Notation of the synthesis system.
\r\n\t2. Animal and vegetal protein hydrolysates
\r\n\t3. Macroalgae seaweeds extracts
\r\n\t4. Beneficial microorganisms, etc.
\r\n\tThe elucidation of the agricultural function (i.e. improving nutrient use efficiency, quality, and tolerance to abiotic stresses) and action mechanisms of PBs will permit to develop a second generation of PBs where synergies and complementary mechanisms can be functionally designed to feed the future.
",isbn:"978-1-80355-553-9",printIsbn:"978-1-80355-552-2",pdfIsbn:"978-1-80355-554-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"4c1b31fff4d04b36466a40927904f210",bookSignature:"Dr. Vijay Singh Meena, Dr. Hanuman Prasad Parewa and Dr. Sunita Kumari Meena",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11327.jpg",keywords:"Ecological Diversity, Mutualistic Symbiosis, Temperatures, Frost, Salinity, Acidity, Nutrients, Water, Crop Yield, Grain, Straw, Biofortified",numberOfDownloads:88,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 21st 2021",dateEndSecondStepPublish:"December 1st 2021",dateEndThirdStepPublish:"January 30th 2022",dateEndFourthStepPublish:"April 20th 2022",dateEndFifthStepPublish:"June 19th 2022",remainingDaysToSecondStep:"6 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Vijay Singh Meena has worked in various aspects of soil aggregation, carbon management index as well as carbon and nitrogen sequestration potential under climate-resilient agriculture. He identified the carbon management index as the key indicator to measure soil degradation in different agro-ecosystems. He has edited 10 books on microbes, organic farming, and agricultural sustainability and received several scholarships and awards during his academic and professional career.",coeditorOneBiosketch:"Dr. Hanuman Prasad Parewa has specialized in the field of soil fertility, INM, and plant growth-promoting rhizobacteria. His research revealed that integrated application of fertilizer, FYM and bio inoculants highly effective for sustainable wheat and Mung bean production and soil quality.",coeditorTwoBiosketch:"Dr. Sunita Kumari Meena has previously served as a research scholar at both Banaras Hindu University, Varanasi, and at ICAR-Indian Agricultural Research Institute, New Delhi. She has published in the Journal of Cleaner Production, Ecological Engineering, Scientia Horticulturae, Environmental Science and Pollution Research and Biocatalysis and Agricultural Biotechnology.",coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"350226",title:"Dr.",name:"Vijay",middleName:"Singh",surname:"Meena",slug:"vijay-meena",fullName:"Vijay Meena",profilePictureURL:"https://mts.intechopen.com/storage/users/350226/images/system/350226.png",biography:"Vijay Singh Meena is currently working as a Project Coordinator (Soil Scientist) at CIMMYT-BISA, Pusa, India. His previous position includes that of Scientist (Soils) at the Indian Council of Agricultural Research (Indian equivalent to USDA-ARS). He has worked in various aspects of soil aggregation, carbon management index and carbon and nitrogen sequestration potential under climate resilient agriculture. He identified carbon management index as the key indicator to measure soil degradation in different agro-ecosystems. His research revealed that the application of FYM and vermicompost along with vegetative barrier across the slope are highly effective in sustaining the soil quality. Dr. Meena and his team identified that the combined application of organic and inorganic sources is important in sustaining the productivity of soils and prevent soil erosion. He is instrumental in the preparation and distribution of > 4000 soil health cards to different farmers. Dr. Meena and his team reported that the long-term judicious application of organic and mineral fertilizer positively influenced soil aggregation, carbon distribution, water stable aggregates, maize and wheat yields and reduced the runoff and soil loss (without fertilization) and recommended the dose of fertilizers. The concept of CMI was found to be effective in assessing the best nutrient management practices in sloppy crop lands as it showed significant correlation with yield, runoff and soil loss. The estimation of CMI values of any fertilization management can indicate the soil degradation status quantitatively thus helpful in mitigating land degradation in the hilly agro-ecosystem.\nHe also edited seven Springer books and three Elsevier books on microbes, organic farming and agricultural sustainability. He has received several scholarship and awards during his academic and professional career. 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The development of weed biocontrol is stimulated due to their increasing resistance to chemical herbicides and slow down development of novel herbicidal active components with new mode of action [1]. There are a few mycoherbicides among biopesticides registered in the last years [2].
Despite biocontrol efficacy is generally lower than application of pesticides, biologicals have some advantages over chemicals: (1) biopesticides can be used for resistance management, especially since may have multiple modes of action, which would reduce the chance of resistance occurring in a particular crop pest; (2) many biopesticides have no or low restricted entry intervals, meaning that post-application, restricted entry into the field is very low and there are often no limitations prior to harvest and (3) there are generally exemptions of biopesticides from maximum residue limits because they are considered acceptable and relatively safe [3].
More than half a century had passed since the first mycoherbicide was registered. Dispute raged, and still rages today, about whether “Have bioherbicides come of age?”, “What is they really contribution to crop protection?” or “Athletes foot or Achilles heel?” [4, 5, 6, 7, 8, 9]. This is partly because the biological herbicides as distinct from chemical preparations are not “stand alone” products. There are significant differences in their origins (biological vs. chemical), modes of action (multiple vs. singular), manufacturing methods (fermentation vs. synthesis), requirements to storing and application conditions, etc. [10]. Efficacy of mycoherbicide strategy depends on thorough understanding of host-pathogen-environment interactions. The biological herbicides are more effective when they are incorporated into integrated weed management programs [11]. For example, it was demonstrated that the bioherbicide
Currently, it highlighted 18 of the most serious weeds in agriculture and 50 troublesome ones in cultivated crops, pastures and waterways [11]. Mycoherbicides are mainly used to prevent and control the spread of such worst parasitic weeds as
Key features of mycoherbicides are host specificity, crop tolerance, efficacy, environmental fate, temperature and moisture spectrum, mode of action and toxicology [23]. It is important to realize that not only the choice of the strain, but also types of propagules (conidia, mycelium, sclerotia, etc.), production and application method is influenced by mycoherbicide features. Fungal propagules are influenced by a number of environmental factors (temperature, humidity etc.) that affect their biocontrol efficacy. It was demonstrated that the propagules’ choice, formulation and application strategy potentially reduce the dew period requirement [24, 25]. Another possible approach would be a manipulation with fermentation conditions up to product infection materials with set-up parameters [7, 26]. Similarly, during fungal growth physical, chemical and nutritional conditions can be altered to manipulate endogenous reserves for production of propagules with improved stress tolerance to abiotic factors and virulence to host [7, 27, 28, 29]. Depending on production method conidia significantly differ by the content of compatible solutes and resistance to environmental influences. The maximum difference is observed when comparing conidia obtained on artificial nutrient media and in nature [28, 30].
Despite of considerable progress in technologies of production and application of mycoherbicides, biopesticides for control of phytophagous insects and plant pathogens have showed much higher commercial success. In some cases, the useful experience for development commercially viable mycoinsecticides and mycofungicides can be tested for the improvement of potential mycoherbicides. For this reason, in this review we analyzed the approaches for producing both mycoherbicides and other types of biopesticides based on fungi.
Various kinds of fungal propagules often fulfill different purposes. In nature, the typical infectious propagules of the pathogenic Ascomycetes are the aerial conidia that facilitate distribution and spreading of these fungi. Generally, aerial conidia can be cost-effectively produced under laboratory conditions [31]. Blastospores, submerged (microcycle) conidia, sporogenically competent mycelia and microsclerotia may be used as the infectious agents as well. They often have a higher survival capability as well as the increased genetic diversity, which probably enhances survival in unstable environments [32, 33]. The morphological and physiological features of submerged conidia can significantly differ from properties of aerial conidia produced by a solid-state culture. For example, submerged conidia and blastospores of
However, a few of successful field experiments with microsclerotia-based mycoinsecticide were described. The field efficacy of solid and liquid formulations of microslecrotia
High spore density (about 1012–1014 CFU per ha) is required for use of mycoherbicides in the field. Therefore, one of the main technological goals is to obtain cost-effective, viable and aggressive infectious material [3, 26]. The secondary use of substrates is a solution of their decontamination and utilization. For example, multi-step waste wood bio-recycling includes the cultivation of
The loss of viability of the infectious material is usually observed during its drying and storage. Moreover, in nature, the combination of temperature and humidity optimal for rapid germination of fungal spores is relatively rare. Germination of spores can be also suppressed by the action of solar irradiation. Thus, the techniques and conditions for cultivation of biocontrol fungi and the selection of the nutrient media composition should be directed both to reach high biomass yields and to improve their activity in the field [63, 64].
There are several approaches to improve fitness of biocontrol fungi: strain selection, optimization of media composition, addition protectors (compatible solutes such as trehalose, sucrose, glycine-betaine, etc.) and treatment of growing cultures with sub-lethal doses of stress factors (e.g. oxidative stress and temperature) [26, 65, 66]. However, on the practice sub-optimal water activity of the substrates are widely used and helpful [67, 68].
Propagules can be produced by solid-state and liquid fermentation or two-phase system.
LSF is the most commonly used technology for microbial inoculum production. Collego and DeVine, the first commercially produced bioherbicides, had been manufactured this way. The ability to fully control the cultivation process and its relatively short duration (several days) is an undoubted advantage of LSF over solid-state fermentation. The composition of a culture medium is an important parameter in the biotechnological process because it is 30–40% of the production costs. A commercial LSF medium for
To obtain a high yield of viable and stress tolerant infectious material, the composition of the liquid nutrient medium requires optimization. Its algorithm can include three main steps: (1) selection of the basal medium with a set of vitamins and trace elements, on which the fungus grows and/or sporulate well; (2) selection of carbon and nitrogen sources and their optimal concentration and ratio determination and (3) replacement of artificial carbon and nitrogen sources by cheap natural ones [72]. Application of factorial design and response surface methods were successfully used to optimize the growth parameters required for large scale conidia production of potential mycoherbicides based on
To obtain high titers of
The liquid nutrient medium tonicity has a significant effect on the yield and quality of propagules. Sporulation of
Non-optimal carbon sources also stimulated
At the same time, liquid substrates are uncommon one for fungal growth.
Solid-state fermentation is the most suitable for cultivation of fungi because their habitats are chiefly solid substrates. In fact, SSF imitates the yields aerial conidia as the final product of conidiation processes. For example, 98% of marine fungi were isolated from submerged solid substrates [82]. In the most cases, spore yields and viability are higher than they are produced by SSF [83]. Hydrophobic air conidia are best suitable for oil formulations, since prolong the conidial viability and decreases UV radiation sensitivity [84, 85, 86]. Indeed, numerous studies have shown that conidia produced in an SSF culture are tolerant toward environmental factors (dehydration, drop of temperature and solar irradiation) than spores obtained by SmF [87]. Conidia and blastospores are the main infective units used in biological control with entomopathogenic fungi. There is no absolute advantage between both infective units. However, most formulations of mycoinsecticides are based on aerial conidia obtained in solid-state culture, since these propagules are more resistant to abiotic factors found in open fields [88].
A polysaccharide matrix often surrounds the spores produced by SSF and protects them during desiccation opposite the spores produced by LSF [89]. The choice of substrate, its humidity and growing time also affect the quality of propagules [90]. For example, dried conidia of Colletotrichum truncatum produced on vermiculite tended to retain efficacy during storage better than spores recovered from perlite culture [91]. Sometimes the fermentation can be terminated after the fungus has penetrated the nutritive substrate but before conidiation has begun [92, 93]. Dried grain kernels colonized by
In the case of small manufacturers, the propagules traditionally produced in the plastic bottle or perforated polypropylene carrier bags [95, 96]. This process was the first designed to meet the biological requirements of genus
It is well known the positive effect of near ultraviolet radiation on sporulation of certain phytopathogenic fungi from genera
Naturally occurring substances can be applied for bioherbicide production [106, 107]. SSF allows to obtain bioherbicides utilizing the agroindustry waste such as bagasse, soybean bran and corn steep liquor [108].
Biological material produced by fermentation and separation from a substrate as a rule cannot be stored for a long time. Even at a low temperature of the storage fungal spores, the mycelium can germinate slowly under appropriate wetness that is unpromising without a plant substrate. Many locally produced biopesticides should be used within several weeks after fermentation was finished as DeVine™, a mycoherbicide based on spores of
At the high-productivity biotech companies, the microorganisms should be stabilized to prevent germination of propagules for a long time (months, years). This can be achieved basically by concentration, drying or encapsulation of biomaterial on polymer layer and storage under appropriate conditions. In the ideal situation, the modern biopesticides can be stored not less than 2 years at the temperature 4°С, 3 months at 30°C and several days at 40–50°С [64].
There are quite simple and cheap techniques of stabilization and storage of some microorganisms. For instance, infection material of
It is well known that fungal growth and development are depend on temperature, free water availability, pH and oxygen concentration. For stabilization of the fungal propagules, these factors are manipulated by lowering pH, water activity, temperature and oxygen concentration [67, 68].
In many fungi, spores or spore matrix contains the inhibitors that prevent their germination in fruiting bodies, conidiomata, pustules even at the favorable wetness and temperature. These compounds isolated from some rust and anthracnose fungi were demonstrated to be fungistatic [111, 112, 113, 114, 115]. Probably, they can be used as natural preservatives and for stabilization of spores of biocontrol fungi.
Spores of many different fungi aggregated in conidiomata can survive over a season and longer under stress and varied environmental conditions including drying, UV-irradiation and low winter temperature. As a rule, such spores are pigmented or/and surrounded by thin shell (as teliospores of rust and smut fungi) or incorporated into spore matrix (as in coelomycetous fungi). Chemical analysis of the matrix in
Protective compounds, such as pigments and compatible solutes, in fungal cells as well thickness of cell wall and plasma membrane lipid composition play important role in their resistance to artificial drying. Pigments, especially phenolic ones, utilize reactive oxygen species (ROS) which production is induced in drying process [28, 46]. Taking in account this consideration protective compounds are added to the biomaterial (at the concentration about 5–20%) before drying to prevent deleterious effects of ROS and to regulate osmotic pressure. Dried biomass should be stored at the darkness and lower oxygen concentrations. The rehydration is the important step too. It should be gradual and be made in wet atmosphere, warm water (30–37°C) in order to prevent the injury of fungal plasma membranes [46, 118].
The preparation of the concentrated suspensions or emulsions, pastes with addition of preservatives (germination inhibitors, antibiotics, etc.) is the simple techniques of stabilization and storage of fungal propagules, especially, if the it sensitive to drying.
A liquid formulation of the biofungicide was developed on the base of the yeast
Some components of emulsion concentrates (for instance, plant or paraffinic oils) affect efficacy of biopesticides including mycoherbicides. They prevent fast water evaporation from spray droplets and improve thermotolerance of fungal cells as it was shown for
The mycelium of
The drying is the most popular technique of inoculum stabilization. Besides simple drying by warm heat on trays (convection drying), spray drying, fluid bed drying and lyophilisation (freeze-drying) are used. The selection of the drying technique depends on availability, costs and sensitivity of the biomaterial.
The biomaterial mixed with preservatives and fillers is dried on trays in thin layer. This technique is used for production of the biofungicide
In some inoculum stabilization protocols, convection drying was proposed for formulation of conidia and microsclerotia of
The drying technique “Stareze” is based on the addition of a membrane stabilizer (sucrose) during the fermentation. High concentration of sucrose (400 g/L) was added to 96-h submerged culture of
The spore suspension with some adjuvants and additives is sprayed in heated air followed by fast drying (5–30 s). In the case of fluid bed drying, the suspension follows to the bed from dried material babbling by air that forms pseudo-boiling layer. Particles of the drying material stick to gradually form granules (www.niroinc.com).
Submerged conidia of
A method was developed for microencapsulation of
Under liophylisation, water vapors from ice under low pressure bypass the liquid state. Conidia of
Concentrated biomaterial can be incorporated into different polymer matrices that protect fungal cells from effects of some factors such as UV-irradiation and microbial contamination. Products that are resulted from encapsulation process include gel, granules, capsules and microcapsules. There are various industrial equipment for their production [134].
The process is based on the polymerization of sodium alginate in the solution calcium chloride. For instance, the suspension of the biomaterial (1 part) is mixed with sodium alginate (1.3% solution, 4 parts) and kaolin (5% of total weight); the mixture is dropped into 0.25 M solution of calcium chloride; the resulted granules are filtered and dried. The technique was used for the first time to formulate conidia of
Various compositions of alginate granules were evaluated for many potential and commercial biopesticides. Chitin (2% of granules weight) together with wheat bran (2%) significantly increased spore production of
Composition of alginate formulation of
Fungal biomaterial (e.g. conidia and mycelia) suspended in sodium alginate solution or in the mixture of agar-agar (1%) and gelatin (1:1, v/v) is emulsified in corn oil with n-hexadecan (6:4) and lecithin as emulsifier. Gelatin-agar globules were gelated in the emulsion while alginate microcapsules were polymerized when dropped into calcium chloride solution. The size of microcapsules varied from 10 to 400 μm depending on ratio of the mentioned components. The microcapsules were separated from the liquids by vacuum filtration and used by spraying. The microencapsulation technique was successfully used in model experiments for development of artificial conidia based on conidia of
The production of Pesta granules is based on the technology of pasta production. Inoculum suspension (52 mL), wheat semolina flour (80 g) and kaolin (20 g) are mixed to produce dough. The dough is passed through a pasta maker after that it is dried, crashed and sieved. The technique was tried for encapsulation of conidia of potential mycoherbicides (
Microslecrotia of
The composition of Pesta granules can be easily modified. Shabana et al. [148] evaluated various compositions for
For encapsulation of conidia of potential mycopesticides (
The main components of these granules are a membrane stabilizer (for instance, sucrose at the concentration 10–65% from granules weight), a water absorbance agent (starch), a filler (diathomaceous earth, silica Hi-Sil® at the concentration 5–20%). Additionally, the granules can include vegetable oil (ca. 20%), UV-protectant, preservatives and other inert fillers [151]. For example, sucrose (4 parts), starch (1 part), unrefined vegetable oil (1 part), silica gel (1.5 parts) and biological suspension (4 parts) are mixed and extruded; the resulted pasta is conventionally dried and crashed or milled. This technique was successfully used for potential bioherbicides based on
The safety and evaluation of postponed risks of mycopesticides are still under question. An agroecosystem is inundated by a fungus at very high concentrations and there is a risk of the crop injury. Some plant pathogens can survive in the soil or plant debris. They are able of producing biologically active compounds (mycotoxins, antibiotics, phytotoxins, etc.). The number of safety research on the safety of mycoherbicides is limited to
Molecular marking of biocontrol strains is an approach for their post-application tracking and quantification. For instance, the strain
In conclusion, the approaches for stabilization and storage of biopesticides based on fungal propagules were discussed in this review. In order to produce both virulent and stress tolerant propagules for mycoherbicides based on the submerged fungal mycelium as well as on conidia, chlamydospores and microsclerotia a liquid medium should be optimized. The construction of bioreactors, in particular, for solid-state fermentation is continuously being improved that allows of producing highly stress tolerant fungal aerial conidia. Various recipes for liquid (e.g. suspension and emulsion concentrates) and solid (like alginate and stabilize granules) formulation of mycoherbicides were developed to be stored for a long time and effectively used. However, the efficacy of mycoherbicides is still unstable and their safety is not proved clearly to be widely commercialized.
The research was supported by Russian Science Foundation (project # 16-16-00085).
Chemical engineering processes are frequently composed of multiple complex phenomena. These systems can be represented by a set of several equations, such as
In the chemical process industries, ammonia is one of the most widely manufactured inorganic compounds [3]. The majority of ammonia produced commercially is consumed in fertilizers, with the rest going into plastics, synthetic fibers and resins, pharmaceuticals, explosives, papers, and refrigeration [4]. As a result, modeling and optimization of ammonia synthesis process have received a significant attention from both the academia and industry. Ammonia is produced predominantly from the combination of elements such as nitrogen and hydrogen in a catalytic process using a promoted iron catalyst firstly established by Haber and Bosch as the reaction [4]:
The reaction is reversible and exothermic, releasing a significant amount of heat. In order to achieve a high conversion, the heat of the reaction should be removed. Therefore, the process is typically carried out in an autothermal synthesis reactor, in which the heat of reaction is utilized to preheat the feed gas and ensure the suitable temperature inside. The production of ammonia depends on several factors such as the reactor length, the operating pressure, temperature of the feed and reacted gas, the flow rate, and composition of the gas mixture. The optimization problem of the process is to maximize the economic return. Many studies discussing the modeling, simulation, and optimization of an autothermal ammonia synthesis reactor can be found in literature. Some of them can be mentioned here as in Babu et al. [5], Babu and Angira [6], Carvalho et al. [7], Edgar et al. [8], Ksasy et al. [9], Murase et al. [10], Upreti and Deb [11], Yusup et al. [12]. However, the model discussed in the studies of Edgar et al. [8], Murase et al. [10] has some minor errors and has been corrected in Upreti and Deb [11]. Moreover, the studies primarily focus on optimizing reactor length for a specific reactor top temperature, usually 694 K [6, 7, 12], or for a limited set of temperatures [9, 11]. However, as reported in some studies [11, 12], the economic return is determined by the top temperature and also the reactor length (the temperature of feed gas entering to the reaction zone). As a result, rather than a single variable problem of reactor length, the optimization problem should be viewed as a multivariable problem.
In the study [13], both the reactor length and the reactor top temperature are considered in the design variables for maximizing the profit return of the process. In order to solve the multivariate optimization problem, the cyclic coordinate search technique was employed. This method alters the value of one decision variable at a time, and for each coordinate direction, the golden section search was utilized to solve the single variable optimum problem. However, this traditional searching approach is prone to get caught in local optima. Therefore, the genetic algorithm has higher chance to obtain the global optimum profit of the process.
The system discussed here is an autothermal synthesis reactor, which is described in [10] and contains the correction of the objective function reported in [6, 11]. The feed gas contains 21.75 mole% nitrogen, 65.25 mole% hydrogen, 5.0 mole% ammonia, 4.0 mole% methane, and 4.0 mole% argon. In an autothermal reactor, the feed gas mixture enters from the bottom of the reactor, flows upward, enters the catalyst zone from the top, and moves downward. In the catalyst zone, the reaction takes place at around 500°C and 200 atm of pressure. The heat generated by the reaction is utilized to preheat the feed gas mixture in counter current flow. Figure 1 shows the schematic diagram of an autothermal ammonia synthesis reactor. The considered factors affecting the synthesis process are the temperature of feed gas at the entrance of the reaction zone (top temperature) and the reactor length. The goal of the optimal design is to determine the conditions that will give the highest economic return from the reactor operation.
Schematic diagram of an autothermal ammonia reactor [
The return of the process, which is calculated from the value of the product gas (heating value and ammonia value), subtract the cost of feed gas (as a source of heat only) and minus the amortization of reactor capital expenses, is the objective function for maximization (
in which,
The heat balance for the feed gas and the reacting gas and the mass balance for the nitrogen flow along the catalyst zone, respectively, give the mathematical model for the system:
in which
The differential equations are valid in the interval [0,
The notations
Other notations of the system are summarized in Table 1.
Notation | |
---|---|
Heat capacity of the feed gas | |
Heat capacity of the reacting gas | |
Catalyst activity | |
Δ | Heat of reaction |
Mass flow of component designed by subscript | |
Reaction rate constant | |
Partial pressure of component designated by subscript | |
Universal gas constant | |
Surface area of catalyst tubes per unit length of reactor | |
Cross-sectional area of catalyst zone | |
Overall heat transfer coefficient | |
Total mass transfer flow rate |
Notation of the synthesis system.
The variables are subjected to the following physical constraints, as is typical in industries [10]:
The length of the reactor and the top temperature are chosen as the design variables. The remaining variables (
The optimal design problem is summarized as follows:
The system of ordinary differential Eqs. (3), (4), and (5) with initial conditions (11) was solved by Runge–Kutta fourth-order method. The system is well defined when the top temperature (
The range of the design variables is
In barrier or penalty methods, the objective function will receive an undesired value when one of the constraints is violated. Therefore, the solution will be kept in the feasible region. The objective function has been modified as
Figure 2 shows the fitness values as a function of generation. As can be observed, the fitness function value achieved the highest after roughly 20 generations and then stayed unchanged. After 100 generations, it was obtained that the reactor length should be 6.772 m, and the top temperature should be 707.09 K. The process produces a profit of 5.018× 106 $ per year. The other parameters of the process are summarized in Table 3 and compared with the findings of a cyclic coordinate search [13]. The profit value is slightly higher than those reported in the literature, which focused solely on reactor length optimization. From the results, the temperature at the entrance of the catalyst zone should be slightly higher, and that the reactor length should also be slightly longer than previously reported.
Fitness value versus generations.
Variables | Interval | Cyclic coordinate [13] | Genetic algorithm |
---|---|---|---|
[0,10] | 6.724 | 6.772 | |
[600,800] | 700.27 | 707.09 | |
[400,800] | 400.00 | 401.09 | |
629.94 | 631.12 | ||
[0,3220] | 490.68 | 490.68 | |
5.018 | 5.018 |
Maximization results.
The behavior of permeate flux has a significant impact on the performance of cross-flow ultrafiltration. Many factors cause flux declination, such as solution properties, membrane properties, and operation conditions. The majority of current research has centered on increasing membrane performance in terms of permeability and selectivity [14, 15]. Just a few studies have paid attention to the configuration and operation of the membrane module [16].
Various factors determine the decision of membrane module geometry for a given application, including fabrication method, power consumption, and fouling potential [17]. Manufacturers frequently recommend the membrane module design from the fabrication standpoint [17]. There is virtually no evidence that their approach prioritizes the energy efficiency. Currently, with a growing in energy concern and a falling in membrane cost, the membrane module design should place a higher attention on energy efficiency. As a result, it is necessary to propose a module design methodology that takes into account the energy factor.
Furthermore, membrane operating conditions are usually decided by user experience, a handbook, or a manual from the membrane supplier. However, the permeate flux equation governing the performance of the membrane system varies greatly between different situations. In this aspect, for any specific application, a general methodology for the design and operation conditions should be studied.
In cross-flow ultrafiltration of protein solution, Nguyen et al. [18] proposed a simple combined model, which simultaneously considers pore blockage and cake filtration, to describe the flux declination. Then, in the study [19], the correlation between the steady-state permeate flux and operation parameters was reported. From the steady-state operation equation, optimal design and operation conditions for each particular application could be established.
However, just a few reports on the optimization of membrane processes and cost estimation have been published, or the cost estimation is too general. For example, Wiley et al. [17] optimized the membrane module configurations for brackish water desalination. However, the operation mode is single-pass and only the membrane cost and energy cost were taken into account. Sethi and Wiesner [20] developed the cost model for the removal of natural organic matter, but the study has not conducted the optimization. In membrane technology, the feed and bleed operation mode, which combines the batch and the single-pass configurations, is commonly utilized for continuous full-scale filtration [21, 22]. Therefore, the optimization of a membrane module operated in feed and bleed mode for protein ultrafiltration is considered. The membrane geometry dimensions and operating conditions are design variables in the problem. The system is represented by a set of ordinary differential equations. The objective function is the annual cost, which consists of various types of capital investments and an operating expense. The capital investments are classified into several categories, which are individually correlated to plant scale, particularly the membrane area. The operating expense is the power consumption.
The configuration of filtration system is continuous feed and bleed, which is shown schematically in Figure 3. The notations are summarized in Table 4. There are two main pumps in this operation: the feed pump provides the necessary trans-membrane pressure, while the recirculation pump maintains the cross-flow rate through the modules. The concentrate is continually withdrawn from the system at a flow rate (
Schematic configuration of feed-and-bleed mode membrane system.
Notation | Name and units |
---|---|
Feed flow rate [m3/hr] | |
Retentate (concentrate) flow rate [m3/hr] | |
Recirculation flow rate [m3/hr] | |
Flow rate in membrane module [m3/hr] | |
Permeation flow rate [m3/hr] | |
Pressure at outlet of feed pump [kPa] | |
Pressure at the inlet of membrane module [kPa] | |
Pressure at the inlet of membrane module [kPa] | |
Energy consumed by the feed pump [kW] | |
Energy consumed by the recirculation pump [kW] | |
Initial concentration of protein solution [m3/m3] | |
Inlet concentration of protein solution [m3/m3] | |
Final concentration of protein solution [m3/m3] | |
Concentration of protein in permeate flux [m3/m3] | |
Fluid flow velocity [m/s] | |
Fluid density [kg/m3] | |
Fluid viscosity [kg/(m·s)] | |
Width, height, length, hydraulic diameter of the membrane module |
Summary of system configuration notations.
The material balance for total mass and protein give:
The viscosity and density of protein solution correlate to its concentration [23]:
in which,
The permeate flux through the membrane is [19].
in which
The equation for permeate flux can be rewritten as:
or in terms of shear rate
The flow rate/velocity drop and channel length change are calculated from the total mass balance and component balance within the control volume
The pressure loss is estimated by the Darcy-Weisbach Equation [24, 25].
in which
The set of ordinary equations that describes the membrane module system was established as follows [26].
in the range of concentration [
The system of the ordinary equations can be solved numerically by Runge–Kutta fourth-order method [27] to obtain the flow rate, the length, and the pressure. From that, the two important factors determining the total cost, membrane area, and total energy were calculated:
In this equation,
Δ
The operating cost consists of power consumption of the pumps and membrane replacement. The annual energy expense of the pumps is calculated as
The membrane replacement cost is calculated as
where
The membrane price is usually about 200 $/m2 ([9]), and membrane life is 12–18 months. Therefore, the membrane replacement cost per year is roughly estimated as 200 $/m2/year for the interest of
It is widely observed that capital costs are correlated to the size in the power-law form [30]:
In order to achieve higher accuracy, rather than simply predicting the whole capital cost of the membrane plant to capacity, Sethi and Wiesner [20] divided the capital investment into several major categories, which was correlated to the size independently. The major categories include pumps and other manufactured equipment.
Pump capital cost
The pumps capital cost can be estimated as (Perry et al. [31]):
in which.
The cost index,
The pump size (
Capital cost of other equipment
In membrane application, the membrane area is the key parameter, which determines the plant capacity [34]. Thus, the membrane area is chosen as the basic for the estimation of various components in the capital costs.
Non-membrane equipment and facilities, excluding the pumps, were grouped into four main categories: (1) pipes and valves; (2) instruments and controls; (3) tanks and frames; and (4) miscellaneous. The capital cost of each is correlated to the membrane area as follows (Sethi and Wiesner [20])
Pipes and valves
Instruments and controls
Tanks and frames
Miscellaneous
Annual capital cost
The capital cost can be annualized using the amortization factor as
For the plant design year of 20 years and the interest rate 8%, the amortization factor will be about 0.1.
In the problem, some variables, called input variables, are fixed due to the requirement of the design. In membrane design, these are feed flow
The design variables were: channel geometry (width × length × height), the inlet pressure (
The objective function is the sum of capital cost and operating cost, which were annualized:
The pressure at the outlet point should be positive. This constraint is satisfied by assigning a high value to the objective function if the outlet pressure is negative.
The decision variables are frequently limited on a finite range
in which
The system parameters and variables are summarized in Table 5.
Parameters | Value |
---|---|
Feed flow rate (m3/hr) | 0.02–200 |
Inlet pressure (kPa) | 200–1000 |
Recirculation flow rate (m3/hr) | 0–50 |
Initial solid fraction (m3/m3) | 0.1 |
Final solid fraction (m3/m3) | 0.4 |
Plant design year (year) | 20 |
Interest rate (%) | 8 |
Energy price ($/kWh) | 0.08 |
Efficiency of pumps (%) | 70 |
Operating temperature (°C) | 25 |
Module height (mm) | 0–100 |
Module width (m) | 0–30 |
System parameters and variables.
The parameters of GA such as population size, crossover probability, mutation probability values were set to be, 100, 1.0, and 0.30, respectively. The selection was based on roulette wheel with elitism, which means the most fit individual is guaranteed a place in the next generation. The number of generations was assigned to be 500. Because the problem is to minimize the cost, the fitness function was defined as:
For the demonstration of this method, optimum designs of several feed flow rates have been carried out. The lower limit of the membrane width is 0.1 m, the lower limit for the module height is 0.5 mm. The designs are shown in Table 6.
Feed [m3/hr] | Pressure [kPa] | Recirculation [m3/hr] | width [m] | height [mm] | total cost [$/yr] | ||
---|---|---|---|---|---|---|---|
0.02 | 0.1 | 0.4 | 523 | 2.8 | 0.1 | 5.0 | 1.29 × 103 |
0.2 | 0.1 | 0.4 | 1000 | 4.9 | 0.1 | 8.9 | 4.30 × 103 |
2 | 0.1 | 0.4 | 1000 | 0.2 | 0.1 | 6.9 | 1.18 × 104 |
20 | 0.1 | 0.4 | 987 | 0.2 | 1.3 | 5.0 | 5.60 × 104 |
200 | 0.1 | 0.4 | 1000 | 0.8 | 11.1 | 5.0 | 3.65 × 105 |
Optimum designs of membrane module.
Figure 4 presents the optimum total cost per unit of feed flow. The cost per unit of feed flow decreases with an increase in plant capacity. It reflects the economies of scale.
The behavior of cost per unit flow rate design in optimum condition with plant capacity.
The results also suggest that the membrane module dimensions and operation condition will change greatly depending on the process requirements, such as the required feed capacity. It is challenging to predict the direction. It might be concluded that the permeate flux also greatly affects the geometric design and operation strategy in membrane separation processes. It is difficult to find a general rule for the design, for each specific system, the correlation between the permeate flux and operating conditions and membrane geometry should be investigated.
Fuel cells that are highly effective and green technology for converting chemical energy stored in fuel to useable power are currently regarded as one of the most promising approaches for future energy requirements [35]. The solid oxide fuel cell (SOFC) has demonstrated an exceptional integration of advantages, such as high efficiency, fuel flexibility, wide contamination acceptance, and low pollution [36, 37]. Modeling and simulation are valuable tools for determining the impact of various design factors and operating conditions on cell performance, as well as for improving fuel cells [38, 39, 40]. Plenty of models have been reported to add to the understanding of fuel cells. Modeling approaches can be categorized into two types: theoretical and empirical one [39, 41, 42]. In the theoretical approach, the spatial dimensions of the models range from simple 0 (0-D) [43, 44] and 1 (1-D) [42, 45, 46, 47], to more complicated 2 (2-D) [48, 49, 50, 51] and 3 (3-D) [52, 53, 54], all with various characteristics and directed at different objectives. The mathematical models, which are based on conservation principles, require a lot of data on parameters and properties of fuel cell, as well as complicated equations and time-consuming calculation.
Empirical or data-driven approach may be more feasible for fuel cell users since the behavior can be quickly and simply deduced without a comprehensive understanding of the internal components, just based on the experimental data [39, 41]. Least squares support vector machine (LS-SVM) [55], Hammerstein model [56, 57] are examples of these approaches. In this approach, artificial neural network (ANN) shows several advantages, including high nonlinearity, rapid computation, a low degree of error in matching experimental data. Using ANNs to model SOFCs appears to be a very promising method.
In this section, an ANN was used to model the performance of the BSCF/GDC-based cathode SOFC. The cell voltage was predicted from cathode sintering temperature, cell operating temperature, and cell current. Several network architectures were examined to find the best structure, and the network was trained using back-propagation methods. The data for training, validation, and testing were taken from our study [58]. The genetic algorithm and the developed ANN were then used to find the best conditions for achieving maximum power.
Artificial neural networks (ANNs), which were analogous to biological nervous systems, consist of interconnected nodes known as neurons to receive and transfer data [59]. The most basic form, feed-forward architecture, is made up of an input layer, one hidden layers, and an output layer. The input and output layers have the same number of neurons as the number of inputs and outputs in the system to be modeled. Weighted connections connect each neuron to every other neuron in the next layer. In any layer except the input, the weighted sum of data from the previous layer is the input of a neuron. The neuron then activates the data using a function and transfers the response to all neurons in the next layer. The size of the hidden layers is a significant factor that affects the estimation precision because it can make the network become insufficient or overfitting [60]. The number of neurons in hidden layer is generally determined through trials. Figure 5 illustrates a 3–5-1 feed forward artificial neural network with operating temperature, sintering temperature, and current as inputs.
Artificial neural network (3–5-1) structure.
The activation function employed in this model is the logistic sigmoid
The input data (
in which xmax and xmin are the bounded interval of the experimental data.
To assess the performance of ANN, the mean squared error (MSE) and coefficient of determination (R2) are usually used [61].
Various factors affect the performance of fuel cells such as cathode and anode structure, electrolyte material and thickness, cell temperature, inlet and outlet gas compositions. Two important factors, cathode sintered temperature and cell operating temperature, were considered in this model. The sintered temperature is from 1000–1050°C, whereas the operating temperature ranges from 625–700°C. The sintered temperature affects the structure of the obtained cathode as reported in [58]. The explanation of the range for the investigated parameters can be found in [62].
An ANN with one input layer, one hidden layer, and one single output layer was proposed. Current density, sintered temperature of the cathode, and cell operating temperature are the inputs. Back-propagation algorithm [63] was used to train the network. The maximum number of iteration and minimum performance gradient were set to 400 and 10−5, respectively, to stop the training. The proper network structure is determined through a series of trial tests. The data were split into three subsets at random: training, validation, and test, each containing 70, 20, 10% of the total samples, respectively. The validation and test sets are necessary for evaluating the validation and power of the networks.
The parameters of the neural network were saved and utilized in the next stage to optimize the power density using genetic algorithms.
The objective function is the power density of the fuel cell
where
The design variables and their corresponding ranges are summarized as follows:
sintered temperature of the cathode, [1000–1050] (°C).
operating temperature of the cell, [625–700] (°C).
electric current of the cell, [0–1500] (mA.cm−2)
The parameters of GA as population size, mutation probability values were set to be 100 and 0.10, respectively. The survival of the individuals was decided by roulette wheel with elitism. The number of generations was 500.
Figure 6 depicts the fitness values (maximum and mean) of the population versus generation. As indicated in the figure, after about 20 generations, the value of fitness function attained to a maximum value and then remained unchanged. After 100 generations, the maximum fuel cell power density of 451.64 mW/cm2 could be achieved at the sintered temperature of 1005°C, operating temperature of 668°C, and current density of 777 mA/cm2.
The fitness values versus generation.
The application of genetic algorithm in chemical engineering processes has been illustrated by three case studies. The results suggest that the optimum conditions of complex chemical problems can be easily obtained using genetic algorithm. The successes of genetic algorithm for the challenging problems reported herein, the development of many faster and flexible versions of GA, the improvement of computing ability all suggest the continually increasing impact of metaheuristic methods in chemical engineering systems.
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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. 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Legumes are nutritionally valuable, providing proteins (20–45%) with essential amino acids, complex carbohydrates (±60%) and dietary fibre (5–37%). Legumes also have no cholesterol and are generally low in fat, with ±5% energy from fat, with the exception of peanuts (±45%), chickpeas (±15%) and soybeans (±47%) and provide essential minerals and vitamins. In addition to their nutritional superiority, legumes have also been ascribed economical, cultural, physiological and medicinal roles owing to their possession of beneficial bioactive compounds. Research has shown that most of the bioactive compounds in legumes possess antioxidant properties, which play a role in the prevention of some cancers, heart diseases, osteoporosis and other degenerative diseases. Because of their composition, legumes are attractive to health conscious consumers, celiac and diabetic patients as well as consumers concerned with weight management. The incorporation of legumes in diets, especially in developing countries, could play a major role in eradicating protein-energy malnutrition especially in developing Afro-Asian countries. Legumes could be a base for the development of many functional foods to promote human health.",book:{id:"5963",slug:"functional-food-improve-health-through-adequate-food",title:"Functional Food",fullTitle:"Functional Food - Improve Health through Adequate Food"},signatures:"Yvonne Maphosa and Victoria A. 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The main global health organizations have incorporated patient safety in their review of work practices. The data provided by the medical laboratories have a direct impact on patient safety and a fault in any of processes such as strategic, operational and support, could affect it. To provide appreciate and reliable data to the physicians, it is important to emphasize the need to design risk management plan in the laboratory. Failure Mode and Effect Analysis (FMEA) is an efficient technique for error detection and reduction. Technical Committee of the International Organization for Standardization (ISO) licensed a technical specification for medical laboratories suggesting FMEA as a method for prospective risk analysis of high-risk processes. FMEA model helps to identify quality failures, their effects and risks with their reduction/elimination, which depends on severity, probability and detection. 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Leadership in health services is important for following innovations and adapting to current situations. Nurses working together with other health personnel in hospitals providing health services constitute an important group in leadership. Nursing, which is a key force for patient safety and safe care, is a human-centered profession, and therefore leadership is a key skill for nurses at all levels. The leadership styles of nurse managers are believed to be an important determinant of job satisfaction and persistence of nurses. The need for nurses with leadership skills and the need for nurses to develop their leadership skills are increasing day by day. There are several leadership styles defined in nursing literature. These leadership styles are examined under the titles of relational leadership style, transformational leadership, resonant leadership, emotional intelligence leadership, and participatory leadership. The task-focused leadership style is explored under the headings of transactional and autocratic leadership, laissez-faire leadership, and instrumental leadership.",book:{id:"9047",slug:"nursing-new-perspectives",title:"Nursing",fullTitle:"Nursing - New Perspectives"},signatures:"Serpil Çelik Durmuş and Kamile Kırca",authors:null},{id:"58916",title:"Factors Affecting the Attitudes of Women toward Family Planning",slug:"factors-affecting-the-attitudes-of-women-toward-family-planning",totalDownloads:8404,totalCrossrefCites:9,totalDimensionsCites:17,abstract:"Everyone has the right to decide on the number and timing of children without discrimination, violence and oppression, to have the necessary information and facilities for it, to access sexual and reproductive health services at the highest standard. Deficient or incorrect family planning methods, wrong attitudes and behaviors toward the methods and consequent unplanned pregnancies, increased maternal and infant mortality rates are the main health problems in most countries. Individuals’ learning modern family planning methods and having positive attitude for these methods may increase the usage of these methods and contributes the formation of healthy communities. 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Over periods of time, some of these norms become standards that all members of the community are expected to adhere to. Deviance from these standards is seen as absurd, wrong, or frankly abnormal. However, many of these cultural mores have no scientific basis and, some of them actually promote behaviors with negative health consequences. This chapter examines the cultural practices of some communities in Africa and their health consequences and, explores ways to address the challenges.",book:{id:"9138",slug:"public-health-in-developing-countries-challenges-and-opportunities",title:"Public Health in Developing Countries",fullTitle:"Public Health in Developing Countries - Challenges and Opportunities"},signatures:"Radiance Ogundipe",authors:[{id:"302308",title:"Dr.",name:"Radiance",middleName:null,surname:"Ogundipe",slug:"radiance-ogundipe",fullName:"Radiance Ogundipe"}]},{id:"55808",title:"The Role of Legumes in Human Nutrition",slug:"the-role-of-legumes-in-human-nutrition",totalDownloads:5312,totalCrossrefCites:55,totalDimensionsCites:94,abstract:"Legumes are valued worldwide as a sustainable and inexpensive meat alternative and are considered the second most important food source after cereals. Legumes are nutritionally valuable, providing proteins (20–45%) with essential amino acids, complex carbohydrates (±60%) and dietary fibre (5–37%). Legumes also have no cholesterol and are generally low in fat, with ±5% energy from fat, with the exception of peanuts (±45%), chickpeas (±15%) and soybeans (±47%) and provide essential minerals and vitamins. In addition to their nutritional superiority, legumes have also been ascribed economical, cultural, physiological and medicinal roles owing to their possession of beneficial bioactive compounds. Research has shown that most of the bioactive compounds in legumes possess antioxidant properties, which play a role in the prevention of some cancers, heart diseases, osteoporosis and other degenerative diseases. Because of their composition, legumes are attractive to health conscious consumers, celiac and diabetic patients as well as consumers concerned with weight management. 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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},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"3",title:"Bacterial Infectious Diseases",coverUrl:"https://cdn.intechopen.com/series_topics/covers/3.jpg",isOpenForSubmission:!1,editor:null,editorTwo:null,editorThree:null},{id:"4",title:"Fungal Infectious Diseases",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",isOpenForSubmission:!0,editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",slug:"yuping-ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",biography:"Dr. Yuping Ran, Professor, Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China. Completed the Course Medical Mycology, the Centraalbureau voor Schimmelcultures (CBS), Fungal Biodiversity Centre, Netherlands (2006). International Union of Microbiological Societies (IUMS) Fellow, and International Emerging Infectious Diseases (IEID) Fellow, Centers for Diseases Control and Prevention (CDC), Atlanta, USA. Diploma of Dermatological Scientist, Japanese Society for Investigative Dermatology. Ph.D. of Juntendo University, Japan. Bachelor’s and Master’s degree, Medicine, West China University of Medical Sciences. Chair of Sichuan Medical Association Dermatology Committee. General Secretary of The 19th Annual Meeting of Chinese Society of Dermatology and the Asia Pacific Society for Medical Mycology (2013). In charge of the Annual Medical Mycology Course over 20-years authorized by National Continue Medical Education Committee of China. Member of the board of directors of the Asia-Pacific Society for Medical Mycology (APSMM). Associate editor of Mycopathologia. Vice-chief of the editorial board of Chinses Journal of Mycology, China. Board Member and Chair of Mycology Group of Chinese Society of Dermatology.",institutionString:null,institution:{name:"Sichuan University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null},{id:"5",title:"Parasitic Infectious Diseases",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",isOpenForSubmission:!0,editor:{id:"67907",title:"Dr.",name:"Amidou",middleName:null,surname:"Samie",slug:"amidou-samie",fullName:"Amidou Samie",profilePictureURL:"https://mts.intechopen.com/storage/users/67907/images/system/67907.jpg",biography:"Dr. Amidou Samie is an Associate Professor of Microbiology at the University of Venda, in South Africa, where he graduated for his PhD in May 2008. He joined the Department of Microbiology the same year and has been giving lectures on topics covering parasitology, immunology, molecular biology and industrial microbiology. He is currently a rated researcher by the National Research Foundation of South Africa at category C2. He has published widely in the field of infectious diseases and has overseen several MSc’s and PhDs. His research activities mostly cover topics on infectious diseases from epidemiology to control. His particular interest lies in the study of intestinal protozoan parasites and opportunistic infections among HIV patients as well as the potential impact of childhood diarrhoea on growth and child development. He also conducts research on water-borne diseases and water quality and is involved in the evaluation of point-of-use water treatment technologies using silver and copper nanoparticles in collaboration with the University of Virginia, USA. 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His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. 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