeding, desert, arid, genomics",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/78323.pdf",chapterXML:"https://mts.intechopen.com/source/xml/78323.xml",downloadPdfUrl:"/chapter/pdf-download/78323",previewPdfUrl:"/chapter/pdf-preview/78323",totalDownloads:119,totalViews:0,totalCrossrefCites:0,dateSubmitted:"February 1st 2021",dateReviewed:"July 9th 2021",datePrePublished:"October 15th 2021",datePublished:null,dateFinished:"August 30th 2021",readingETA:"0",abstract:"Goat farming has been severely affected by Desertification, limiting their water and food resources and inducing physiological heat stress that reduces the doe milk yield. Does well adapted to heat stress would be a possible solution, but creole or indigenous goats from desert or arid areas produce between 0.5 to 1.5 L of milk per day, which is lower than the 3 L of milk per day produced by dairy goats like the Saanen breed. Nevertheless, in this chapter, we will discuss the disadvantages of introducing common dairy goats in dry places. Instead, we propose the introduction of desert goats from the Middle East or India, because they produce high-quality milk with low feed intake, making a profitable goat farming activity, and an opportunity to include crossbreeding strategies to improve the herd milk yield. Creole goats, on other hand, has been an underestimated livestock animal with a rich and unveil genetic patrimony that migth improve the herd milk yield. The effect of improved diets and extensive husbandry conditions remains unexplored in desert creole goats, and the use of advanced knowledge in goat genomics, genetic expression, and a wide variety of molecular markers can improve the studies on creole goats for crossbreeding strategies identifying the best traits involved in high-quality milk production and adaptation to dry environments. In this way, the synergy between goat type selection and molecular markers should boost goat farming in recently new desert or arid zones, counteracting the detrimental effects produced by the desertification.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/78323",risUrl:"/chapter/ris/78323",signatures:"Erwin Strahsburger and Juan Scopinich-Cisternas",book:{id:"9706",type:"book",title:"Goat Science - Environment, Health and Economy",subtitle:null,fullTitle:"Goat Science - Environment, Health and Economy",slug:null,publishedDate:null,bookSignature:"Prof. Sándor Kukovics",coverURL:"https://cdn.intechopen.com/books/images_new/9706.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-78984-709-3",printIsbn:"978-1-78984-708-6",pdfIsbn:"978-1-78985-193-9",isAvailableForWebshopOrdering:!0,editors:[{id:"25894",title:"Prof.",name:"Sándor",middleName:null,surname:"Kukovics",slug:"sandor-kukovics",fullName:"Sándor Kukovics"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Methodology",level:"1"},{id:"sec_2_2",title:"2.1 Comparison of Milk Yield in Diverse Goat Types",level:"2"},{id:"sec_4",title:"3. The dairy goat type for desertify zones",level:"1"},{id:"sec_4_2",title:"3.1 Milk production by dairy goat naturally not adapted for arid or drought zones",level:"2"},{id:"sec_5_2",title:"3.2 Milk production by dairy goat adapted to arid or drought zones",level:"2"},{id:"sec_6_2",title:"3.3 The creole goats in dairy goat farming; an unexplored type",level:"2"},{id:"sec_8",title:"4. Goat milk quality",level:"1"},{id:"sec_8_2",title:"4.1 Benefits of goat Milk",level:"2"},{id:"sec_9_2",title:"4.2 Goat Milk quality",level:"2"},{id:"sec_11",title:"5. Molecular markers for dairy goats",level:"1"},{id:"sec_11_2",title:"5.1 General characteristic of domestic goats",level:"2"},{id:"sec_12_2",title:"5.2 αS1, αS2, β, and Κ-casein polymorphism",level:"2"},{id:"sec_13_2",title:"5.3 Single nucleotide polymorphism",level:"2"},{id:"sec_15",title:"6. Conclusion",level:"1"},{id:"sec_16",title:"Acknowledgments",level:"1"},{id:"sec_19",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Chen J, Dahlin MJ, Luuppala L, Bickford D, Boljka L, Burns V, et al. Air Pollution and Climate Change: Sustainability, Restoration, and Ethical Implications. Encyclopedia of Sustainability Science and Technology. 2020. 1-48 p.'},{id:"B2",body:'Rust JM, Rust T. Climate change and livestock production: A review with emphasis on Africa. South African J Anim Sci. 2013;43(3):256-267.'},{id:"B3",body:'Scopinich-Cisternas J, Strahsburger E. Goat type: The key factor to produce goat milk with economic profitable purpose in arid and desert zones. 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Genetic polymorphism of Casein cluster in Sudan Nubian dairy goats. 1992;(Haenlein).'},{id:"B94",body:'Martin P, Bianchi L, Cebo C, Miranda G. Genetic Polymorphism of Milk Proteins. In: McSweeney PLH, Fox PF, editors. Advanced Dairy Chemistry: Volume 1A: Proteins: Basic Aspects, 4th Edition [Internet]. Boston, MA: Springer US; 2013. p. 463-514. Available from: https://doi.org/10.1007/978-1-4614-4714-6_15'},{id:"B95",body:'Marletta D, Criscione A, Bordonaro S, Guastella AM, D’Urso G. Casein polymorphism in goat’s milk. Lait [Internet]. 2007;87(6):491-504. Available from: http://www.lelait-journal.org/10.1051/lait:2007034'},{id:"B96",body:'Caravaca F, Amills M, Jordana J, Angiolillo A, Agüera P, Aranda C, et al. Effect of αs1-casein (CSN1S1) genotype on milk CSN1S1 content in Malagueña and Murciano-Granadina goats. J Dairy Res. 2008;75(4):481-484.'},{id:"B97",body:'Pagano RI, Pennisi P, Valenti B, Lanza M, Di Trana A, Di Gregorio P, et al. Effect of CSN1S1 genotype and its interaction with diet energy level on milk production and quality in Girgentana goats fed ad libitum. J Dairy Res. 2010;77(2):245-251.'},{id:"B98",body:'Grosclaude F, Mahe M-F, Brignon G, Di Stasio L, Jeunet R. A Mendelian polymorphism underlying quantitative variations of goat alpha S1-Casein. Genet Sel Evol. 1987;19(4):399-412.'},{id:"B99",body:'Carillier-Jacquin C, Larroque H, Robert-Granié C. Including α s1 casein gene information in genomic evaluations of French dairy goats. Genet Sel Evol. 2016;48(1):1-13.'},{id:"B100",body:'Caroli A, Chiatti F, Chessa S, Rignanese D, Ibeagha-Awemu EM, Erhardt G. Characterization of the casein gene complex in west african goats and description of a new αs1-Casein polymorphism. J Dairy Sci [Internet]. 2007;90(6):2989-2996. Available from: http://linkinghub.elsevier.com/retrieve/pii/S002203020770111X'},{id:"B101",body:'Ramunno L, Cosenza G, Pappalardo M, Longobardi E, Gallo D, Pastore N, et al. Characterization of two new alleles at the goat CSN1S2 locus. Anim Genet. 2001;32(5):264-268.'},{id:"B102",body:'Ramunno L, Longobardi E, Pappalardo M, Rando A, Di Gregorio P, Cosenza G, et al. An allele associated with a non-detectable amount of casein in of αS2 casein in goat milk. Anim Genet. 2001;32(1):19-26.'},{id:"B103",body:'Marletta D, Bordonaro S, Guastella AM, Falagiani P, Crimi N, D’Urso G. Goat milk with different αs2-casein content: Analysis of allergenic potency by REAST-inhibition assay. Small Rumin Res. 2004;52(1-2):19-24.'},{id:"B104",body:'Caravaca F, Ares JL, Carrizosa J, Urrutia B, Baena F, Jordana J, et al. Effects of αs1-casein (CSN1S1) and κ-casein (CSN3) genotypes on milk coagulation properties in Murciano-Granadina goats. J Dairy Res. 2011;78(1):32-37.'},{id:"B105",body:'Albenzio M, Campanozzi A, D’Apolito M, Santillo A, Mantovani MP, Sevi A. Differences in protein fraction from goat and cow milk and their role on cytokine production in children with cow’s milk protein allergy. Small Rumin Res [Internet]. 2012;105(1-3):202-205. Available from: http://dx.doi.org/10.1016/j.smallrumres.2012.02.018'},{id:"B106",body:'Prinzenberg EM, Gutscher K, Chessa S, Caroli A, Erhardt G. Caprine κ-casein (CSN3) polymorphism: New developments in molecular knowledge. J Dairy Sci [Internet]. 2005;88(4):1490-1498. Available from: http://dx.doi.org/10.3168/jds.S0022-0302(05)72817-4'},{id:"B107",body:'Chiatti F, Chessa S, Bolla P, Cigalino G, Caroli A, Pagnacco G. Effect of k-casein polymorphism on milk composition in the orobica goat. J Dairy Sci [Internet]. 2007;90(4):1962-1966. Available from: http://dx.doi.org/10.3168/jds.2006-508'},{id:"B108",body:'Kusza S, Loor J, Cziszter LT, Ilie DE, Sauer M, Padeanu I, et al. Kompetitive Allele Specific PCR (KASP TM) genotyping of 48 polymorphisms at different caprine loci in French Alpine and Saanen goat breeds and their association with milk composition. PeerJ. 2018;6:e4416.'},{id:"B109",body:'Vignal A, Milan D, San Cristobal M, Eggen A. A review on SNP and other types of molecular markers and their use in animal genetics. Genet Sel Evol. 2002;34(March):275-305.'},{id:"B110",body:'Tosser-Klopp G, Bardou P, Bouchez O, Cabau C, Crooijmans R, Dong Y, et al. Design and characterization of a 52K SNP chip for goats. PLoS One. 2014;9(1):e86227.'},{id:"B111",body:'Brito LF, Kijas JW, Ventura R V., Sargolzaei M, Porto-Neto LR, Cánovas A, et al. Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers. BMC Genomics. 2017;18:229.'},{id:"B112",body:'Mucha S, Mrode R, Coffey M, Kizilaslan M, Desire S, Conington J. Genome-wide association study of conformation and milk yield in mixed-breed dairy goats. J Dairy Sci. 2017;101(3):2213-2225.'},{id:"B113",body:'Mdladla K, Dzomba EF, Muchadeyi FC. Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations. Heredity (Edinb) [Internet]. 2018;120(4):369-378. Available from: https://doi.org/10.1038/s41437-017-0044-z'},{id:"B114",body:'Mdladla K, Dzomba EF, Huson HJ, Muchadeyi FC. Population genomic structure and linkage disequilibrium analysis of South African goat breeds using genome-wide SNP data. Anim Genet. 2016;47:471-482.'},{id:"B115",body:'Alamer M. Physiological responses of Saudi Arabia indigenous goats to water deprivation. Small Rumin Res. 2006;63:100-109.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Erwin Strahsburger",address:"erwin.strahsburger@uda.cl",affiliation:'
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The Open Access model is applied to all of our publications and is designed to eliminate subscriptions and pay-per-view fees. This approach ensures free, immediate access to full text versions of your research.
As a gold Open Access publisher, an Open Access Publishing Fee is payable on acceptance following peer review of the manuscript. In return, we provide high quality publishing services and exclusive benefits for all contributors. IntechOpen is the trusted publishing partner of over 140,000 international scientists and researchers.
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850 GBP Journal Article (Across Portfolio)
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During the launching phase journals do not charge an APC, rather they will be funded by IntechOpen.
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*These prices do not include Value-Added Tax (VAT). Residents of European Union countries need to add VAT based on the specific rate in their country of residence. Institutions and companies registered as VAT taxable entities in their own EU member state will not pay VAT as long as provision of the VAT registration number is made during the application process. This is made possible by the EU reverse charge method.
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Services included are:
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XML Typesetting and pagination - web (PDF, HTML) and print files preparation
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Discoverability - electronic citation and linking via DOI
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Permanent and unrestricted online access to your work
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What isn't covered by the Open Access Publishing Fee?
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If your manuscript:
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\\n\\t
Exceeds the number of pages defined by the publishing guidelines, an additional fee per page may be required
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If a manuscript requires Heavy Editing or Language Polishing, this will incur additional fees.
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Your Author Service Manager will inform you of any items not covered by the OAPF and provide exact information regarding those additional costs before proceeding.
\\n\\n
Open Access Funding
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To explore funding opportunities and learn more about how you can finance your IntechOpen publication, go to our Open Access Funding page. IntechOpen offers expert assistance to all of its Authors. We can support you in approaching funding bodies and institutions in relation to publishing fees by providing information about compliance with the Open Access policies of your funder or institution. We can also assist with communicating the benefits of Open Access in order to support and strengthen your funding request and provide personal guidance through your application process. You can contact us at funders@intechopen.com for further details or assistance.
\\n\\n
For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
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Added Value of Publishing with IntechOpen
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Choosing to publish with IntechOpen ensures the following benefits:
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Indexing and listing across major repositories, see details ...
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Long-term archiving
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Visibility on the world's strongest OA platform
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Live Performance Metrics to track readership and the impact of your chapter
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Dissemination and Promotion
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Benefits of Publishing with IntechOpen
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Proven world leader in Open Access book publishing with over 10 years experience
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+5,700 OA books published
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Most competitive prices in the market
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Fully compliant with OA funding requirements
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Optimized processes that assure your research is made available to the scientific community without delay
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Personal support during every step of the publication process
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+184,650 citations in Web of Science databases
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Currently strongest OA platform with over 175 million downloads
As a gold Open Access publisher, an Open Access Publishing Fee is payable on acceptance following peer review of the manuscript. In return, we provide high quality publishing services and exclusive benefits for all contributors. IntechOpen is the trusted publishing partner of over 140,000 international scientists and researchers.
\n\n
The Open Access Publishing Fee (OAPF) is payable only after your book chapter, monograph or journal article is accepted for publication.
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OAPF Publishing Options
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1,400 GBP Chapter - Edited Volume
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850 GBP Chapter - Book Series Topic (Annual Volume)
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10,000 GBP Monograph - Long Form
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4,000 GBP Compacts Monograph - Short Form
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850 GBP Journal Article (Across Portfolio)
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During the launching phase journals do not charge an APC, rather they will be funded by IntechOpen.
\n\n
*These prices do not include Value-Added Tax (VAT). Residents of European Union countries need to add VAT based on the specific rate in their country of residence. Institutions and companies registered as VAT taxable entities in their own EU member state will not pay VAT as long as provision of the VAT registration number is made during the application process. This is made possible by the EU reverse charge method.
\n\n
Services included are:
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An online manuscript tracking system to facilitate your work
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Personal contact and support throughout the publishing process from your dedicated Author Service Manager
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Assurance that your manuscript meets the highest publishing standards
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English language copyediting and proofreading, including the correction of grammatical, spelling, and other common errors
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XML Typesetting and pagination - web (PDF, HTML) and print files preparation
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Discoverability - electronic citation and linking via DOI
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Permanent and unrestricted online access to your work
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What isn't covered by the Open Access Publishing Fee?
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If your manuscript:
\n\n
\n\t
Exceeds the number of pages defined by the publishing guidelines, an additional fee per page may be required
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If a manuscript requires Heavy Editing or Language Polishing, this will incur additional fees.
\n
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Your Author Service Manager will inform you of any items not covered by the OAPF and provide exact information regarding those additional costs before proceeding.
\n\n
Open Access Funding
\n\n
To explore funding opportunities and learn more about how you can finance your IntechOpen publication, go to our Open Access Funding page. IntechOpen offers expert assistance to all of its Authors. We can support you in approaching funding bodies and institutions in relation to publishing fees by providing information about compliance with the Open Access policies of your funder or institution. We can also assist with communicating the benefits of Open Access in order to support and strengthen your funding request and provide personal guidance through your application process. You can contact us at funders@intechopen.com for further details or assistance.
\n\n
For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
\n\n
Added Value of Publishing with IntechOpen
\n\n
Choosing to publish with IntechOpen ensures the following benefits:
\n\n
\n\t
Indexing and listing across major repositories, see details ...
\n\t
Long-term archiving
\n\t
Visibility on the world's strongest OA platform
\n\t
Live Performance Metrics to track readership and the impact of your chapter
\n\t
Dissemination and Promotion
\n
\n\n
Benefits of Publishing with IntechOpen
\n\n
\n\t
Proven world leader in Open Access book publishing with over 10 years experience
\n\t
+5,700 OA books published
\n\t
Most competitive prices in the market
\n\t
Fully compliant with OA funding requirements
\n\t
Optimized processes that assure your research is made available to the scientific community without delay
\n\t
Personal support during every step of the publication process
\n\t
+184,650 citations in Web of Science databases
\n\t
Currently strongest OA platform with over 175 million downloads
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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. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. 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. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:24,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{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. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. 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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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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\r\n\tIf we aim to prosper as a society and as a species, there is no alternative to sustainability-oriented development and growth. Sustainable development is no longer a choice but a necessity for us all. Ecosystems and preserving ecosystem services and inclusive urban development present promising solutions to environmental problems. Contextually, the emphasis on studying these fields will enable us to identify and define the critical factors for territorial success in the upcoming decades to be considered by the main-actors, decision and policy makers, technicians, and public in general.
\r\n
\r\n\tHolistic urban planning and environmental management are therefore crucial spheres that will define sustainable trajectories for our urbanizing planet. This urban and environmental planning topic aims to attract contributions that address sustainable urban development challenges and solutions, including integrated urban water management, planning for the urban circular economy, monitoring of risks, contingency planning and response to disasters, among several other challenges and solutions.
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He collaborates with the Environmental Resources Analysis Research Group (ARAM), University of Extremadura (UEx), Spain; VALORIZA - Research Center for the Enhancement of Endogenous Resources, Polytechnic Institute of Portalegre (IPP), Portugal; Centre for Tourism Research, Development and Innovation (CITUR), Madeira, Portugal; and AQUAGEO Research Group, University of Campinas (UNICAMP), Brazil.",institutionString:"University of Johannesburg, South Africa and WSB University, Poland",institution:{name:"University of Johannesburg",institutionURL:null,country:{name:"South Africa"}}},editorThree:null,series:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null},editorialBoard:[{id:"181486",title:"Dr.",name:"Claudia",middleName:null,surname:"Trillo",slug:"claudia-trillo",fullName:"Claudia Trillo",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSAZHQA4/Profile_Picture_2022-03-14T08:26:43.jpg",institutionString:null,institution:{name:"University of Salford",institutionURL:null,country:{name:"United Kingdom"}}},{id:"308328",title:"Dr.",name:"Dávid",middleName:null,surname:"Földes",slug:"david-foldes",fullName:"Dávid Földes",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002nXXGKQA4/Profile_Picture_2022-03-11T08:25:45.jpg",institutionString:null,institution:{name:"Budapest University of Technology and Economics",institutionURL:null,country:{name:"Hungary"}}},{id:"282172",title:"Dr.",name:"Ivan",middleName:null,surname:"Oropeza-Perez",slug:"ivan-oropeza-perez",fullName:"Ivan Oropeza-Perez",profilePictureURL:"https://mts.intechopen.com/storage/users/282172/images/system/282172.jpg",institutionString:"Universidad de las Américas Puebla",institution:{name:"Universidad de las Américas Puebla",institutionURL:null,country:{name:"Mexico"}}}]},onlineFirstChapters:{paginationCount:34,paginationItems:[{id:"81595",title:"Prosthetic Concepts in Dental Implantology",doi:"10.5772/intechopen.104725",signatures:"Ivica Pelivan",slug:"prosthetic-concepts-in-dental-implantology",totalDownloads:22,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Current Concepts in Dental Implantology - 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\r\n\tIn general, the harsher the environmental conditions in an ecosystem, the lower the biodiversity. Changes in the environment caused by human activity accelerate the impoverishment of biodiversity.
\r\n
\r\n\tBiodiversity refers to “the variability of living organisms from any source, including terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; it includes diversity within each species, between species, and that of ecosystems”.
\r\n
\r\n\tBiodiversity provides food security and constitutes a gene pool for biotechnology, especially in the field of agriculture and medicine, and promotes the development of ecotourism.
\r\n
\r\n\tCurrently, biologists admit that we are witnessing the first phases of the seventh mass extinction caused by human intervention. It is estimated that the current rate of extinction is between a hundred and a thousand times faster than it was when man first appeared. The disappearance of species is caused not only by an accelerated rate of extinction, but also by a decrease in the rate of emergence of new species as human activities degrade the natural environment. The conservation of biological diversity is "a common concern of humanity" and an integral part of the development process. Its objectives are “the conservation of biological diversity, the sustainable use of its components, and the fair and equitable sharing of the benefits resulting from the use of genetic resources”.
\r\n
\r\n\tThe following are the main causes of biodiversity loss:
\r\n
\r\n\t• The destruction of natural habitats to expand urban and agricultural areas and to obtain timber, minerals and other natural resources.
\r\n
\r\n\t• The introduction of alien species into a habitat, whether intentionally or unintentionally which has an impact on the fauna and flora of the area, and as a result, they are reduced or become extinct.
\r\n
\r\n\t• Pollution from industrial and agricultural products, which devastate the fauna and flora, especially those in fresh water.
\r\n
\r\n\t• Global warming, which is seen as a threat to biological diversity, and will become increasingly important in the future.
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\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
\r\n\tWater is not only a crucial substance needed for biological life on Earth, but it is also a basic requirement for the existence and development of the human society. Owing to the importance of water to life on Earth, early researchers conducted numerous studies and analyses on the liquid form of water from the perspectives of chemistry, physics, earth science, and biology, and concluded that Earth is a "water polo". Water covers approximately 71% of Earth's surface. However, 97.2% of this water is seawater, 21.5% is icebergs and glaciers, and only 0.65% is freshwater that can be used directly by humans. As a result, the amount of water reserves available for human consumption is limited. The development, utilization, and protection of freshwater resources has become the focus of water science research for the continued improvement of human livelihoods and society.
\r\n
\r\n\tWater exists as solid, liquid, and gas within Earth’s atmosphere, lithosphere, and biosphere. Liquid water is used for a variety of purposes besides drinking, including power generation, ecology, landscaping, and shipping. Because water is involved in various environmental hydrological processes as well as numerous aspects of the economy and human society, the study of various phenomena in the hydrosphere, the laws governing their occurrence and development, the relationship between the hydrosphere and other spheres of Earth, and the relationship between water and social development, are all part of water science. Knowledge systems for water science are improving continuously. Water science has become a specialized field concerned with the identification of its physical, chemical, and biological properties. In addition, it reveals the laws of water distribution, movement, and circulation, and proposes methods and tools for water development, utilization, planning, management, and protection. Currently, the field of water science covers research related to topics such as hydrology, water resources and water environment. It also includes research on water related issues such as safety, engineering, economy, law, culture, information, and education.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/41.jpg",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Environmental Sciences",id:"25"},selectedSubseries:null},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 24th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:314,numberOfPublishedBooks:31,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. 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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:"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. 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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. 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