\r\n\tDigital images can be easily distorted by noise during the acquisition, processing, and transmission. Noise level is an important parameter to consider in image processing algorithms, including denoising, compression, feature extraction, motion estimation, optical flow, segmentation, super-resolution, and image quality assessment. Their performance depends on the accuracy of the noise level estimate.
\r\n
\r\n\tImage denoising is an important stage to improve the accuracy of many image processing techniques, such as image segmentation and recognition. Image segmentation is another important stage in computer vision applications. Many methodologies utilize both stages in a unique algorithm to solve the problem of the segmentation of noisy images to provide better classification and recognition compared to algorithms that independently use these two stages. \r\n\tThe goal of this book will be to collect original research chapters that develop or apply new theories and/or hardware or software to process the acquired noisy images to solve the problem of Segmentation of noisy images in the field of medical imaging, remote sensing, engineering, and other research applications.
",isbn:"978-1-83768-210-2",printIsbn:"978-1-83769-987-2",pdfIsbn:"978-1-83768-211-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"6da8427ef3062c142b4e9650a5fed534",bookSignature:"Dr. Francisco J. Gallegos-Funes",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11514.jpg",keywords:"Noisy Images, Segmentation of Noisy Images, Classification of Data, Recognition, Color, Data Sensors, Feature Extraction, Noise Level Estimate, Parameter Optimization, Automatic Segmentation, Object Detection, Edge Localization",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 5th 2022",dateEndSecondStepPublish:"July 7th 2022",dateEndThirdStepPublish:"September 5th 2022",dateEndFourthStepPublish:"November 24th 2022",dateEndFifthStepPublish:"January 23rd 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a month",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Francisco J. Gallegos-Funes received his Ph.D. in communications and electronics from the National Polytechnic Institute of Mexico in 2003. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"2868",title:"Dr.",name:"Francisco",middleName:"J.",surname:"Gallegos-Funes",slug:"francisco-gallegos-funes",fullName:"Francisco Gallegos-Funes",profilePictureURL:"https://mts.intechopen.com/storage/users/2868/images/system/2868.jpg",biography:"Francisco J. Gallegos-Funes received his Ph.D. in communications and electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. 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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
Due to both practical and theoretical reasons, the properties and the possible preparation techniques of chiral compounds are investigated in ever widening fields of research, applying various examination methods [1, 2]. It is a great challenge for some researchers if the goal is to find a simple, inexpensive, economical and also patentable preparation of a given chiral compound (single enantiomer), for example according to the demands of the industrial production or drug discovery. Although nowadays several alternative synthetic pathways can be found for the preparation of a given single enantiomer, most probably in most cases the break-up of a certain racemic composition [3], leading to the synthesis of the final product, followed by the purification of the mixture, is applied [1, 2, 4]. In most cases, mixtures of diastereomers received with appropriate resolving agents, or mixtures of enantiomers isolated thereof, have to be separated. It is common in the two separation methods, that the distribution of the mixtures between two phases, and the phase separation can be applied [4, 5, 6]. However, the phase distribution of the mixtures of chiral compounds is not linear, but the distributions follow the binary melting phase diagrams of the mixtures, or the ternary phase diagrams characteristic also for the applied solvent [7, 8].
Besides the effect of the applied solvents, the phase distribution of the mixtures is also determined by kinetic or thermodynamic control [9]. The phase distribution is also determined by the eutectic composition of the chiral molecules in the mixtures [10, 11]. The equilibrium of the supramolecular helical structures, which participate in the phase distribution, determines the formation of the phase equilibriums [12]. A remarkable consequence of the effect of the helical structures is that the mirror-image macroscopic enantiomers form not only mirror-image crystals, but by attaching together, mirror-image helical crystals are formed [13, 14]. At the same time, mainly one of the helicities can be attributed to a given enantiomer, most probably this is the reason behind the results of separations. In the followings, the most characteristic examples of the above-mentioned methods will be discussed.
2. Separation of enantiomeric mixtures without chiral reagent
2.1. Formation of macroscopically helical crystals
The enantiomeric mixtures form crystals of a given helicity corresponding to the major configuration (Scheme 1).
Scheme 1.
Purification of enantiomeric mixtures of threonine from water (ee0 ≠ 0).
In case of purification of enantiomeric mixtures of threonine was observed, that the majority of crystals have a convolution corresponding to the helical structure of the excess, while the minor enantiomer, crystallized near the excess, have the opposite convolution. The ratio between the major and minor helical crystals is in good correlation with the eutectic composition of the enantiomeric mixture of threonine. So the eutectic composition (eeEu) precipitates during evaporation, dominated by the helicity of the excess, along with the crystallization of the minor enantiomer as well.
Mirror-image crystals are formed from the supramolecular helical structures, which contain one of the enantiomer in excess. The helicity of the crystals is determined by the optical rotation of the enantiomer in excess [13, 14].
2.2. Particle-size-controlled crystallization
The ethanol solution of the conglomerate racemic trans-hydrobenzoin [15] (THB) was seeded with different amounts of (S,S)-THB and (R,R)-THB seeds of different particle size during a specified cooling program. After crystallization, the received crystals were separated to different ranges of particle size by sieving. Thus, enantiomeric mixtures of (S,S)-THB and (R,R)-THB of 83% and 87% enantiomeric excess were gained, respectively (Scheme 2) [16].
Scheme 2.
Application of particle-size-controlled crystallization for resolution.
2.3. Gravity-based enantiomer separation
According to Soloshonok et al., the SDE (self disproportionation of enantiomers) appears in three main areas: gravitational field, phase transition, and the achiral chromatography [17]. Basically, the gravity-based SDE applies the differences in crystal density. The racemate enantiomeric mixture can be considered as the mechanical mixture of the racemic and enantiopure crystals, which can have different crystal densities. This difference can be applied for the separation of the racemic and enantiopure fraction. For example, from a enantiomeric mixture of phenylalanine (Phe) having 50% enantiomeric purity, two phases of 90 and 13% enantiomeric purity, respectively, could be separated after stirring in an inert solvent of appropriate density, set between the densities of the racemic and enantiopure crystals (Scheme 3) [18, 19].
Scheme 3.
Application of density difference for the purification of enantiomeric mixtures.
Based on these results, separation of amino acid enantiomeric mixtures was carried out via density gradient ultracentrifugation, applying an iodinated gradient (Nycodenz) used in the isolation of nucleic acids and proteins. Recently, the density difference between the racemic and enantiopure Ibuprofen was utilized in an apparatus based on principle of magnetic levitation [20].
2.4. Distribution between phases, enantiomeric separation
In the case of phase transitions, the SDE phenomenon is not uniform, it highly depends on the type of the phase transition [17].
2.4.1. Fractionated crystallization
In the case of the recrystallization of enantiomeric mixtures, by plotting the enantiomeric purity of the solid phase in function of the starting enantiomeric purity, a curve similar to binary and ternary phase diagrams can be obtained (ee0-ee curve) (Scheme 4). Regarding a racemate enantiomer mixture, by recrystallizing a mixture having lower purity than the eutectic composition, in any case increased purity will be gained in the solution/melt phase, while above the eutectic composition, the enantiomeric enrichment is expected in the solid phase [2]. The recrystallization is not successful in all the cases to reach enantiomeric enrichment, for example the recrystallization experiments of the enantiomer mixtures of N-formyl-phenylalanin (N-formyl-Phe) and N-acetyl-phenylalanin (N-Ac-Phe), were unsuccessful [21].
Scheme 4.
Typical curve received from the recrystallization of a conglomerate-type enantiomer mixture (ee0-ee diagram) and an example of ee0-ee diagram for crystallization from melt [22] (upper diagrams); and a typical curve received from the recrystallization of a racemate-type enantiomer mixture (ee0-ee diagram) and an example of ee0-ee diagram for crystallization from solution (lower diagrams) [23].
A possible mechanism of the recrystallization of racemate-type enantiomeric mixtures is described by Tamura [24, 25, 26, 27, 28].
2.4.2. Distribution between solid and gas phases, enantiomer separation
In the case of mandelic acid, the vapor phase has a eutectic composition, which is independent from the composition of the starting mixture and this composition will sublimate [29]. Independently from the preparation of the starting mixture, enantiomeric mixtures of mandelic acid of 30–54% enantiomeric purity were received as sublimates (Scheme 5), which approximates well the eutectic composition determined from the binary and ternary phase diagrams of mandelic acid (eeeu: 32% [30, 31]). In the case of the sublimation of several racemate-type amino acids, the purities received in the sublimates [32, 33, 34] were identical to the eutectic compositions determined from the ternary phase diagrams [35].
Scheme 5.
Sublimation of enantiomer mixtures of mandelic acid (MA).
2.4.3. Distribution between liquid and gas phases, enantiomer separation
During the distillation of enantiomer mixtures of isopropyl-(S)-trifluorlactate (isopropyl-(S)-TLAK), the purity of the enantiomer mixtures gained in the distillate and in the residue was different from the starting composition (Scheme 6) [36, 37]. Another example for the enantiomer enrichment received by fractionated distillation is that an enantiomeric mixture of 91% enantiomer purity of N-trifluoracetyl-(S)-valine-methyl-ester (N-trifluoracetyl-Val-Me) could be further separated to two parts of 88.0 and 97.6% enantiomeric excess, respectively [38].
Scheme 6.
Separation of enantiomer mixtures by distillation.
2.4.4. Separation of enantiomeric mixtures by achiral chromatography
The SDE phenomenon prevails in the case of enantiomeric enrichment by achiral chromatography. Applying achiral stationary phase and an appropriate eluent, the enantiomeric mixtures can be separated to a polar and a less polar phase, which have different enantiomer purity from the staring composition due to the formation of homo- and heterochiral associations. For example, an enantiomeric mixture of N-acetyl-1-phenylethylamin (N-Ac-PhEA) having 71% enantiomeric excess could be further separated on silica gel stationary phase to two fractions of 99 and a 28% ee values, respectively (Scheme 7) [39].
Scheme 7.
Purification of enantiomeric mixture of N-acetyl-phenylethylamine applying achiral chromatography [45].
Such a separation was first described by Cundy and Crooks [40], but this method is applied by others as well, for the purification of enantiomeric mixtures [17, 41].
2.4.5. Separation of enantiomers by fractionated precipitation
After partial liberation of the achiral salt of the enantiomeric mixtures, the purity of the received enantiomeric mixture may be different from the starting composition. By the addition of base equivalent to the enantiomeric excess to the hydrochloric salt of the conglomerate Tisercin (Levomepromazine) (TIS) in every case the liberating enantiomeric mixture is purer than the starting composition (Scheme 8) [42, 43].
Scheme 8.
Fractionated precipitation of enantiomer mixture of Tisercin.
By the resolution of the racemic cis-permethric acid (CPA), a mixture enriched in (S,S)-enantiomer was received. Further purification of the CPA was carried out by precipitation from its Na-salt with hydrochloric acid (Scheme 9) [44].
Scheme 9.
Fractionated precipitation of cis-permethric acid.
2.4.6. Kinetic control at the fractionated precipitation
In the case of the fractionated precipitation of the enantiomer mixtures of N-propionyl-phenylalanine (N-propionyl-PhA), the curve expected from the binary phase diagram is significantly different from the received one. The crystals of the enantiomeric excess catalyze (instead of the separation of a low enantiomeric excess, expected under thermodynamic control) the separation of much higher enantiomer purity. For example, in the case of a starting composition around ee0: 20%, in the first fraction one of the enantiomers is enriched, while the second fraction will be enriched in the other one (Scheme 10) [21].
Scheme 10.
Fractionated precipitation of N-propionyl-phenylalanine.
2.4.7. Precipitation and extraction
With the combination of precipitation and extraction, for example by liberating a part of the enantiomer mixture in the mixture of water and a water-immiscible solvent, the free enantiomer will stay in the organic phase, while the salt in the water [45].
2.4.8. Precipitation and distillation
The purification of enantiomer mixtures can also be carried out by the transformation of the racemic percentage of the enantiomer mixture into solid phase as salt, followed by the distillation of the free enantiomeric excess [46, 47]. This method was applied in the case of enantiomer mixtures of salts of 1-phenylethyl-amine (PhEA) composed with nonequivalent amounts of dicarboxylic acids. By plotting enantiomer purity of the distillate and the residue in the function of the starting enantiomer purity, a diagram similar to the ee0-ee curve, received in course of recrystallizations, can be obtained, and also, the joins are in accordance with the eutectic composition of the ternary phase diagram [48].
2.4.9. Precipitation of neutral salts of dicarboxylic acid
The racemic amlodipine with the chiral dicarboxylic tartaric acid crystallizes as the neutral salt of the racemic compound from solvents, without the presence of solvates or solvate-like molecules. Consequently, in the case of enantiomeric mixtures with achiral dicarboxylic acids, the crystallization of the neutral salt of the racemic percentage seemed to be logical.
To the enantiomeric mixture of AML in solution (in acetone), achiral fumaric acid (FUM) was given in equal amount to the racemic percentage. The mixture was dissolved by heating. After cooling, the fumaric acid salt of the racemic percentage was filtered out, while the residue was evaporated, resulting in enantiopure (S)-AML and (R)-AML base, respectively. From a starting AML enantiomeric mixture of ee: 68%, reacted with 0.16 equivalent fumaric acid (equivalent to the racemic percentage), after the filtration of the precipitated crystalline neutral fumaric acid salt, (S)-AML of ee: 99.9% enantiomeric excess can be separated from the mother liquor (Scheme 11).
Scheme 11.
Purification of enantiomeric mixture of amlodipine.
3. Separation of diastereomeric mixtures (recent results)
3.1. Chiral salt of helical supramolecular structure as resolving agent (separation of diastereomeric molecular complex)
The salt of a chiral amine of supramolecular helical (double helix) structure and an achiral acid precipitates from the solvent (methanol) containing racemic alcohol as well, in the form of supramolecular helical crystals, which are composed of chiral amine, acid and one enantiomer of the racemic alcohol (Scheme 12) [49].
Scheme 12.
The salt of chiral base and achiral acid crystallizes with the appropriate enantiomer of racemic alcohol.
According to Kinbara, the most suitable resolving agent of a racemic molecule can be selected by the design of a stable hydrogen bond system [50]. Saigo et al. concluded after the analysis of several single crystals of pairs of diastereomeric salts, that the formed CH/π interactions play a significant role in the solubility difference of the diastereomers, which clearly influences the chiral recognition and thus the result of the separation [51, 52].
Others estimated well by quantum chemical computations the difference between the lattice energies of the pairs of diastereomeric salts, without preliminary knowledge on the crystal structure [53, 54]. However, it is confessed by the authors that these calculations need to be upgraded in order to be safely applicable in the search of resolving agents.
The conclusions drawn from the preparative results can facilitate the choice of the resolving agent. For example, it is already trivial, that very good separations can be reached with the application of a resolving agent of similar molecular structure (structurally related) to the racemic compound [10, 21, 55, 56, 57, 58].
3.2. Ratio of the molecules composing the diastereomer
Another approach construes the importance of the ratio of molecular lengths of the racemic molecule and the resolving agent instead of the structural similarity. According to Sakai, the author of the “space-filler concept,” the crystal-lattice of the less soluble diastereomer salt is influenced by the structural properties of the constituents of the salt (i.e., the enantiomer and the resolving agent), such as the molecular size. Sakai et al. investigated the relative molecular length of the racemic molecule and the resolving agent in course of resolutions of 1-aryl-alkylamines with 2-hydroxycarboxylic acids and vice versa (Scheme 13). Based on the results of 20 resolutions, the best separations of the racemic mixtures can be reached with the application of a resolving agent of similar molecular length [59].
Scheme 13.
Calculation of molecular length according to Sakai.
Other researchers considered the longest carbon-chain as the length of a molecule (Scheme 14). Based on the average of the results of 21 resolutions (ee, F), almost linear correlation was found between the difference of the molecular length of structurally related racemic mixtures and resolving agents, and the result of the resolution (Schemes 15 and 16) [10].
Scheme 14.
Calculation method of molecular length used by other researchers.
Scheme 15.
Average of enantiomeric excess values of enantiomeric mixtures separated from diastereomeric salt in function of the difference of molecular length.
Scheme 16.
Average of efficiency of resolution values of enantiomeric mixtures separated from diastereomeric salt in function of the difference of molecular length.
Besides the abovementioned 21 resolutions [10], carried out with structurally related resolving agents, the results of 28 additional resolutions [8, 18, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74] applying structurally nonrelated resolving agents were systematized (most of them were industrialized).
Based on the results of 49 resolutions, by plotting the average enantiomeric excess and efficiency of resolution values in function of the difference of molecular length, respectively, the following diagrams are received (Schemes 17 and 18). Accordingly, higher enantiomeric excess can be reached in case of higher difference of molecular length of the racemic compound and the resolving agent [75].
Scheme 17.
eeaverage values of 49 resolutions in function of the difference of molecular lengths (blue numbers represent the number of samples).
Scheme 18.
Faverage values of 49 resolutions in function of the difference of molecular lengths (blue numbers represent the number of samples).
4. Amino acids and their mixtures as resolving agents
4.1. Amino acid resolving agents
1-Aminoindane was successfully resolved with the application of nearly 0.5 equivalent aspartic acid (Asp) and the (R)-enantiomer was separated (Scheme 19) [76].
Scheme 19.
Resolution of Rasagilin intermediate with (S)-aspartic acid.
For the resolution of racemic acids basic amino acids were also applied, for example (S)-lysine (Lys) (Scheme 20) [77, 78].
Scheme 20.
Resolution of 2-chloro-mandelic acid with (S)-lysine.
4.2. Mixtures of amino acids as resolving agents
With the application of equivalent amount of (S)-Phe, (S,S)-AP and (S)-PG resolving agents or their mixtures in course of the resolution of racemic mandelic acid (Scheme 21), the most effective resolving agent was the (S)-PG. In the case of resolutions carried out using the mixtures of resolving agents in 1:1 ratio, the most effective combination was the mixture of (S)-Phe and (S)-PG.
Scheme 21.
Resolution of mandelic acid with the application of mixtures of resolving agents according to the Pope-Peachey half-equivalent method.
Among the half-equivalent resolving agents, (S)-Phe was the most effective, while from the half-equivalent resolving agent combinations, the mixture of (S)-Phe and (S,S)-AP was the most effective [8].
The racemic mandelic acid (MA) cannot be resolved from water with the application of (S)-Ala, however, a diastereomeric salt of ee: 23% enantiomeric excess was received using (S)-Phe as resolving agent. Applying mixtures of the two resolving agents in different ratios, (S)-MA of significantly increased enantiomeric excess could be separated from the precipitated diastereomeric mixture when the resolving agent consisted of 0.35 mol (S)-Phe and 0.65 mol (S)-Ala [8]. This is the application of the Dutch resolution method in the case of amino acid mixture resolving agents (Scheme 22).
Scheme 22.
Resolution of mandelic acid with the mixture of (S)-Phe and (S)-Ala resolving agents.
5. Presence, role, and effect on the diastereomer separation of achiral additive
5.1. Achiral additive structurally related to the racemic compound
After the resolution of N-acetyl phenylalanine (N-acetyl-Phe) with 1.0 equivalent (R)-1-phenylethylamine ((R)-PhEA), (S)-N-acetyl phenylalanine of 5% enantiomer purity could be separated from the diastereomeric salt. However, when equivalent amount of the structurally related phenoxy acetic acid (PhOAA) was given to the racemic N-acetyl-phenylalanine and this mixture was resolved with 2 equivalents of (R)-1-phenylethylamine, (S)-N-acetyl-phenylalanine of 88% enantiomeric excess was enriched in the diastereomeric salt (Scheme 23) [79].
Scheme 23.
Resolution of N-acetyl-phenylalanine in the presence of phenoxy acetic acid.
5.2. Achiral additive structurally related to the resolving agent
With the application of achiral additives, which are structurally related to the resolving agent, the efficiency of the enantiomer separations was significantly improved.
By changing the half of the phenylglycine methyl ester (PhG-Me) enantiomer resolving agent to the structurally related benzylamine (BA) in course of the resolution of N-acetyl phenylglycine (N-Ac-PhG), the enantiomer purity of the diastereomer salt of N-Ac-PhG increased by 54%, compared to the results of the 1 equivalent PhG-Me resolving agent (Scheme 24). Also in the case of 1-phenyl-ethyl amine (PhEA) resolving agent, by exchanging the half of PhEA to benzylamine, both the enantiomer purity and the efficiency of resolution values increased [79].
Scheme 24.
Resolution of N-acetyl-phenylglycine with 1-phenylethylamine and with benzylamine as achiral additive.
The resolution of racemic ibuprofen (IBU) with (R)-1-phenylethylamine ((R)-PhEA) and benzylamine (BA) as structurally related achiral additive was investigated. The unreacted enantiomer mixture of IBU was removed by scCO2 extraction from the received diastereomeric salt. The addition of the achiral benzylamine resulted in higher efficiency of resolution (FSCS) values compared to the experiments without additive (Scheme 25) [80].
Scheme 25.
Effect of benzylamine on the resolution of racemic ibuprofen by scCO2 extraction.
5.3. Additive of similar structure to the polar part of the resolving agent
Racemic 1-phenylethylamine (PhEA) was resolved with N-glutaryl-1-phenylethylamine (PhEA-GA) applying urea and its derivatives and thiourea additives of neutral character, which show structural similarity with a part of the resolving agent. Although the enantiomer purity of the PhEA received from the diastereomeric salt decreased (from ee: 62% to ee: 51–54%), the increased yields led to higher efficiency of resolution values (from F: 0.36 to F: 0.37–0.49) in all cases (Scheme 26). The urea was proven to be present in the solid phase; therefore the process of the crystallization was investigated by polarization microscopy. According to the results, the nucleation of the diastereomer salt of (S)-PhEA∙(R)-PhEA-GA starts on the surface of the initially appearing needle-like urea crystals [81].
Scheme 26.
Resolution of racemic 1-phenylethylamine in the presence of urea and its derivatives.
5.4. Application of achiral additives structurally related to amino acids [19]
The resolution of racemic mandelic acid (MA) was carried out with mixtures of amphoteric resolving agents and structurally similar achiral compounds in 1:1 ratio, namely with the mixtures of (S)-Phe and Gly, (S,S)-AP and β-Ala, and (S)-PG and GABA, respectively (Scheme 27).
Scheme 27.
Resolution of mandelic acid with the application of amphoteric achiral additives.
The results were compared to experiments carried out with the application of solely half-equivalent resolving agent. In the case of (S)-Phe, the addition of achiral glycine resulted in Δee = 15%, in the case of aspartame ((S,S)-AP), the achiral β-Ala led to Δee = 38%; while the combination of (S)-pregabalin ((S)-PG) and γ-aminobutyric acid (GABA) led to an increase of Δee = 9% in enantiomeric purity.
6. Effect of solvate forming solvents and molecules having similar structure on the results of diastereomer separation
In the case of resolution of amlodipine with (S,S)-tartaric acid ((S,S)-TA) from dimethyl-sulfoxide solvent, the dimethyl-sulfoxide solvate of (S)-amlodipine-hemi-(S,S)-tartrate salt crystallizes with high purity (Scheme 28I) [82]. The diastereomer salt enriched in (S)-amlodipine precipitates also from N,N-dimethylacetamide (DMA) solvent (Scheme 28II) [83] from 2-butanone solvent, the diastereomer salt of (S)-amlodipine crystallized applying (R,R)-tartaric acid as resolving agent (Scheme 29I) [84]. From the mixture of N,N-dimethylformamide and cosolvents, the DMF solvate of ((S)-AML)2∙(R,R)-TA crystallized, with high enantiomeric purity (Scheme 29II) [85].
Scheme 28.
Resolutions of amlodipine with (S,S)-tartaric acid.
Scheme 29.
Resolution of amlodipine with (R,R)-tartaric acid.
With the addition of urea, which has similar structure to the different solvates, to the resolving agent (S,S)-tartaric acid, from the mixture of 2-propanol and water enantiopure S-amlodipine can be received with good yield (Scheme 30) [86]. The reason of the selection of urea as additive is not explained by the inventors, but the structural similarity is easily recognizable, thus this patent can be considered as the first published form of the application of achiral additive having similar structure as the solvate.
Scheme 30.
Resolution of amlodipine with (S,S)-tartaric acid in the presence of urea.
7. Conclusion
One of the possibilities for the separation of mixtures of chiral compounds (enantiomers, diastereomers) is their nonlinear distribution between two phases. The phase-distribution depends on the starting mixture, which follows well the curves of the binary and ternary phase diagrams. The equilibrium processes between the supramolecular associates, formed from the chiral molecules, as well as the solubility equilibriums and the catalytic interactions of the formed crystals lead to the phase distribution of the mixtures. Most probably the helical structure of the associates, resulting in another mirror-image relation, determines their phase-distribution.
In the case of enantiomeric mixtures, the macroscopic manifestation of the helical associates is the formation of crystals of helical structure, related to the configuration of the enantiomer in excess. The phase-distribution is determined by the eutectic composition of one of the present chiral molecules through the effects of the solvent and the time-dependence of the phase equilibriums. The equilibriums can be affected by the partial replacement of the chiral compounds by structurally related chiral or achiral molecules.
It has a more beneficial effect, if the molecules composing the diastereomer have different size and bond lengths.
Acknowledgments
The authors thank the financial support of the Hungarian OTKA Foundation (K 124180 for E. Fogassy).
\n',keywords:"enantiomeric mixtures, resolution, eutectic composition, helical structure",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/61339.pdf",chapterXML:"https://mts.intechopen.com/source/xml/61339.xml",downloadPdfUrl:"/chapter/pdf-download/61339",previewPdfUrl:"/chapter/pdf-preview/61339",totalDownloads:2014,totalViews:982,totalCrossrefCites:2,totalDimensionsCites:2,totalAltmetricsMentions:0,introChapter:null,impactScore:1,impactScorePercentile:72,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"December 12th 2017",dateReviewed:"March 14th 2018",datePrePublished:null,datePublished:"October 10th 2018",dateFinished:"May 9th 2018",readingETA:"0",abstract:"Despite the dramatic development of enantioselective synthesis and chromatographic separation methods, optical resolution still remains the cheapest and operationally simplest method for producing pure enantiomers on a larger scale. No extreme conditions or expensive reagents are required, and the eventually expensive resolving agents can be recovered. This chapter is based mainly on the authors’ long experience in the resolution of industrially important molecules, and it presents new observations and establishments as well. Several methods for separation of chiral mixtures, enantiomeric and diastereomeric mixtures, are shown, and possibilities for predicting the efficiency of resolution based on the analysis of physico-chemical properties of the reactants are also described.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/61339",risUrl:"/chapter/ris/61339",book:{id:"6770",slug:"laboratory-unit-operations-and-experimental-methods-in-chemical-engineering"},signatures:"Emese Pálovics, Szeleczky Zsolt, Szolnoki Beáta, Bosits Miklós and\nFogassy Elemér",authors:[{id:"96278",title:"Prof.",name:"Elemér",middleName:null,surname:"Fogassy",fullName:"Elemér Fogassy",slug:"elemer-fogassy",email:"efogassy@mail.bme.hu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Budapest University of Technology and Economics",institutionURL:null,country:{name:"Hungary"}}},{id:"239488",title:"Dr.",name:"Emese",middleName:null,surname:"Pálovics",fullName:"Emese Pálovics",slug:"emese-palovics",email:"epalo@mail.bme.hu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"246451",title:"Dr.",name:"Beáta",middleName:null,surname:"Szolnoki",fullName:"Beáta Szolnoki",slug:"beata-szolnoki",email:"bszolnoki@mail.bme.hu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"246452",title:"Dr.",name:"Zsolt",middleName:null,surname:"Szeleczky",fullName:"Zsolt Szeleczky",slug:"zsolt-szeleczky",email:"zszeleczky@mail.bme.hu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"246453",title:"Mr.",name:"Miklós",middleName:null,surname:"Bosits",fullName:"Miklós Bosits",slug:"miklos-bosits",email:"bositsmiklos@gmail.com",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. Separation of enantiomeric mixtures without chiral reagent",level:"1"},{id:"sec_2_2",title:"2.1. Formation of macroscopically helical crystals",level:"2"},{id:"sec_3_2",title:"2.2. Particle-size-controlled crystallization",level:"2"},{id:"sec_4_2",title:"2.3. Gravity-based enantiomer separation",level:"2"},{id:"sec_5_2",title:"2.4. Distribution between phases, enantiomeric separation",level:"2"},{id:"sec_5_3",title:"2.4.1. Fractionated crystallization",level:"3"},{id:"sec_6_3",title:"2.4.2. Distribution between solid and gas phases, enantiomer separation",level:"3"},{id:"sec_7_3",title:"2.4.3. Distribution between liquid and gas phases, enantiomer separation",level:"3"},{id:"sec_8_3",title:"2.4.4. Separation of enantiomeric mixtures by achiral chromatography",level:"3"},{id:"sec_9_3",title:"2.4.5. Separation of enantiomers by fractionated precipitation",level:"3"},{id:"sec_10_3",title:"2.4.6. Kinetic control at the fractionated precipitation",level:"3"},{id:"sec_11_3",title:"2.4.7. Precipitation and extraction",level:"3"},{id:"sec_12_3",title:"2.4.8. Precipitation and distillation",level:"3"},{id:"sec_13_3",title:"2.4.9. Precipitation of neutral salts of dicarboxylic acid",level:"3"},{id:"sec_16",title:"3. Separation of diastereomeric mixtures (recent results)",level:"1"},{id:"sec_16_2",title:"3.1. Chiral salt of helical supramolecular structure as resolving agent (separation of diastereomeric molecular complex)",level:"2"},{id:"sec_17_2",title:"3.2. Ratio of the molecules composing the diastereomer",level:"2"},{id:"sec_19",title:"4. Amino acids and their mixtures as resolving agents",level:"1"},{id:"sec_19_2",title:"4.1. Amino acid resolving agents",level:"2"},{id:"sec_20_2",title:"4.2. Mixtures of amino acids as resolving agents",level:"2"},{id:"sec_22",title:"5. Presence, role, and effect on the diastereomer separation of achiral additive",level:"1"},{id:"sec_22_2",title:"5.1. Achiral additive structurally related to the racemic compound",level:"2"},{id:"sec_23_2",title:"5.2. Achiral additive structurally related to the resolving agent",level:"2"},{id:"sec_24_2",title:"5.3. Additive of similar structure to the polar part of the resolving agent",level:"2"},{id:"sec_25_2",title:"5.4. Application of achiral additives structurally related to amino acids [19]",level:"2"},{id:"sec_27",title:"6. Effect of solvate forming solvents and molecules having similar structure on the results of diastereomer separation",level:"1"},{id:"sec_28",title:"7. Conclusion",level:"1"},{id:"sec_29",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Fogassy E, Nógrádi M, Kozma D, Egri G, Pálovics E, Kiss V. Optical resolution methods. 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Resolution of β-aminoalcohols and 1,2-diamines using fractional crystallization of diastereomeric salts of dehydroabietic acid. Tetrahedron: Asymmetry.2003;14:3297-3300. doi.org/10.1016/j.tetasy.2003.08.033'},{id:"B58",body:'Faigl F, Schindler J, Fogassy E. Advantages of structural similaritiesof the reactants in optical resolution processes. In: Sakai K, Hirayama N, Tamura R, editors. Novel Optical Resolution Technologies, Vol. 269. Berlin Heidelberg: Springer; 2007. pp. 133-157'},{id:"B59",body:'Sakai K, Sakurai R, Nohira H. New resolution technologies controlled by chiral discrimination mechanisms. In: Sakai K, Hirayama N, Tamura R, editors. Novel Optical Resolution Technologies, Vol. 269. Berlin Heidelberg: Springer; 2007. pp. 199-231'},{id:"B60",body:'Kozma D, Fogassy E. Preparative methods for enantiomeric enrichment of non-racemic enantiomeric mixtures. Enantiomer. 1997;2:51-59'},{id:"B61",body:'Fogassy E, Ács M, Felméri J, Aracs J. Problems of optical resolution of asparagine and aspartic-acid. Periodica Polytechnica Chemical Engineering. 1976;20:248'},{id:"B62",body:'Fogassy E, Ács M, Gizur T, Harsányi K, Aracs J, Berki K, Tőke L, Jászay Z. Optical resolution of threo-2-hydroxy-3-(2-aminophenylthio)-3-(4-methoxyphenyl)-propionic acid. WO Patent 9100270. Chemical Abstracts. 1991;115:28893'},{id:"B63",body:'Nagy L, Fogassy E, Tőke L, Ács M, Árvai L, Szabó G. Resolution of alkali metal salts and lactones of racemic cis-2-hydroxycyclopent-4en-1-ylacetic acid with optically-active α-phenylethylamine. Hungarian Patent 177583. Chemical Abstracts. 1982;96:6258'},{id:"B64",body:'Fogassy E, Ács M. Process for producing 2-(4-hydroxyphenoxy)propionic acid enantiomers from enantiomer mixtures. Hungarian Patent 60226. Chemical Abstracts. 1993;118:59420'},{id:"B65",body:'Fogassy E, Simay A, Bergmann J, Faigl F, Birkás E, Mozsolits K, Szinnyei É, Török Z, Zolyomi G, Ács M. Chemical Abstracts. 1989;111:96797'},{id:"B66",body:'Fogassy E, Faigl F, Ács M. Diastereomer salts of phenylalanine and N-acyl derivatives for the separation of optically active phenylalanine and N-acyl derivatives WO Patent 8503932. Chemical Abstracts. 1986;104:168835'},{id:"B67",body:'Nagy L, Fogassy E, Faigl F, Kozsda É, Csíz L, Czudor I. Producing enantiomers of insecticidal cis- or trans-cyclopropanecarboxylic acid esters Hungarian Patent 46649. Chemical Abstracts. 1989;111:553257'},{id:"B68",body:'Fogassy E. Optically active 3-methoxy-10-(2-methyl-3 dimethylaminopropyl)phenothiazine Hungarian Patent 152208. Chemical Abstracts. 1965;63:72057'},{id:"B69",body:'Fogassy E, Ács M, Faigl F. Process for preparing optically active alpha-/formyl-amino/-beta-phenyl-propionic acids Hungarian Patent 193201. Chemical Abstracts. 1986;104:168835'},{id:"B70",body:'Bálint J, Egri G, Vass G, Schindler J, Gajáry A, Friesz A, Fogassy E. 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Processes for optical resolution of racemic 2-hydroxy-2-(2-chlorophenyl)acetic acid, and racemization of (S)-(+)-2-hydroxy-2-(2-chlorophenyl)acetic acid, for production of (R)-(-)-2-hydroxy-2-(2-chlorophenyl)acetic acid, an intermediate for clopidogrel. WO Patent 2003000636. Chemical Abstracts. 2003;138:73080'},{id:"B78",body:'Bousquet A, Musolino A. US Patent 9918110. Chemical Abstracts. 1999;130:296510'},{id:"B79",body:'Pálovics E, Schindler J, Faigl F, Fogassy E. The influence of molecular structure and crystallization time on the efficiency of diastereoisomeric salt forming resolutions. Tetrahedron: Asymmetry. 2010;21:2429-2434. doi.org/10.1016/j.tetasy.2010.09.005'},{id:"B80",body:'Molnár P, Bombicz P, Varga C, Bereczki L, Székely E, Pokol G, Fogassy E, Simándi B. Influence of benzylamine on the resolution of ibuprofen with (+)‐(R)‐phenylethylamine via supercritical fluid extraction. Chirality. 2009;21:628-636. doi.org/10.1002/chir.20655'},{id:"B81",body:'Schindler J, Egressy M, Bereczki L, Pokol G, Fogassy E, Marthi K. Enhanced efficiency due to the use of achiral additives in the optical resolution of 1‐phenylethylamine by its glutaric acid derivative. Chirality. 2007;19:239-244. doi.org/10.1002/chir.20377'},{id:"B82",body:'Lee J, Lee MS, Yang WK, Lee J-C, Choi C-J, Kim HK, Chang Y-K. Lee G. (S)-(-)-amlodipine camsylate or hydrate thereof and pharmaceutical composition comprising same WO Patent 2008010659. Chemical Abstracts. 2008;148:175751'},{id:"B83",body:'Grogan D, Bush L. Compositions comprising (S)-amlodipine and an angiotensin receptor blocker and methods of their use WO Patent 2005070462. Chemical Abstracts. 2005;143:179633'},{id:"B84",body:'Zhong N, Zhao X, Ma H. Chen. Y. A Method for the Enantiomoeric Separation of Optical Active Amlodipine WO Patent 2005054196. Chemical Abstracts. 2005;143:43779'},{id:"B85",body:'Gharpure MM, Bhawal BM, Ranade PV, Deshmukh RD, Mehta SR. Process for producing enantiomer of amlodipine in high optical purity WO Patent 2006043148. Chemical Abstracts. 2006;144:432695'},{id:"B86",body:'Jang SY, Kim S, Yun S, Bang HJ, Kim HK, Suh KH. Method for preparing (S)-(-)-amlodipine or a salt thereof and an intermediate used therein WO Patent 2008/100023. Chemical Abstracts. 2008;149:274860'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Emese Pálovics",address:"epalo@mail.bme.hu",affiliation:'
Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Budapest, Hungary
Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Budapest, Hungary
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1. Introduction
Population growth and increased demand for food have led humanity to look for new ways to increase food production. Energy, which is an essential input in agriculture, has been considered as a feasible option to increase food productivity and enhance food security. As a result, agriculture has become energy-intensive to meet increased food and biofuel demand [1].
After the green revolution, the introduction of high yield varieties and intensive crop management practices has increased the use of energy manifolds in both developing and developed countries [2, 3].
It is anticipated that energy input for crop production will increase further mainly due to population and economic growth, climate change, degrading quality of soils, and shortage of labor [4, 5]. On the other hand, intensive use of energy in crop production is posing many threats to agriculture sustainability, human health, and sustainability of the environment. Sometimes to get maximum returns farmers make overuse of energy inputs. This has led to increased energy used in crop production at a faster rate compared to other sectors. Escape of traditional practices in agriculture, technological advancements in Agri-machinery, and increased application rate of fertilizer is also responsible for increased use of energy in crop production. It is also ascribed to the introduction of high yielding varieties, and excessive use of biocides and chemical fertilizer. In addition to this diesel fuel consumption has also increased due to farm mechanization and pumping of underground water. Finally, scarcity of cultivable lands and irrigation water increased the human population, and the desire for improved living standards has also contributed to the intensive use of energy in agriculture. Both agriculture and the environment are dependent on each other and the efficient use of energy is a basic requirement for sustainable agriculture [6, 7]. Sustainable development of agriculture is dependent on high energy use efficiency with low energy use in crop production. Thus, increasing energy use efficiency in crop production is important for food security and environmental sustainability. Keeping in view the multiple interactions of agriculture with the environment, analysis of the consumption of energy (both operational and embodied) in the agriculture system is urgently needed to fight both environmental issues stemming from agriculture and climate change impacts on agriculture.
1.1 Environmental implications of input energy use in agriculture
Agriculture contributes 24% of global Greenhouse gases emission, and agricultural activities are considered a significant source of pollution [8, 9]. It is estimated that GHG emission from agriculture has doubled in the last 50 years, they could increase by another 30% by 2050 [10]. Increasing use of energy inputs in agriculture is associated with numerous environmental problems such as loss of biodiversity, pollution of the aquatic environment by chemical fertilizers and pesticides, and high consumption of non-renewable energy resources. Among all other energy inputs used in crop production, diesel fuel and fertilizers have the highest share of energy consumption [11, 12]. Studies have found that fertilizer and pesticides are among the most substantial secondary sources of CO2 emissions [8]. According to an intergovernmental panel on climate change [13]. Direct and indirect consumption of fossil fuels for crop production leads to the emission of carbon dioxide (CO2), nitrous oxide (NO2), and methane (CH4). Climate Change resulting from greenhouse gasses is the most important environmental challenges in today’s world [13]. A significant portion of these greenhouse gases is produced by agriculture. About 10–12% of all anthropogenic GHG emissions are contributed by agricultural greenhouse gasses emission [14].
The major use of commercial energy in agriculture is during the production and operation of agricultural machinery. Most of the agricultural operations like, land preparation, irrigation, fertilization, spraying, and harvesting are performed using fossil fuels. The combustion of fossil fuels in agricultural machinery releases CO2 into the atmosphere.
Excessive or over-use of fertilizers leads to loss of nutrient elements, which are main contributors to non-point source pollution from agriculture, degradation of water and soil quality, decrease in the quality of agricultural products, and increase in air emissions. Due to losses incurred by pest attacks, the use of pesticides is increasing at a higher rate. There is a 4.4% average annual growth in the use of agrochemicals worldwide [15]. This increased use of pesticides is causing air, water, and soil pollution. The increasing use of pesticides in agriculture is becoming the main environmental hazard and a major contributor to agriculture pollution. Additionally, agriculture is thought to be the major contributor of N2O by indirect and direct sources [16]. The food production system is under increasing pressure due to consistent population growth and climate change; by an increase in demand for food security while protecting the natural resources by minimizing the environmental footprints [17].
Both sustainable environment and sustainable agriculture are dependent on each other. Environmental factors have a significant contribution to agriculture; agriculture, as compared to other sectors, is more dependent on the natural environment. Agriculture is the source of food and fiber for the human being and vital for human existence; as a result, sustainable agriculture development is not just related to economic development but also human survival. Therefore, efficient use of energy is one of the conditions for sustainable agriculture [18].
1.2 Energy efficiency in agriculture
Efficient use of energy inputs helps to increase production and productivity, profitability and competitiveness of agriculture, and sustainable rural living. Higher energy use efficiency will promote sustainable agriculture by minimizing environmental problems and preventing the destruction of natural resources. The use of renewable energy sources and increase in efficiency of energy can also make a significant contribution in achieving sustainable energy development goals [19]. Currently, the world is focused to develop a production system that maintains high levels of output while minimizing the input of fossil energy and as a result, helps to reduce greenhouse gas emissions. To combat global warming, reducing emissions of greenhouse gases by minimizing the direct and indirect use of fossil fuels for crop production is a vital strategy. Energy efficiency is an essential element for achieving sustainable agricultural development. This is also important for increasing economic returns, preserving fossil fuel reserves, and sustainable agricultural production. Therefore, environmental impact assessments, energy analysis, and GHG emission assessments are important components.
2. Wheat production in Pakistan
Wheat (Triticum aestivum L.) is an important winter crop in Pakistan. Wheat significantly contributes to the livelihood and food security of the population in Pakistan, as well as at the global and regional levels. It meets about 1/5th of the daily calorie and protein requirement of human beings [20] and it constitutes 65% of staple food consumption in Pakistan. It contributes 1.7% to the national GDP of Pakistan and 8,7% to agriculture value addition. Wheat was cultivated on 8,25 Million hectares in 2019–2020 and the area under wheat has slightly decreased in the past five years. Over the years, wheat yield per acre has been stagnant or little change has been seen due to declined under-ground water table, soil degradation, environmental pollution, etc. delayed sowings, low germination rate, insect-pest infestation, and low crop stand has lowered the production efficiency of wheat. A further decline in wheat yield in recent years can be attributed to locust attacks. Keeping in view increasing population and government policies (increased support price from 1400/40 kg to 1650/40 kg before the wheat season in 2020), it is projected that farmer will divert their resource towards wheat to get maximum output from a limited quantity of arable land. The limited supply of labor on one hand and incentives for higher productivity on other hand will lead to increased use of energy in wheat production. In Pakistan, winter wheat is grown both irrigated and drylands. During winter availability of canal water is almost negligible and irrigated wheat is irrigated with groundwater. However, sustainability productivity of wheat crop is under threat due to over-exploitation of underground water. Moreover, a substantial amount of diesel fuel is used to pump water from underground, leading to significant consumption of diesel fuel energy in wheat production. On the other hand, water is a scarce resource and the water table is depleting rapidly in Pakistan. These both issues are posing a great threat to the environmental sustainability of Pakistan, as Pakistan is among the 10 most climate affected countries in the world. The worsening energy and water issue in Pakistan needs the urgent attention of policymakers.
2.1 Input energy use in wheat production
There’s substantial use of energy in wheat production both directly and indirectly. In operations like tillage, planting, and harvesting there’s a direct use of energy, while energy is indirectly used in inputs such weedicides, fertilizers, and agriculture machinery (Figure 1).
Figure 1.
System boundaries of wheat production system in Pakistan.
2.1.1 Human labor
Human labor is the most important source of the energy in agriculture, although the introduction of machines has reduced human labor in the industry in the field activities, human labor is still playing its key role. In agricultural activities, human labor is used almost at every step, from manual work on the farm, driving agricultural machinery, maintenance, fertilizer and pesticide application, irrigation, and harvesting to management. In developing countries, human power constitutes 73% of the total energy use on farms [21]. Maybe in the future with full mechanization of farms, the use of human labor will be reduced, but some scientists believe that organic and modern agriculture needs more manual work for weeding and harvesting [22, 23]. There are different estimates for the energy output of human labor on farms. The main physical activities in wheat production are driving a tractor, manual sowing, manual fertilization and spraying, harvesting, and transportation. In this study, human labor work was calculated based on the information provided by the wheat farmers on the number of hours spent in each operation. The energy equivalent of human labor is muscle power used in the field operations of crop production. The energy equivalent of human labor is 1.96 MJ/h determined from literature (Table 1). Labor energy consumption can be determined by multiplying total hours of human activity by the energy coefficients of workers. In Pakistan, where still mechanization of the farms is not so common, there is ample use of human labor in the farm operations. On average 178.45 hours of human labor is used in one hectare of wheat production.
Quantity of inputs used in wheat production in Pakistan and their energy equivalents.
2.1.2 Seed
Seed is mostly provided by seed producers and private seed companies; however, some farmers also use seeds from their farms. Wheat is planted either by seed drill or manually by spreading, the amount of seed also varies according to the sowing method. On average, 134.19 kg/ha wheat seed is used in Pakistan. Energy equivalents of the seed are the energy used in the preparation of wheat seed. Energy inputs of seed can be calculated by multiplying the quantity of seed used per hectare with its energy equivalents (8.65 MJ/kg).
2.1.3 Farm machinery
The embedded energy necessary to manufacture machinery for crop production is a tertiary input that typically has a minor impact on the total energy. Farrell et al. [24] reported that machinery accounted for only 1.7% of the total energy associated with corn production. Therefore, energy use in machinery is not included in the estimation of energy used in wheat production.
2.1.4 Fossil fuels
Diesel fuel is the main fuel used in farm machinery and water pump for different crop operations. Consumption of the fuel is dependent on several factors like climate, crop, soil, rolling assistance, and speed. In dry and warm climate use of diesel is more for irrigation than other operations, while in dry farming system diesel is mainly used in tillage and sowing as compared to irrigation. The energy output of diesel fuel was calculated by multiplying liter/ha with fuel equivalent of energy per liter. Energy equivalents of diesel fuel are 44.83 MJ/L. The average diesel fuel use is 39.98 liter/ha in wheat production.
2.1.5 Fertilizer chemical and pesticides
Soil nutrients are the most important obstacle to crop productivity. Fertilizers are used by farmers to increase soil nutrients and resultant growth. Chemical, organic, and biological fertilizers are used in crop production, but just chemical fertilizers are believed to increase the yield more than any other fertilizer. Nitrogen is the main mineral fertilizer being used in crop production. Nitrogen fertilizer is energy-intensive, on the other hand, phosphate and potash do not need high energy. Chemical and chemical fertilizers energy equivalents mean the energy consumption for production, packing, and distribution of the material. On average 177.68 kg per hectare of nitrogen nutrients, 130.17 kg phosphate nutrients, and 37.36 kg potash are used in wheat production in Pakistan. Additionally, 1.60 kg per hectare of herbicides are used in wheat production for weed management.
2.1.6 Water for irrigation
While dry-land wheat is dependent on rains, but irrigated wheat requires irrigation water throughout the production process. On average 8483.07 m3 of irrigation water is used in one hectare of wheat. The energy equivalents of the water for irrigation input is the indirect energy of irrigation consists of the energy consumed for manufacturing the material for the dams, canals, pipes, pumps, and equipment as well as the energy for constructing the walls and building the on-farm irrigation system. The energy equivalent of the irrigation was estimated to be 0.014 MJ/m3.
2.2 Energy balances in wheat production
Energy consumption in wheat production includes; labor, embodied energy in seed, chemical and fertilizers, diesel, and water for irrigation. Except water for irrigation all other input energies are same for rainfed (dry land) wheat. There’s a wide variation of input energy (Table 2), which shows high level of mismanagement in usage of energy resources among some wheat producers. This also indicates that there is great scope for improving energy consumption efficiencies of wheat producers in both farming systems. On average total input energy consumption in irrigated wheat is 49,079.27 MJ ha−1 and 31421.59 MJ ha−1 for rainfed wheat. The higher use of input energy use in irrigated wheat can be attributed to irrigation energy. Highest share of energy consumption in irrigated wheat is from chemical fertilizer (31.33%), while farmyard manure contributes highest in total input energy consumption in rainfed wheat.
Energy Inputs
Irrigated
Rain-fed
Energy equivalents MJ ha−1
SD*
Energy equivalents MJ ha−1
SD*
Human labor
402.07
166.78
259.45
163.12
Seed
2157.54
193.91
2017.93
157.72
Diesel fuel
9435.13
2697.53
5155.56
1835.76
Water for irrigation
13578.13
7578.43
—
—
Chemicals
627.10
358.56
129.87
324.53
Farmyard manure
7518.00
10767.05
12837.32
12363.56
Nitrogen
13069.26
6998.60
9437.68
6374.82
Phosphate
1702.02
675.63
1474.07
1015.25
Potash
589.68
994.91
109.69
354.96
Yield (output)
50756.79
11715.46
34427.32
20161.36
Table 2.
Energy balance in both production systems.
Standard Deviation.
In fertilizers, nitrogen constitutes the highest share, 80.39% and 82.31%, in irrigated and rain-fed wheat, respectively. Highest share of nitrogen in total fertilizer consumption is also recorded in some other countries by [25, 26, 27]. Though, nitrogen fertilizer has played key role in enhancing the food production, at the same time excessive use of nitrogen has contributed to soil, water, and air pollution in many parts of the world. Sustainability of crop production is threatened by overuse of inorganic fertilizer which inflicts severely on soil health. The need for nitrogen can be reduced by fertilization management and integrating a legume in crop rotation. In order to reduce demand for inorganic fertilizer in medium term, soil fertility and organic matter contents can be increased by applying composts, chopped residues or other soil amendments. Almost, 55% of the farmers in Punjab (Pakistan) just use inorganic fertilizers, and 30% use combination of both organic and inorganic. Furthermore, farmers use more than recommended dose of fertilizer (Zulfiqar et al. 2017). So, adopting balanced use of fertilizer by wheat producers will reduce the use of nitrogen, as nitrogen has been found to be main difference between conventional and sustainable farming system (Pimentel et al. 2005). So, consumption of nitrogen with organic fertilizer and balanced use of fertilizer will reduce energy consumption in production system and improve its productivity.
Water for irrigation is the second largest consumer of energy in irrigated wheat. Diesel fuel is used for operating machinery in wheat production, it constitutes 19.25% of the total input energy consumption in irrigated and 16.4% in rain-fed. Börjesson and Tufvesson [28] found diesel as the main energy input after fertilizer in wheat, sugar beet, canola and maize. Particularly in irrigated land where diesel is also used for ground water pumping its use is higher (9435.13 MJ ha−1) than rain-fed (1835.76 MJ ha−1). Siddiqi and Wescoat [29] reported that ground water pumping consumes 61% of direct energy in Punjab. Pumping systems are mostly dependent on fossil fuels, almost 91% of the total installed pumps use diesel driven motors.
Furthermore, share of human labor (0.81%) with amount of 402.07 MJ ha-1 in the irrigated farming system is the least in total energy consumption, followed by chemicals and seed. In rain-fed wheat share of chemical (0.4%) in total energy consumption was negligible followed by human labor and seed. The average output energy in irrigated wheat was calculated as 50756.79 MJ ha-1, and 34427.32 MJ ha-1 for rain-fed wheat farming.
2.3 Energy indices
Energy ratio which is a relationship between input and output energy is often used as an index to measure energy efficiency in crop production. Energy ratio can also be used to determine subsistence of the system in isolated societies. If ratio is lower than one, it means system is losing energy and if it is higher than one it means system is earning energy. Energy efficiency for irrigated and rain-fed wheat production is estimated to be 1.03 and 1.09, respectively (Table 3). Irrigation can be the reason for difference between two production system, higher energy efficiency for rain-fed and comparatively low for irrigated. This suggests that an efficient irrigation system will improve energy ratio in irrigated wheat. For comparisons between two production system energy efficiency may not be very good approach, because difference in energy efficiency can be due to difference in energy input and yield. Ziaei et al. [30] said that energy productivity is comparatively a better parameter to show the difference between two production systems, as it calculates the ratio of production yield per kg into consumer energy. Estimates of energy productivity shows that, for each unit of input energy (MJ) consumed in wheat, 0.07 and 0.06 yield units are achieved in rain-fed and irrigated wheat production, respectively (Table 3). This again shows that, energy is more efficiently being used in rainfed production system. Specific energy was estimated to be 12.70 and 14.49 MJ kg−1 for rain-fed and irrigated wheat production (Table 3). Lower value of specific energy shows that less amount of energy is used for production of one yield unit, as it is reciprocation of energy productivity. As a result, rain-fed is superior to irrigated wheat production from specific energy perspective also. The net energy per hectare for rain-fed and irrigated wheat production was 3005.73 and 1677.52 MJ, respectively.
=Human Labor + Seed +Water for irrigation + Farmyard manure
Non-renewable energy (NRE)
MJ ha−1
16306.67
25423.19
=Tractor + Harvester +Diesel Fuel + Herbicides + Chemical fertilizers
Total energy input
MJ ha−1
31421.59
49079.27
=NRE + RE or = DE + IDE
Table 3.
Energy indices for wheat production in Pakistan.
The distribution of input energy according to renewable and non-renewable, direct and indirect forms is important for energy analysis. In both production systems, ratios of indirect and non-renewable energy are higher than direct and renewable energy. Higher share of non-renewable energy in irrigated wheat production is due to high dependence on fossil fuels. In other words, common use of diesel driven motor for ground water pumping and higher use of chemical fertilizer is the reason for share of non-renewable energy. Penetration of electricity driven irrigation systems, efficient water management, and balanced use of fertilizer will reduce share of the non-renewable energy in agricultural systems. Moreover, investment in renewable energy system such as solar, wind etc. will improve the situation. According to [31] improvement in energy efficiency and increase in amount of renewable energy in agricultural system is very important to achieve sustainable system of food production.
3. Efficiency analysis
Traditionally input–output ratios have been used to determine efficiency. Though, input–output ratios are also helpful in explaining efficiency of the system. However recently, researchers have started applying Data Envelopment Analysis (DEA) to analyze efficiency of farmers. DEA is generalization of single-input single-output technical efficiency measure of Farrel (1957) and use multiple-input multiple-output technique to evaluate the relative efficiency of peer units with respect to multiple performance measures [32, 33]. A decision-making unit called DMU are under evaluation in DEA. A DMU is considered as efficient when no other DMU can produce more output using an equal or lesser amount of inputs [34].
3.1 Efficiency estimates
An input-oriented DEA approach was used to determine technical, pure technical and scale efficiencies of wheat farmers in both production systems. Technical efficiency of all farmers was evaluated using CCR model, and BCC model was used to determine pure technical (PTE) and scale efficiency (SE). The results from CCR and BCC model for rain-fed wheat producers in Pakistan are presented in Figure 2. It can be seen from the figure that only about 18% rainfed farmers are technically efficient. This shows that there is a considerable inefficiency between wheat producers in the study area. From efficient farmers 17% are efficient in both technical and pure technical efficiency score; this means that these farmers are globally efficient and operating at most productive scale size, on the other hand the 22% farmers are only locally efficient farmers and they have disadvantageous scale size. Additionally, 14% and 36% of the farmers have pure technical and technical efficiency score less than 0.5.
Figure 2.
Percentage distribution of TE, PTE, and SE scores of wheat producers in rainfed production system.
Efficiency scores of irrigated wheat producers are demonstrated in Figure 3. About 34% irrigated farmers are technically efficient and 42% are pure technically efficient. Among efficient farmers 90% are globally efficient and 10% are locally efficient due to scale problem. Considering CCR model 7% farmers have efficiency scores between 0.9 to less than 1 and 19% have between 0.8 to less than 0.9. On the other hand, in BCC model 13% had scores between 0 to less than 1 and 16% had between 0.8 to less than 0.9. Less than one score of the pure technical efficiency means that producer is using more energy from different sources than required [35].
Figure 3.
Percentage distribution of TE, PTE, and SE scores of wheat producers in irrigated production system.
Table 4 presents the summarized statistics for technical efficiency, pure technical efficiency and scale efficiency for wheat producer of Pakistan. The results revealed that average technical efficiency of wheat producer in rain-fed production system was 0.62 and in irrigated it was 0.82. The pure technical efficiency and scale efficiency was 0.78 and 0.67, respectively in rain-fed, and 0.87 and 0.85 in irrigated wheat production system. The technical efficiency of irrigated wheat farmers varied between 0.12 to 1 which shows that all farmers did not have knowledge of right production techniques or they were not applying at the right time. The low average values of scale efficiency in both production systems imply that the average size of the wheat farms is not equal to optimal farm size. This mean if the inefficient wheat farmers operate at optimal scale size considerable saving of energy from different sources is possible without affecting the yield level.
Particular
Rain-fed
Irrigated
Mean
SD
Min
Max
Mean
SD
Min
Max
Technical Efficiency
0.629
0.291
0.126
1
0.825
0.179
0.224
1
Pure Technical Efficiency
0.782
0.222
0.35
1
0.879
0.141
0.420
1
Scale Efficiency
0.674
0.287
0.12
1
0.869
0.161
0.230
1
Table 4.
Average efficiency of rain-fed and irrigated wheat production in Pakistan.
3.2 Input use pattern of efficient and inefficient wheat producers
The amount of physical inputs and output for 10 efficient and inefficient farmers based on CCR model in both rain-fed and irrigated wheat production system are presented in Table 5. The efficient farmers use all inputs in less amount compared to inefficient farmers in irrigated production system. While in rain-fed production system except diesel and nitrogen use of all other inputs was low for efficient farmers than inefficient. Inefficient farmers in rain-fed production system use more human labor hours by 27.78%, seed by 1.92%, FYM by 48.5%, and phosphate by 7.14%. In irrigated production system, use of inputs by efficient farmers is lower than inefficient farmers by, 28.40% for human labor hour, 11.61% for diesel fuel, 34% for chemicals, 42.85% for nitrogen, 34.6% for phosphate, 59.97% for potash and 60% for water for irrigation. Looking at output it is evident that yield of efficient farmers is higher than inefficient farmers in both production systems.
Inputs/output (unit)
Rainfed
Irrigated
10 EF (1)
10 IF (2)
Difference (%) (2–1) *100/2
10 EF (1)
10 IF (2)
Difference (%) (2–1)*100/2
A. Inputs
Human Labor (h)
80.04
110.84
27.78
184.65
257.92
28.40
Seed (kg)
133.38
136
1.92
135.88
130.91
−3.79
Diesel (l)
89.16
65.94
−35.21
140.58
159.06
11.61
Farmyard manure (kg)
25,688
49,894
48.51
0
39,520
Herbicide (kg)
0.12
0
−0.12
1.70
2.59
34.36
Nitrogen (kg)
102.91
98.84
−4.11
148.2
259.35
42.85
Phosphate (kg)
80.27
86.45
7.14
104.97
160.55
34.61
Potash (kg)
12.33
0
−12.33
49.35
123.31
59.97
Water for irrigation
—
—
—
2187.43
3033.06
27.88
B. Output
Wheat (kg)
4004.64
592.92
−575.40
3946.32
2041.20
−93.33
Table 5.
Amount of input and output for 10 efficient and inefficient wheat producers.
EF = Efficient Farmers.
IF = Inefficient Farmers.
4. Conclusions
Energy security and environmental problems due to its use are the major concern for most of the developing world. Agriculture is among the largest energy consuming sectors; this chapter was an effort to estimate energy use in wheat production which is an important staple food in Pakistan. Data on quantity of different energy inputs used in wheat production was collected through field surveys. Energy consumption in wheat was calculated by multiplying amount of inputs with their energy equivalents drawn from literature. Energy indices which are important to interpret how energy is being used were also estimated. A non-parametric data envelopment analysis technique was used to identify efficient and inefficient farmers.
In Pakistan two different wheat production systems prevail (rain-fed and irrigated). So, all estimations were performed separately for both production systems. The results of the study showed that, FYM, fertilizer, and diesel fuel has the highest share in total input energy consumption in rain-fed wheat, while in irrigated wheat fertilizer, water for irrigation, and diesel were the main energy consuming inputs. In both production systems consumption of indirect and non-renewable energy resources was higher than direct and renewable energy resources. The results of the DEA analysis revealed that, 85% of the farmers in rain-fed wheat production and 65% in irrigated wheat production were technical efficient in Pakistan. Based on BCC model the estimate of target energy use showed that there is a great scope for energy savings from various input sources. If the optimum energy requirement levels are adopted by farmers, then it would lead to increase in energy efficiency. Comparison of 10 most efficient and no-efficient farmers revealed that input usage of inefficient farmers is comparatively higher than efficient ones with no difference in yield output and size. Based on result it could be said that there is dire need for dissemination of information about best agricultural practices and economic benefits of use of inputs at recommended levels. Adoption of better agriculture technologies is highly recommended as it will result in improvement in efficiency of use of diesel and human labor. Most of the wheat is cultivated manually and majority of the farmers apply flood irrigation leading to higher use of water and diesel fuel also. Efficient management of water for irrigation would improve energy efficiency and minimize environmental impacts.
Conflict of interest
The authors declare no conflict of interest.
\n',keywords:"energy use efficiency, input–output analysis, DEA, wheat, Pakistan",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/74465.pdf",chapterXML:"https://mts.intechopen.com/source/xml/74465.xml",downloadPdfUrl:"/chapter/pdf-download/74465",previewPdfUrl:"/chapter/pdf-preview/74465",totalDownloads:313,totalViews:0,totalCrossrefCites:0,dateSubmitted:"November 22nd 2020",dateReviewed:"November 30th 2020",datePrePublished:"December 16th 2020",datePublished:"May 11th 2022",dateFinished:"December 16th 2020",readingETA:"0",abstract:"Wheat is an important staple food in Pakistan and is grown in both irrigated and rainfed production systems. To meet increased demand, farmers have increased the use of input energy in wheat production. The intensive use of energy has many consequences for energy security and environmental sustainability. In this chapter, we have analyzed the energy use efficiency of wheat crop grown in two different production systems using data collected from wheat farmers of Punjab province of Pakistan through face-to-face interviews. Energy input–output analysis revealed that 49,079 MJ/ha input energy is used in irrigated wheat and 31,421 MJ/ha in rainfed wheat. The main difference between both production systems is because of irrigation water. Fertilizer has the highest share in total energy consumption followed by diesel fuel. Energy consumed per kilogram of wheat produced is less in rainfed wheat compared to irrigated. Similarly, energy efficiency values of rainfed wheat are better than irrigated wheat. Results of data envelopment analysis reveal that 38% of wheat farmers in rainfed systems and 62% in the irrigated system are using energy efficiently. The substantial difference between the energy use of inefficient and efficient indicates that there’s a significant potential to improve energy use efficiency in both systems.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/74465",risUrl:"/chapter/ris/74465",signatures:"Muhammad Imran and Orhan Özçatalbaş",book:{id:"9670",type:"book",title:"Current Trends in Wheat Research",subtitle:null,fullTitle:"Current Trends in Wheat Research",slug:"current-trends-in-wheat-research",publishedDate:"May 11th 2022",bookSignature:"Mahmood-ur-Rahman Ansari",coverURL:"https://cdn.intechopen.com/books/images_new/9670.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-594-1",printIsbn:"978-1-83968-593-4",pdfIsbn:"978-1-83968-595-8",isAvailableForWebshopOrdering:!0,editors:[{id:"185476",title:"Dr.",name:"Mahmood-ur-Rahman",middleName:null,surname:"Ansari",slug:"mahmood-ur-rahman-ansari",fullName:"Mahmood-ur-Rahman Ansari"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"170206",title:"Prof.",name:"Dr. Orhan",middleName:null,surname:"Özçatalbaş",fullName:"Dr. Orhan Özçatalbaş",slug:"dr.-orhan-ozcatalbas",email:"orhan.ozca@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/170206/images/system/170206.png",institution:{name:"Akdeniz University",institutionURL:null,country:{name:"Turkey"}}},{id:"332065",title:"Assistant Prof.",name:"Muhammad",middleName:null,surname:"Imran",fullName:"Muhammad Imran",slug:"muhammad-imran",email:"maniuaf@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Veterinary and Animal Sciences",institutionURL:null,country:{name:"Pakistan"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 Environmental implications of input energy use in agriculture",level:"2"},{id:"sec_2_2",title:"1.2 Energy efficiency in agriculture",level:"2"},{id:"sec_4",title:"2. Wheat production in Pakistan",level:"1"},{id:"sec_4_2",title:"2.1 Input energy use in wheat production",level:"2"},{id:"sec_4_3",title:"Table 1.",level:"3"},{id:"sec_5_3",title:"2.1.2 Seed",level:"3"},{id:"sec_6_3",title:"2.1.3 Farm machinery",level:"3"},{id:"sec_7_3",title:"2.1.4 Fossil fuels",level:"3"},{id:"sec_8_3",title:"2.1.5 Fertilizer chemical and pesticides",level:"3"},{id:"sec_9_3",title:"2.1.6 Water for irrigation",level:"3"},{id:"sec_11_2",title:"2.2 Energy balances in wheat production",level:"2"},{id:"sec_12_2",title:"2.3 Energy indices",level:"2"},{id:"sec_14",title:"3. Efficiency analysis",level:"1"},{id:"sec_14_2",title:"3.1 Efficiency estimates",level:"2"},{id:"sec_15_2",title:"3.2 Input use pattern of efficient and inefficient wheat producers",level:"2"},{id:"sec_17",title:"4. Conclusions",level:"1"},{id:"sec_21",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Yuan S, Peng S, Wang B, Man J. Evaluation of the energy budget and energy use efficiency in wheat production under various crop management practices in China. Energy 160 (2018) 184-191. 10.1016/j.energy.2018.07.006.'},{id:"B2",body:'Evenson RE, Gollin D. Assessing the impact of the green revolution, 1960 to 2000. Science 2003; 300:758-62.'},{id:"B3",body:'Kazemi H, Kamkar B, Lakzaei S, Badsar M, Shahbyki M. Energy flow analysis for rice production in different geographical regions of Iran. Energy 2015;84: 390-6.'},{id:"B4",body:'Maraseni T, Chen G, Banhazi T, Bundschuh J, Yusuf T. 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Department of Economics and Business Management, University of Veterinary and Animal Sciences, Pakistan
Department of Agricultural Economics, Akdeniz University, Turkey
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He obtained his PhD degree in 2007 at the University of Pretoria.\r\nHis professional experience includes employment in the private sector as Quality Control Chemist between 1981 and 1985. He held the following positions at the University of Limpopo: Senior Laboratory Assistant (1986 to 1990); Tutor (1991 – 2003); Lecturer (2003 – 2007); Senior Lecturer (2007 - current). His fields of interest include: Plant Physiology; Plant Biotechnology and Phytochemistry. Student supervision: six completed MSc studies; and current one MSc and three PhD students.",institutionString:null,institution:{name:"University of Limpopo",institutionURL:null,country:{name:"South Africa"}}}]},generic:{page:{slug:"partnerships",title:"Partnerships",intro:"
IntechOpen has always supported new and evolving ideas in scholarly publishing. We understand the community we serve, but to provide an even better service for our IntechOpen Authors and Academic Editors, we have partnered with leading companies and associations in the scientific field and beyond.
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ALPSP
\\n\\n
\\n\\t
The Association of Learned and Professional Society Publishers (ALPSP) is the largest association of scholarly and professional publishers in the world. Its mission is to connect, inform, develop and represent the international scholarly and professional publishing community. IntechOpen has been a member of ALPSP since 2016 and has consequently stayed informed about industry trends through connecting with peers and developing jointly.
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\\n\\n
OASPA
\\n\\n
\\n\\t
The Open Access Scholarly Publishers Association (OASPA) was established in 2008 to represent the interests of Open Access (OA) publishers globally in all scientific, technical and scholarly disciplines. Its mission is carried out through exchange of information, the setting of standards, advancing models, advocacy, education, and the promotion of innovation.
\\n
\\n\\n
STM
\\n\\n
\\n\\t
The International Association of Scientific, Technical and Medical Publishers (STM) is the leading global trade association for academic and professional publishers. As a member, IntechOpen has not only made a commitment to STM's Ethical Principles.
\\n
\\n\\n
COPE
\\n\\n
\\n\\t
The Committee on Publication Ethics (COPE) provides advice to editors and publishers on all aspects of publication ethics and, in particular, how to handle cases of misconduct in research and publication. IntechOpen has been a member of COPE since 2013 and adheres to the COPE Code of Conduct and Best Practice Guidelines, ensuring that we maintain the highest ethical standards.
\\n
\\n\\n
Creative Commons
\\n\\n
\\n\\t
Creative Commons (CC) is a nonprofit organization that enables the sharing and use of creativity and knowledge through free legal tools. IntechOpen uses the CC BY 3.0 license for chapters, meaning Authors retain copyright and their work can be reused and adapted as long as the source is properly cited and Authors are acknowledged.
\\n
\\n\\n
Crossref
\\n\\n
\\n\\t
Crossref is the official Digital Object Identifier (DOI) Registration Agency for scholarly and professional publications with a goal of making scholarly communications more effective. IntechOpen deposits metadata and registers DOIs for all content using the Crossref System. IntechOpen also deposits its references and uses the Crossref Cited-by service that enables researchers to track citation statistics.
\\n
\\n\\n
Altmetric and Dimensions from Digital Science
\\n\\n
\\n\\t
Digital Science is a technology company serving the needs of scientific and research communities at key points along the full cycle of research. They support innovative businesses and technologies that make all parts of the research process more open, efficient and effective. IntechOpen integrates tools such as Altmetric to enable our researchers to track and measure the activity around their academic research and Dimensions, to ease access to the most relevant information and better understand and analyze the global research landscape.
\\n
\\n\\n
CLOCKSS
\\n\\n
\\n\\t
CLOCKSS preserves scholarly publications in original formats, ensuring that they always remain available and openly accessible to everyone.
\\n
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Counter
\\n\\n
\\n\\t
COUNTER provides the Code of Practice that enables publishers and vendors to report usage of their electronic resources in a consistent way. This enables libraries to compare data received from different publishers and vendors.
\\n
\\n\\n
DORA
\\n\\n
\\n\\t
DORA is a worldwide initiative covering all scholarly disciplines which recognizes the need to improve the ways in which the outputs of scholarly research are evaluated and seeks to develop and promote best practice. To date it has been signed by over 1500 organizations and around 14,700 individuals.
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iThenticate
\\n\\n
\\n\\t
iThenticate is the leading provider of professional plagiarism detection and prevention technology and is used worldwide by scholarly publishers and research institutions to ensure the originality of written work before publication. IntechOpen uses the iThenticate plagiarism software to ensure content originality and the research integrity of our published work.
\\n
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Enago
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IntechOpen collaborates with Enago, through its sister brand, Ulatus, one of the world’s leading providers of book translation services. Their services are designed to convey the essence of your work to readers from across the globe in the language they understand.
\\n\\t
IntechOpen Authors that wish to use this service will receive a 20% discount on all translation services. To find out more information or obtain a quote, please visit https://www.enago.com/intech
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Straive
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\\n\\t
Straive is the market leader in technology-driven solutions for the extraction, enrichment and transformation of content assets. IntechOpen publishing services are designed to meet the unique needs of Authors. As part of our commitment to that objective, we have an ongoing partnership agreement for production solutions.
\\n
\\n\\n
Amazon
\\n\\n
\\n\\t
Amazon is the world’s largest online retailer and cloud services provider. IntechOpen books have been available on Amazon since 2017, guaranteeing more visibility for our Authors and Academic Editors.
\\n
\\n\\n
DHL
\\n\\n
\\n\\t
IntechOpen has partnered with DHL since 2011 to ensure the fastest delivery of Print on Demand books.
\\n
\\n\\n
United Nations Sustainable Development Goals Publishers Compact
\\n\\n
\\n\\t
The Compact is designed to inspire action among publishers. Launched in collaboration with the International Publishers Association, the Compact aims to accelerate progress to achieve the Sustainable Development Goals (SDGs) by 2030. Signatories aspire to develop sustainable practices and act as champions of the SDGs during the Decade of Action (2020-2030), publishing books and journals that will help inform, develop, and inspire action in that direction. Learn more here
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River Valley Technology
\\n\\n
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River Valley Technology is the world’s first XML-based publishing solution from submission to peer review to production and to final hosting, giving full control to publishers, with full transparency of data.
\\n
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Figshare
\\n\\n
\\n\\t
Figshare is an online open access repository where researchers can preserve and share their research outputs, including figures, datasets, images, and videos. It is free to upload content and free to access, in adherence to the principle of open data.
The Association of Learned and Professional Society Publishers (ALPSP) is the largest association of scholarly and professional publishers in the world. Its mission is to connect, inform, develop and represent the international scholarly and professional publishing community. IntechOpen has been a member of ALPSP since 2016 and has consequently stayed informed about industry trends through connecting with peers and developing jointly.
\n
\n\n
OASPA
\n\n
\n\t
The Open Access Scholarly Publishers Association (OASPA) was established in 2008 to represent the interests of Open Access (OA) publishers globally in all scientific, technical and scholarly disciplines. Its mission is carried out through exchange of information, the setting of standards, advancing models, advocacy, education, and the promotion of innovation.
\n
\n\n
STM
\n\n
\n\t
The International Association of Scientific, Technical and Medical Publishers (STM) is the leading global trade association for academic and professional publishers. As a member, IntechOpen has not only made a commitment to STM's Ethical Principles.
\n
\n\n
COPE
\n\n
\n\t
The Committee on Publication Ethics (COPE) provides advice to editors and publishers on all aspects of publication ethics and, in particular, how to handle cases of misconduct in research and publication. IntechOpen has been a member of COPE since 2013 and adheres to the COPE Code of Conduct and Best Practice Guidelines, ensuring that we maintain the highest ethical standards.
\n
\n\n
Creative Commons
\n\n
\n\t
Creative Commons (CC) is a nonprofit organization that enables the sharing and use of creativity and knowledge through free legal tools. IntechOpen uses the CC BY 3.0 license for chapters, meaning Authors retain copyright and their work can be reused and adapted as long as the source is properly cited and Authors are acknowledged.
\n
\n\n
Crossref
\n\n
\n\t
Crossref is the official Digital Object Identifier (DOI) Registration Agency for scholarly and professional publications with a goal of making scholarly communications more effective. IntechOpen deposits metadata and registers DOIs for all content using the Crossref System. IntechOpen also deposits its references and uses the Crossref Cited-by service that enables researchers to track citation statistics.
\n
\n\n
Altmetric and Dimensions from Digital Science
\n\n
\n\t
Digital Science is a technology company serving the needs of scientific and research communities at key points along the full cycle of research. They support innovative businesses and technologies that make all parts of the research process more open, efficient and effective. IntechOpen integrates tools such as Altmetric to enable our researchers to track and measure the activity around their academic research and Dimensions, to ease access to the most relevant information and better understand and analyze the global research landscape.
\n
\n\n
CLOCKSS
\n\n
\n\t
CLOCKSS preserves scholarly publications in original formats, ensuring that they always remain available and openly accessible to everyone.
\n
\n\n
Counter
\n\n
\n\t
COUNTER provides the Code of Practice that enables publishers and vendors to report usage of their electronic resources in a consistent way. This enables libraries to compare data received from different publishers and vendors.
\n
\n\n
DORA
\n\n
\n\t
DORA is a worldwide initiative covering all scholarly disciplines which recognizes the need to improve the ways in which the outputs of scholarly research are evaluated and seeks to develop and promote best practice. To date it has been signed by over 1500 organizations and around 14,700 individuals.
\n
\n\n
iThenticate
\n\n
\n\t
iThenticate is the leading provider of professional plagiarism detection and prevention technology and is used worldwide by scholarly publishers and research institutions to ensure the originality of written work before publication. IntechOpen uses the iThenticate plagiarism software to ensure content originality and the research integrity of our published work.
\n
\n\n
Enago
\n\n
\n\t
IntechOpen collaborates with Enago, through its sister brand, Ulatus, one of the world’s leading providers of book translation services. Their services are designed to convey the essence of your work to readers from across the globe in the language they understand.
\n\t
IntechOpen Authors that wish to use this service will receive a 20% discount on all translation services. To find out more information or obtain a quote, please visit https://www.enago.com/intech
\n
\n\n
Straive
\n\n
\n\t
Straive is the market leader in technology-driven solutions for the extraction, enrichment and transformation of content assets. IntechOpen publishing services are designed to meet the unique needs of Authors. As part of our commitment to that objective, we have an ongoing partnership agreement for production solutions.
\n
\n\n
Amazon
\n\n
\n\t
Amazon is the world’s largest online retailer and cloud services provider. IntechOpen books have been available on Amazon since 2017, guaranteeing more visibility for our Authors and Academic Editors.
\n
\n\n
DHL
\n\n
\n\t
IntechOpen has partnered with DHL since 2011 to ensure the fastest delivery of Print on Demand books.
\n
\n\n
United Nations Sustainable Development Goals Publishers Compact
\n\n
\n\t
The Compact is designed to inspire action among publishers. Launched in collaboration with the International Publishers Association, the Compact aims to accelerate progress to achieve the Sustainable Development Goals (SDGs) by 2030. Signatories aspire to develop sustainable practices and act as champions of the SDGs during the Decade of Action (2020-2030), publishing books and journals that will help inform, develop, and inspire action in that direction. Learn more here
\n
\n\n
River Valley Technology
\n\n
\n\t
River Valley Technology is the world’s first XML-based publishing solution from submission to peer review to production and to final hosting, giving full control to publishers, with full transparency of data.
\n
\n\n
Figshare
\n\n
\n\t
Figshare is an online open access repository where researchers can preserve and share their research outputs, including figures, datasets, images, and videos. It is free to upload content and free to access, in adherence to the principle of open data.
\n
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. 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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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He also has an honorary appointment to serve as a Collaborative Professor at Kanazawa University, Japan, from Mar 2015 to the present. \nFormerly, Dr. Rahman was a faculty member of the University of Chittagong, Bangladesh, affiliated with the Department of Chemistry (Oct 2002 to Mar 2012) and the Department of Applied Chemistry and Chemical Engineering (Mar 2012 to Sep 2015). Dr. Rahman was also adjunctly attached with Kanazawa University, Japan (Visiting Research Professor, Dec 2014 to Mar 2015; JSPS Postdoctoral Research Fellow, Apr 2012 to Mar 2014), and Tokyo Institute of Technology, Japan (TokyoTech-UNESCO Research Fellow, Oct 2004–Sep 2005). \nHe received his Ph.D. degree in Environmental Analytical Chemistry from Kanazawa University, Japan (2011). He also achieved a Diploma in Environment from the Tokyo Institute of Technology, Japan (2005). 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. 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. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. 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Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. 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\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
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Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 16th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:124,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
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Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. 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In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. 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The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",annualVolume:11402,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",editor:{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",fullName:"Shailendra K. 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