\r\n\tThis book chapter’s main theme will be focused on transmission dynamics, pathogenesis, mechanisms of host interaction and response, epigenetics and markers, molecular diagnosis, RNA interacting proteins, RNA binding proteins, advanced development of tools for diagnosis, possible development of concepts for vaccines and anti drugs for RNA viruses, immunological mechanisms, treatment, prevention and control.
\r\n\t
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Zilfyan and Arto V. Zilfyan",authors:[{id:"157235",title:"Dr.",name:"Artashes",middleName:"Arto",surname:"Zilfyan",fullName:"Artashes Zilfyan",slug:"artashes-zilfyan"},{id:"170581",title:"Dr.",name:"Arto",middleName:null,surname:"Zilfyan",fullName:"Arto Zilfyan",slug:"arto-zilfyan"}]},{id:"46783",title:"Paranasal Sinus Mucoceles – Opthalmic Manifestations, Radiological Imaging, Endoscopic Endonasal Marsupilization and Outcome",slug:"paranasal-sinus-mucoceles-opthalmic-manifestations-radiological-imaging-endoscopic-endonasal-marsupi",signatures:"Balwant Singh Gendeh",authors:[{id:"67669",title:null,name:"Balwant Singh",middleName:null,surname:"Gendeh",fullName:"Balwant Singh Gendeh",slug:"balwant-singh-gendeh"}]}]}],publishedBooks:[{type:"book",id:"286",title:"Keratoplasties",subtitle:"Surgical techniques and complications",isOpenForSubmission:!1,hash:"8e8d2ab941ea6074e7a7ae55de9c78fa",slug:"keratoplasties-surgical-techniques-and-complications",bookSignature:"Luigi Mosca",coverURL:"https://cdn.intechopen.com/books/images_new/286.jpg",editedByType:"Edited by",editors:[{id:"37700",title:"Dr.",name:"Luigi",surname:"Mosca",slug:"luigi-mosca",fullName:"Luigi Mosca"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"360",title:"Electroretinograms",subtitle:null,isOpenForSubmission:!1,hash:"bfbc5538173f11acb0f9549a85b70488",slug:"electroretinograms",bookSignature:"Gregor Belusic",coverURL:"https://cdn.intechopen.com/books/images_new/360.jpg",editedByType:"Edited by",editors:[{id:"44595",title:"Dr.",name:"Gregor",surname:"Belusic",slug:"gregor-belusic",fullName:"Gregor Belusic"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"540",title:"Age Related Macular Degeneration",subtitle:"The Recent Advances in Basic Research and Clinical Care",isOpenForSubmission:!1,hash:"457bf890ed1e947a2ed23fc8237e34f0",slug:"age-related-macular-degeneration-the-recent-advances-in-basic-research-and-clinical-care",bookSignature:"Gui-Shuang Ying",coverURL:"https://cdn.intechopen.com/books/images_new/540.jpg",editedByType:"Edited by",editors:[{id:"86603",title:"Dr.",name:"Gui-Shuang",surname:"Ying",slug:"gui-shuang-ying",fullName:"Gui-Shuang Ying"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"666",title:"Diabetic Retinopathy",subtitle:null,isOpenForSubmission:!1,hash:"cc9ab3a3c861825692bb9eea670aea2e",slug:"diabetic-retinopathy",bookSignature:"Mohammad Shamsul Ola",coverURL:"https://cdn.intechopen.com/books/images_new/666.jpg",editedByType:"Edited by",editors:[{id:"86018",title:"Dr.",name:"Mohammad Shamsul",surname:"Ola",slug:"mohammad-shamsul-ola",fullName:"Mohammad Shamsul Ola"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"751",title:"Advances in Ophthalmology",subtitle:null,isOpenForSubmission:!1,hash:"63feda93d7fee6fb1f164a52e9f6427c",slug:"advances-in-ophthalmology",bookSignature:"Shimon Rumelt",coverURL:"https://cdn.intechopen.com/books/images_new/751.jpg",editedByType:"Edited by",editors:[{id:"54335",title:"Dr.",name:"Shimon",surname:"Rumelt",slug:"shimon-rumelt",fullName:"Shimon Rumelt"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],publishedBooksByAuthor:[]},onlineFirst:{chapter:{type:"chapter",id:"82369",title:"Biological Treatment of Cannery Wastes",doi:"10.5772/intechopen.105411",slug:"biological-treatment-of-cannery-wastes",body:'1. Introduction
Canned foods were well known and widely used for feeding the armies since the mid-eighteenth century. Nowadays, they play a crucial role in the everyday nutrition of everyone all over the globe, where they provide food with good quality that can last for a long time compared with fresh food. The canned food production industry, as any other industry, includes material processing, storing, and transportation. These activities lead to waste and emission generation and can affect the environment negatively if not well planned and applied. These negative effects might include air and water pollution and soil contamination. Of the major pollutants generated by this industry, the organic pollutants are very crucial [1].
In general, food processing from raw materials requires large volumes of high-grade water, which will become wastewater after usage. In particular, it requires a large volume of potable water for several usages, e.g. raw materials cleaning, fluming, blanching, pasteurizing, processing equipment cleaning, and cooling of the final products. These vast usages require the enforcement of quality criteria for the water used in each application; the best quality usage often requires independent treatment to assure complete freedom from odor and taste and to ensure uniform conditions [1]. The wastewater effluents from this industry are characterized by their large volumes. On average, some 10–20 m3 wastewaters are produced per tonne of products. The precise characteristics of these wastewaters are highly dependent on the performed processes during the canned food production, i.e. the process of vegetable washing leads to the generation of wastewaters with high loads of some dissolved organics, and particulate matter [2].
The organic content in the wastewater generated as a result of the operation of different processes in the food canning industries is characterized by high concentrations of biodegradable contaminants and variable pH levels. When an environmental reservoir, e.g. a stream or waterway, receives these wastewater effluents, the organic pollutants will consume some of the dissolved oxygen (DO) that exists in the reservoir during their stabilization. This will reduce considerably the DO to levels below that required for the sustainability of lives of the aquatic organisms. The extent of pollution caused by these effluents can be characterized based on the plant capacity, the utilized process, and the characteristics of the raw materials. In this respect, it is beneficial to categorize the plant capacity in terms of population, where seasonal plants are likely to generate waste loads equivalent to 15,000 to 25,000 people, and large plants generate loads up to 250,000 people. The processing of fruit and vegetables is one of the sources of wastewaters, which contain organic matters. Fruit and vegetable canning companies generate wastewaters with high levels of biochemical oxygen demand (BOD), total solid (TS), and suspended solids (SS) [1]. This chapter aims to introduce the available technologies for secondary wastewater treatment that are widely investigated to prevent and control pollution from the food industry. In this respect, the features of the aerobic and anaerobic biological treatment technologies are summarized. Then, an overview of the uncertainty management in biological treatment plants is provided.
2. Cannery wastewater treatment
Due to the nature of the food industry, the preparatory and operational processes of the raw animals, vegetables, and fruits into edible products do not include the application of chemicals. Subsequently, the organic maters in most of the cannery wastewater effluents are best treated using biological treatment, where these matters are rarely present toxicant or inhibitory compounds in their composition. Yet in some operations, e.g. sterilizing and cleaning the equipment, chemicals are used. In particular, disinfectants and caustic soda are used at the end of the processed batch. These effluents could be characterized as short-time concentrated discharges. They may cause shock loads in the wastewater treatment plants that are not designed to deal with these effluents. In this case, the use of equalization unit can achieve acceptable flow equalization and pH adjustment and dilute the high concentration to a nominal concentration that allows safe operation for the biological treatment unit [3].
3. Aerobic treatment of cannery wastewaters
Aerobic wastewater treatment processes could be applied using several technologies, i.e. pond and lagoon-based treatments; surface and spray aeration; oxidation ditches; trickling filters; septic or aerobic tanks; activated sludge; and aerobic digestion. In this section, sequencing batch reactor (SBR), activated sludge (AS), rotating biological contactor (RBC), and aerobic lagoons (AELs) for treating food processing wastewater are discussed.
3.1 Sequencing batch reactor (SBR)
In general, SBR is a fill-and-draw activated sludge system for wastewater treatment. In that system, wastewater effluent is added to a single batch reactor, where treatment is achieved by removing undesirable components, and then, the effluent is discharged. In the same single batch reactor, equalization, aeration, and clarification are conducted.
The formation of granules in aerobic conditions has been possible and appears as a promising technique for treating high-strength or highly toxic wastewaters. It appeared that aerobic granules were successfully cultivated only in SBR. The cyclic operation of SBR consisted of influent filling, aeration, settling, and effluent removal [4].
The development of aerobic granular sludge to achieve simultaneous removal of COD, phosphorous (P), and nitrogen (N) from saline fish-canning wastewater was investigated by Campo [5]. In that work, a 1.6-L SBR with a hydraulic retention time (HRT) of 0.25 d and a volumetric exchange ratio (VER) of 50% was used. The wastewater fed to the SBR was collected from a fish-canning factory located in the south of Galicia (Spain). The SBR was operated in 3-hour cycles comprising 60-min anaerobic feeding, 112-min aeration, 7–1-min settling, and 1–7-min effluent discharge. The salt concentration was approximately 10.4 ± 0.8 g NaCl/l, and the applied organic loading rate (OLR) equals 5.4 ± 1.9 kg COD/(m3d). Under these conditions, aerobic granules were detected after operational time equals 34 days. Some filamentous bacteria were detected on the surface of the aggregates. The granular biomass has a volatile suspended solids (VSS) concentration of 1.34 gVSS/l, density near 11.5 gVSS/l granule, and mean diameter of 1.35 mm. After 41 days of operation, fluffy-flocculent suspension was formed in the presence of the granules. This behavior was attributed to the salinity and the respectively high fraction of slowly biodegradable COD in the influent (35% of total COD). The study reported good removal efficiencies of soluble COD nearly equal to 80%. The phosphorus and ammonium were mainly concluded to be removed to cover the minimum metabolic demand of heterotrophic bacteria. The study indicated that the enrichment of the biomass with slow growing autotrophic and phosphorus-accumulating bacteria in a saline environment requires a longer operational time [5].
3.2 Activated sludge (AS)
The most commonly used biological wastewater treatment technology is the activated sludge. In that technology, the activated sludge (bacterial biomass suspension) is used to degrade the organic pollutants. Over years, various activated sludge processes have been developed. Depending on the design of the AS unit, the wastewater treatment plant (WWTP) can degrade organic carbon substances and remove nutrients, i.e. N and P. In some biological wastewater treatment systems, activated sludge was attached to a surface to form a bio-film. Examples of these systems are integrated fixed-film activated sludge systems, rotating biological reactors, trickling filters, and moving bed bio-film reactors [6].
3.3 Rotating biological contactor (RBC)
RBC process entails the contact between the wastewater and the biological medium that is used to degrade the organic contaminants. A RBC is described as a device that “consists of a series of closely spaced, parallel discs mounted on a rotating shaft which is supported just above the surface of the wastewater” [4, 7]. RBCs are used to remove biodegradable organic matter and convert ammonia-N and organic-N to nitrate-N. Operational problems caused by high organic loading rates restrict the use of RBCs for partial removal of organic matter (i.e. for “roughing” treatment). However, they can be used quite effectively for the substantial removal of organic matter. Process effluent (i.e. clarified) five-day biochemical oxygen demand (BOD5) and total suspended solids (TSS) concentrations can easily be reduced to less than 30 mg/l each, and even lower can be obtained in some instances [8].
3.4 Aerobic lagoons (AELs)
Aerobic lagoons (AELs) are designed and operated to exclude algae. This is accomplished by two means. First, sufficient mixing is used to keep all biomass from the treatment system in suspension, thereby providing turbidity that restricts penetration of light into the water column. The mixing also has the effect of making the solid retention time (SRT) equal to the hydraulic retention time (HRT). Second, the HRT is controlled to values less than the minimum SRT for algal growth (about two days). Because algae are excluded, oxygen must be delivered by mechanical means [8].
4. Anaerobic treatment of cannery wastewaters
This class of biological wastewater treatment technology utilizes microorganisms to degrade the organic pollutants in the absence of oxygen. The sludge in the anaerobic biological reactor consists of anaerobic bacteria and other microorganisms. Food processing wastewaters are particularly suitable for anaerobic treatment processes, firstly because of their high organic load and secondly because they rarely contain toxicants or inhibitory compounds [2].
4.1 Up-flow anaerobic sludge blanket (UASB)
The UASB process makes use of suspended growth biomass, but the gas-liquid-solids separation system is integrated with the bioreactor. The operating conditions within the reactor could be adjusted to allow the formation of large, dense, and readily settleable particles that can lead to the accumulation of very high concentrations of SS, on the order of 20 to 30 g/l as VSS. These high suspended solids concentrations allow significant separation between the SRT and HRT, and operation at relatively short HRTs, often on the order of two days or less, even when the SRT is long. The three-phase UASB reactor allows the achievement of compact and cheaper units due to its ability to separate the gas, water, and sludge mixtures under high turbulence conditions. It has multiple gas hoods for the separation of biogas and can be operated in a one-metre-height reactor that prevents the formation of floating layers [9]. Due to the extremely large gas/water interfaces, the turbulence is greatly reduced, so it is possible to operate the treatment process with relatively high loading rates of 10–15 kg/m3d [8].
UASB technology is known for its efficiency in treating wastewaters with high carbohydrate content. In this respect, the wastewater effluents from the canning industry are efficiently treated by microbes to produce a nutrient-rich starting material for anaerobic hydrogen production. This has led to the wide application of up-flow anaerobic sludge blanket (UASB) reactor for the treatment of the wastewater effluents from food processing plants [10]. These reactors are well known for their ability to withstand variations in wastewater quality and complete shutdown of the reactor in off season [11].
Anaerobic treatment of a highly alkaline fruit-cannery lye-peeling wastewater was investigated, using an up-flow anaerobic sludge blanket (UArSB) reactor. Only a short initializing period was required before COD reduction and OLR had stabilized at 85 to 90% and 2.40 kg COD/m3d, respectively. With subsequent increases in OLR to 8.1kgCOD/m3d, the COD reduction remained between 85 and 93% and biogas production peaked at 4.1 l/d (63% methane). After 111 days, the COD and reactor pH started to decrease and the gas production was reported to decrease after 102 days and continue to decrease to reach the lowest value of 0.93 l/d after 129 days. Subsequent reductions in the OLR, by reducing influent COD, had no effect on reactor stability. This reduction in the reactor performance was attributed to the inhibition of methanogenesis due to the sodium accumulation of sodium (potentially >20,000 mg/l) in the biomass [10, 12].
4.2 Anaerobic digestion
Anaerobic digestion (AD) is used for the stabilization of particulate organic matter. An anaerobic digester is well mixed with no liquid-solids separation. Consequently, the bioreactor can be treated as a continuous stirred tank reactor (CSTR) in which the HRT and SRT are identical. An SRT of 15 to 20 days is typically used, although SRTs as low as 10 days have been used successfully and longer SRTs are employed when greater waste stabilization is required [8].
For several cannery waste streams, the recovery of useful by-products could be achieved by anaerobic digestion. High COD content fruit and vegetable wastes (>50,000 mg/l) have been treated successfully by AD using a HRT of 10 days and a sludge age of 80 days. For elder sludges, the SS build-up within the reactor reached 30,000 mg/l, but at higher concentrations settling became a problem. Generally, successful treatment of food processing wastes could be achieved using AD with a retention time greater than 10 days and gas production of up to 0.75 m3/kg volatile solids [9, 11].
4.3 SHARON-Anammox process
A Single reactor system for High activity Ammonium Removal Over Nitrite (SHARON) is a treatment process, which utilizes partial nitrification process for the degradation of ammonia and organic nitrogen components from wastewaters. The process results in stable nitrite formation, rather than complete oxidation to nitrate. The process relies on controlling the pH, temperature, and retention time to prevent the nitrate formation by nitrite-oxidizing bacteria, e.g. Nitrobacter. The wastewater denitrification that employs SHARON reactors can proceed with an anoxic reduction, such as Anammox. In the Anammox process (anaerobic ammonium oxidation), nitrite and ammonium are converted into nitrogen gas under anaerobic conditions without the need to add an external carbon source. In comparison with conventional N-removal processes, the SHARON process results in a reduction of required aeration energy and carbon source.
The application of the successive SHARON-Anammox processes was tested to treat the wastewater from a fish cannery plant. The effluents generated from the anaerobic digestion are characterized by their salinity up to 8000–10,000 g NaCl m−3, organic carbon content (1000–1300 g TOCm−3), and high ammonium content (700–1000 g NH+4−Nm−3). In the SHARON reactor, nearly half the ammonia is oxidized to NO−2-N via partial nitrification. Then, SHARON effluent was directed to feed the Anammox reactor. The system was reported to attain average nitrogen removal of 68%. The bacterial population distribution in the Anammox reactor, followed by FISH analysis and batch activity assays, did not change significantly despite the continuous entrance to the system of aerobic ammonium oxidizers coming from the SHARON reactor. Most of the bacteria corresponded to the Anammox population and the rest with slight variable shares to the ammonia oxidizers. Despite the continuous variations in the amounts of ammonium and nitrite in the feed wastewater, the Anammox reactor showed an unexpected robustness. Only in the period when NO−2-N concentration was higher than the NH+4-N concentration did the process destabilized and it took 14 days until the nitrogen removal percentage decreased to 34% with concentrations in the effluent of 340 g NH+4-Nm−3 and 440 g NO−2-N m−3, respectively. That study concluded that this successive application of SHARON-Anammox reactors is successful in treating high nitrogen and saline effluents with acceptable control on the ratio between the NO−2-N and NH+4-N [13].
4.4 Anaerobic membrane bioreactors (An-MBR)
An-MBR can be simply defined as a biological treatment process operated without oxygen and using a membrane to provide solid–liquid separation. The advantages offered by this process over conventional anaerobic systems and aerobic MBR are widely recognized [12].
Saline wastewaters are known for their negative impact on the performance of the biological treatment units. Sodium chloride is widely used, not only for cooking and to melt snow and ice, but also in a wide variety of food industries including food canning, seafood processing, milk processing, etc. In particular, the operation of the seafood processing industry leads to the generation of wastewaters with high soluble and colloidal pollutants and a high concentration of N and SS. For these effluents, the application of conventional biological treatment is not efficient. It was reported that the efficiency could be enhanced by reducing the sodium toxicity with compatible solutes that can increase the sludge activity. Moreover, the anaerobic membrane bioreactor reduces the COD concentration in the wastewater [14].
4.5 Anaerobic filter (AF)
AF consists of a fixed bed biological reactor with one or more series of filtration chambers. This technology relies on the entrapment of the particles in the wastewater on the filter media and the subsequent degradation of the organic matter by the active biomass attached to the surface of the filter media [15]. As the anaerobic biomass should grow on the filter media, 6–9-month start-up period is required for AF to attain the full treatment capacity. The filter can be inoculated with anaerobic bacteria to reduce the start-up time, and the flow should be gradually increased [13, 16].
4.6 Blanket/anaerobic filter
Hybrid UASB/AF systems combine aspects of the UASB process with aspects of the AF process. Influent wastewater and recirculated effluent are distributed across the bioreactor cross section and flow upward through granular and flocculent sludge blankets where anaerobic treatment occurs. The effluent from the sludge blanket zone enters a section of media similar to that used in AF systems where gas-liquid-solids separation occurs. Treated effluent then exits the media section and is collected for discharge from the bioreactor. Gas is collected under the bioreactor cover and is transported to storage and/or use. The hybrid UASB/AF process primarily uses suspended biomass, and process loadings are similar to those used with the UASB process. The solids removal system is similar to that used with the UASB process [8].
A research study on the treatment of wastewater generated from vegetable processing was conducted. In this project, an anaerobic filter, a fluidized bed reactor, and an up-flow anaerobic sludge blanket reactor associated with an anaerobic filter were designed, constructed, and tested [5]. For the anaerobic filter, the removal efficiency for COD was reported to exceed 80% for HRT of 16 h, at temperatures ranging from 20 to 31°C. The FBAR was operated at HRT of 2 h with mean COD removal efficiency of 63%. The UASB/AF achieved mean COD removal efficiency of 80% at HRT of 6 h [17].
5. Cannery wastewater treatment with anaerobic-anoxic-aerobic system
Anoxic process is widely used in wastewater treatment. Anoxic means depletion or deficiency of oxygen. Anoxic process is a biological treatment process by which NO3-N is converted to molecular nitrogen gas in the absence of oxygen.
A system comprised of anaerobic-anoxic-aerobic reactors was tested to treat the wastewater from tuna cooker. This wastewater stream is characterized by high COD and N concentrations. The up-flow anaerobic sludge blanket reactor was used to achieve the anaerobic digestion in a two-step process. In the first, the COD concentration was varied and ORLs up to 4 g COD/(l.d) were achieved. In the second step, the 6 g COD/l and the HRT were varied between 0.5 and 0.8 day, and this step led to ORLs less than 15 g COD/(l.d). The denitrification process was carried out in an up-flow anoxic filter, and the result of the project indicated that the efficiency of this process is dependent on the supplied carbon content. For optimum carbon content, the ratio between the COD and N equalled 4 and the denitrification percentage equalled 80%. Finally, the nitrification was reported to be fixed at 100% ammonia removal regardless of the amount of carbon in the range of 0.2–0.8 g TOC/l. The variation of the recycling ratios between the denitrification and nitrification reactors in the range of 1–2.5 was found to affect the efficiency of the COD and N-removal percentage, where 90 and 60% removal for COD and N was reported at recycling ratio between 2 and 2.5 [15].
6. Uncertainty in cannery wastewater
There are several types of uncertainties that should be addressed during the design of a wastewater treatment plant, e.g. the variation in strength and quantity of wastewater entering into the plant, the diversity, and the dynamics of the microbial community. An uncertainty analysis for a pre-denitrification plant that uses an activated sludge unit was performed [18]. The unit consists of five compartments: the first two are anoxic and the last three are aerobic. Three scenarios were considered in that study that cover the uncertainty due to stoichiometric, bio-kinetic and influent parameters; uncertainty due to hydraulic behavior of the plant and mass transfer parameters; and uncertainty due to the combination of both scenarios. The study concluded that parameters related to the first and second scenarios introduce significant uncertainties in the plant performance measures. In addition, it was stated that the applied uncertainty farming technique largely affects the uncertainty estimates.
The Monte Carlo simulation was intensively used to simulate the design and upgrade of wastewater treatment plants under uncertainty in balancing effluent costs, violating effluent quality standards, predicting the disinfection performance, generating different influent compositions for posterior process performance evaluation or as a pragmatic procedure to automate the calibration of ASM models, and considering the impact of the input parameter uncertainty on the multi-criteria evaluation of control strategies at wastewater plant [19, 20, 21, 22].
Due to the complexity and non-linearity of wastewater treatment plant operations, mathematical models are generally not sufficient to predict the performance of WWTPs. Therefore, AI models have been proposed as an alternative model to linear methods. The methods for minimizing the effect of uncertainty in wastewater characteristics and wastewater flow on wastewater treatment reported in the literature have included support vector machine (SVM) and artificial neural network (ANN) [23]. An optimization model to control uncertainty in operation of wastewater treatment from the shale gas production has been reported in the literature [24]. In addition, genetic algorithms have been developed to model and optimize a biological wastewater treatment plant [25].
Information regarding uncertainty in the wastewater treatment plants in treating cannery wastewater is lacking in the literature. However, the principles governing uncertainty in wastewater treatment plants can be applied to control uncertainty in cannery wastewater treatment.
7. Conclusions
The following conclusions can be reached based on the review of literature in cannery wastewater treatment:
The wastewater that is generated in food canning industries contains high quantities of organic material, a high level of biodegradables and variable pH levels.
The food processing industry requires a large amount of potable water for a variety of non-consumption usages, such as for initial cleaning of raw material, fluming, blanching, pasteurizing, cleaning of processing equipment, and cooling of finished product.
The nature of the organic matter of cannery industry wastewater makes it suitable for biological treatment.
Flow equalization and influent pH control normally have enough diluting and neutralizing effect to permit the use of biological processes for cannery wastewater treatment.
Various treatment processes using aerobic and anaerobic treatment can be applied for the treatment of cannery wastewater, depending upon wastewater strength.
Information regarding uncertainty in wastewater treatment plants in treating cannery wastewater is lacking in the literature. However, the principles governing uncertainty in wastewater treatment plants can be applied to control uncertainty in cannery wastewater treatment.
\n',keywords:"cannery wastes, up-flow anaerobic sludge blanket, anaerobic digestion, sequencing batch reactor, three-stage aerobic rotating biological contactor, uncertainty in wastewater treatment",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/82369.pdf",chapterXML:"https://mts.intechopen.com/source/xml/82369.xml",downloadPdfUrl:"/chapter/pdf-download/82369",previewPdfUrl:"/chapter/pdf-preview/82369",totalDownloads:5,totalViews:0,totalCrossrefCites:0,dateSubmitted:"October 19th 2021",dateReviewed:"May 13th 2022",datePrePublished:"June 24th 2022",datePublished:null,dateFinished:"June 24th 2022",readingETA:"0",abstract:"This chapter reviews various methods of cannery wastewater biological treatment, namely up-flow anaerobic sludge blanket (UASB), sequencing batch reactor (SBR), three-stage aerobic rotating biological contactor (RBC), three sequentially arranged reactors (anaerobic-anoxic-aerobic reactors), lagooning, and anaerobic digestion. The general principles for dealing with the uncertainty of general wastewater treatment plants are applied to control the uncertainty in cannery wastewater treatment. An overview of on the application of Monte Carlo, support vector machine (SVM), artificial neural network (ANN), and genetic algorithm to manage the uncertainty in the biological treatment of wastewater is provided.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/82369",risUrl:"/chapter/ris/82369",signatures:"Yung-Tse Hung, Seyedkiarash Sharifiilierdy, Howard H. Paul, Christopher R. Huhnke and Rehab O. Abdel Rahman",book:{id:"10627",type:"book",title:"Engineering Problems - Uncertainties, Constraints and Optimization Techniques",subtitle:null,fullTitle:"Engineering Problems - Uncertainties, Constraints and Optimization Techniques",slug:null,publishedDate:null,bookSignature:"Dr. Marcos Sales Guerra Tsuzuki and Prof. Rehab O. O. Abdel Rahman",coverURL:"https://cdn.intechopen.com/books/images_new/10627.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-83969-368-7",printIsbn:"978-1-83969-367-0",pdfIsbn:"978-1-83969-369-4",isAvailableForWebshopOrdering:!0,editors:[{id:"146384",title:"Dr.",name:"Marcos Sales Guerra",middleName:null,surname:"Tsuzuki",slug:"marcos-sales-guerra-tsuzuki",fullName:"Marcos Sales Guerra Tsuzuki"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Cannery wastewater treatment",level:"1"},{id:"sec_3",title:"3. Aerobic treatment of cannery wastewaters",level:"1"},{id:"sec_3_2",title:"3.1 Sequencing batch reactor (SBR)",level:"2"},{id:"sec_4_2",title:"3.2 Activated sludge (AS)",level:"2"},{id:"sec_5_2",title:"3.3 Rotating biological contactor (RBC)",level:"2"},{id:"sec_6_2",title:"3.4 Aerobic lagoons (AELs)",level:"2"},{id:"sec_8",title:"4. Anaerobic treatment of cannery wastewaters",level:"1"},{id:"sec_8_2",title:"4.1 Up-flow anaerobic sludge blanket (UASB)",level:"2"},{id:"sec_9_2",title:"4.2 Anaerobic digestion",level:"2"},{id:"sec_10_2",title:"4.3 SHARON-Anammox process",level:"2"},{id:"sec_11_2",title:"4.4 Anaerobic membrane bioreactors (An-MBR)",level:"2"},{id:"sec_12_2",title:"4.5 Anaerobic filter (AF)",level:"2"},{id:"sec_13_2",title:"4.6 Blanket/anaerobic filter",level:"2"},{id:"sec_15",title:"5. Cannery wastewater treatment with anaerobic-anoxic-aerobic system",level:"1"},{id:"sec_16",title:"6. Uncertainty in cannery wastewater",level:"1"},{id:"sec_17",title:"7. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'[Teo A, Teo S. Food Canning Waste in Industrial Processes. UCSI University, 2016. 0.13140/RG.2.1.2769.4487. 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Méndez, Anammox process for nitrogen removal from anaerobically digested fish canning effluents. Water Science and Technology. 2006;53(12):265-274]'},{id:"B14",body:'[Yang J, Spanjers H, Jeison D, Van Lier JB. Impact of Na+ on biological wastewater treatment and the potential of anaerobic membrane bioreactors: A review. Critical Reviews in Environmental Science and Technology. 2013;43(24):2722-2746]'},{id:"B15",body:'[Mosquera-Corral A, Campos J, Sánchez M, Méndez R, Lema J. Combined system for biological removal of nitrogen and carbon from a fish cannery wastewater. Journal of Environmental Engineering. 2003;129(9):826-833]'},{id:"B16",body:'[Tilley E, Ulrich L, Lüthi C, Reymond P, Schertenleib R, Zurbrügg C. Compendium of sanitation systems and technologies: Eawag. 2014. Available online: https://www.eawag.ch/fileadmin/Domain1/Abteilungen/sandec/schwerpunkte/sesp/CLUES/Compendium_2nd_pdfs/Compendium_2nd_Ed_Lowres_1p.pdf (last accessed 5 June 2022)]'},{id:"B17",body:'[Fernandes JA. Applicability of a UASB/AF Reactor in the Treatment of Cannery Industry Wastewaters. (in Portuguese) MSc. Thesis. Brazil: São Carlos School of Engineering. The University of Sao Paulo; 1984]'},{id:"B18",body:'[Sin G, Gernaey KV, Neumann MB, van Loosdrecht MCM, Gujer W. Uncertainty analysis in WWTP model applications: A critical discussion using an example from design. Water Research. 2009;43(11):2894-2906]'},{id:"B19",body:'[Helton JC, Davis FJ. Latin hypercube sampling method and the propagation of uncertainty in analyses of complex systems. Reliability Engineering and System Safety. 2003;81(1):23-69]'},{id:"B20",body:'[Benedetti L, Bixio D, Vanrolleghem PA. Assessment of WWTP design and upgrade options: Balancing costs and risks of standards\' exceedance. Water Science and Technology. 2006;54(6-7):371-378]'},{id:"B21",body:'[Neumann MB, von Gunten U, Gujer W. Uncertainty in prediction of disinfection performance. 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Consequently, much of the information, for example definition of terms used, is repeated to ensure that there can be no misunderstanding of the policies that apply to each category.
",metaTitle:"Copyright Policy",metaDescription:"Copyright is the term used to describe the rights related to the publication and distribution of original works. Most importantly from a publisher's perspective, copyright governs how authors, publishers and the general public can use, publish and distribute publications.",metaKeywords:null,canonicalURL:"/page/copyright-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"Copyright is the term used to describe the rights related to the publication and distribution of original Works. Most importantly from a publisher's perspective, copyright governs how Authors, publishers and the general public can use, publish, and distribute publications.
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\\n\\nPolicy last updated: 2016-06-08
\\n"}]'},components:[{type:"htmlEditorComponent",content:'Copyright is the term used to describe the rights related to the publication and distribution of original Works. Most importantly from a publisher's perspective, copyright governs how Authors, publishers and the general public can use, publish, and distribute publications.
\n\nIntechOpen only publishes manuscripts for which it has publishing rights. This is governed by a publication agreement between the Author and IntechOpen. This agreement is accepted by the Author when the manuscript is submitted and deals with both the rights of the publisher and Author, as well as any obligations concerning a particular manuscript. However, in accepting this agreement, Authors continue to retain significant rights to use and share their publications.
\n\nHOW COPYRIGHT WORKS WITH OPEN ACCESS LICENSES?
\n\n\n\t- By accepting the agreement terms Authors retain their copyright on their Work but grant broad publishing and distribution rights to the publisher.
\n\t- Depending on the type of publication (Chapter or Long Form Monograph/Compacts; see definitions below), IntechOpen applies a Creative Commons license to the publication, allowing readers to use and share it freely.
\n\t- IntechOpen makes the publication available online under an appropriate license.
\n
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There are several ways to apply robust optimization and the choice of form is typical of the problem that is being solved. In this paper, the basic concepts of robust optimization are developed, the different types of robustness are defined in detail, the main areas in which it has been applied are described and finally, the future lines of research that appear in this area are included.",book:{id:"6587",slug:"nature-inspired-methods-for-stochastic-robust-and-dynamic-optimization",title:"Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization",fullTitle:"Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization"},signatures:"José García and Alvaro Peña",authors:[{id:"227809",title:"Ph.D.",name:"Jose",middleName:null,surname:"Garcia",slug:"jose-garcia",fullName:"Jose Garcia"},{id:"240407",title:"Dr.",name:"Alvaro",middleName:null,surname:"Peña",slug:"alvaro-pena",fullName:"Alvaro Peña"}]},{id:"51131",doi:"10.5772/63785",title:"Survey of Meta-Heuristic Algorithms for Deep Learning Training",slug:"survey-of-meta-heuristic-algorithms-for-deep-learning-training",totalDownloads:3141,totalCrossrefCites:15,totalDimensionsCites:24,abstract:"Deep learning (DL) is a type of machine learning that mimics the thinking patterns of a human brain to learn the new abstract features automatically by deep and hierarchical layers. DL is implemented by deep neural network (DNN) which has multi-hidden layers. DNN is developed from traditional artificial neural network (ANN). However, in the training process of DL, it has certain inefficiency due to very long training time required. Meta-heuristic aims to find good or near-optimal solutions at a reasonable computational cost. In this article, meta-heuristic algorithms are reviewed, such as genetic algorithm (GA) and particle swarm optimization (PSO), for traditional neural network’s training and parameter optimization. Thereafter the possibilities of applying meta-heuristic algorithms on DL training and parameter optimization are discussed.",book:{id:"5165",slug:"optimization-algorithms-methods-and-applications",title:"Optimization Algorithms",fullTitle:"Optimization Algorithms - Methods and Applications"},signatures:"Zhonghuan Tian and Simon Fong",authors:[{id:"1952",title:"Dr.",name:"Simon",middleName:null,surname:"Fong",slug:"simon-fong",fullName:"Simon Fong"},{id:"186166",title:"MSc.",name:"Zhonghuan",middleName:null,surname:"Tien",slug:"zhonghuan-tien",fullName:"Zhonghuan Tien"}]},{id:"51209",doi:"10.5772/62472",title:"A Review and Comparative Study of Firefly Algorithm and its Modified Versions",slug:"a-review-and-comparative-study-of-firefly-algorithm-and-its-modified-versions",totalDownloads:2919,totalCrossrefCites:15,totalDimensionsCites:22,abstract:"Firefly algorithm is one of the well-known swarm-based algorithms which gained popularity within a short time and has different applications. It is easy to understand and implement. The existing studies show that it is prone to premature convergence and suggest the relaxation of having constant parameters. To boost the performance of the algorithm, different modifications are done by several researchers. In this chapter, we will review these modifications done on the standard firefly algorithm based on parameter modification, modified search strategy and change the solution space to make the search easy using different probability distributions. The modifications are done for continuous as well as non-continuous problems. Different studies including hybridization of firefly algorithm with other algorithms, extended firefly algorithm for multiobjective as well as multilevel optimization problems, for dynamic problems, constraint handling and convergence study will also be briefly reviewed. A simulation-based comparison will also be provided to analyse the performance of the standard as well as the modified versions of the algorithm.",book:{id:"5165",slug:"optimization-algorithms-methods-and-applications",title:"Optimization Algorithms",fullTitle:"Optimization Algorithms - Methods and Applications"},signatures:"Waqar A. Khan, Nawaf N. Hamadneh, Surafel L. Tilahun and Jean\nM. T. Ngnotchouye",authors:[{id:"180330",title:"Dr.",name:"Surafel",middleName:null,surname:"Tilahun",slug:"surafel-tilahun",fullName:"Surafel Tilahun"},{id:"180784",title:"Dr.",name:"Waqar Ahmed",middleName:null,surname:"Khan",slug:"waqar-ahmed-khan",fullName:"Waqar Ahmed Khan"},{id:"185148",title:"Dr.",name:"Nawaf",middleName:null,surname:"Hamadneh",slug:"nawaf-hamadneh",fullName:"Nawaf Hamadneh"},{id:"185149",title:"Dr.",name:"Jean M. T.",middleName:null,surname:"Ngnotchouye",slug:"jean-m.-t.-ngnotchouye",fullName:"Jean M. T. Ngnotchouye"}]},{id:"68118",doi:"10.5772/intechopen.88185",title:"Overview of Multi-Objective Optimization Approaches in Construction Project Management",slug:"overview-of-multi-objective-optimization-approaches-in-construction-project-management",totalDownloads:1188,totalCrossrefCites:5,totalDimensionsCites:12,abstract:"The difficulties that are met in construction projects include budget issues, contractual time constraints, complying with sustainability rating systems, meeting local building codes, and achieving the desired quality level, to name but a few. Construction researchers have proposed and construction practitioners have used optimization strategies to meet various objectives over the years. They started out by optimizing one objective at a time (e.g., minimizing construction cost) while disregarding others. Because the objectives of construction projects often conflict with each other, single-objective optimization does not offer practical solutions as optimizing one objective would often adversely affect the other objectives that are not being optimized. They then experimented with multi-objective optimization. The many multi-objective optimization approaches that they used have their own advantages and drawbacks when used in some scenarios with different sets of objectives. In this chapter, a review is presented of 16 multi-objective optimization approaches used in 55 research studies performed in the construction industry and that were published in the period 2012–2016. The discussion highlights the strengths and weaknesses of these approaches when used in different scenarios.",book:{id:"8521",slug:"multicriteria-optimization-pareto-optimality-and-threshold-optimality",title:"Multicriteria Optimization",fullTitle:"Multicriteria Optimization - Pareto-Optimality and Threshold-Optimality"},signatures:"Ibraheem Alothaimeen and David Arditi",authors:[{id:"304595",title:"Dr.",name:"David",middleName:null,surname:"Arditi",slug:"david-arditi",fullName:"David Arditi"},{id:"304596",title:"Dr.",name:"Ibraheem",middleName:null,surname:"Alothaimeen",slug:"ibraheem-alothaimeen",fullName:"Ibraheem Alothaimeen"}]},{id:"61251",doi:"10.5772/intechopen.76979",title:"A Brief Survey on Intelligent Swarm-Based Algorithms for Solving Optimization Problems",slug:"a-brief-survey-on-intelligent-swarm-based-algorithms-for-solving-optimization-problems",totalDownloads:1625,totalCrossrefCites:8,totalDimensionsCites:12,abstract:"This chapter presents an overview of optimization techniques followed by a brief survey on several swarm-based natural inspired algorithms which were introduced in the last decade. These techniques were inspired by the natural processes of plants, foraging behaviors of insects and social behaviors of animals. These swam intelligent methods have been tested on various standard benchmark problems and are capable in solving a wide range of optimization issues including stochastic, robust and dynamic problems.",book:{id:"6587",slug:"nature-inspired-methods-for-stochastic-robust-and-dynamic-optimization",title:"Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization",fullTitle:"Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization"},signatures:"Siew Mooi Lim and Kuan Yew Leong",authors:[{id:"229799",title:"Dr.",name:"Siew Mooi",middleName:null,surname:"Lim",slug:"siew-mooi-lim",fullName:"Siew Mooi Lim"},{id:"231023",title:"Dr.",name:"Kuan Yew",middleName:null,surname:"Leong",slug:"kuan-yew-leong",fullName:"Kuan Yew Leong"}]}],mostDownloadedChaptersLast30Days:[{id:"60097",title:"Robust Optimization: Concepts and Applications",slug:"robust-optimization-concepts-and-applications",totalDownloads:2535,totalCrossrefCites:23,totalDimensionsCites:30,abstract:"Robust optimization is an emerging area in research that allows addressing different optimization problems and specifically industrial optimization problems where there is a degree of uncertainty in some of the variables involved. There are several ways to apply robust optimization and the choice of form is typical of the problem that is being solved. In this paper, the basic concepts of robust optimization are developed, the different types of robustness are defined in detail, the main areas in which it has been applied are described and finally, the future lines of research that appear in this area are included.",book:{id:"6587",slug:"nature-inspired-methods-for-stochastic-robust-and-dynamic-optimization",title:"Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization",fullTitle:"Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization"},signatures:"José García and Alvaro Peña",authors:[{id:"227809",title:"Ph.D.",name:"Jose",middleName:null,surname:"Garcia",slug:"jose-garcia",fullName:"Jose Garcia"},{id:"240407",title:"Dr.",name:"Alvaro",middleName:null,surname:"Peña",slug:"alvaro-pena",fullName:"Alvaro Peña"}]},{id:"76058",title:"Ultrasonic Detection of Down Syndrome Using Multiscale Quantiser with Convolutional Neural Network",slug:"ultrasonic-detection-of-down-syndrome-using-multiscale-quantiser-with-convolutional-neural-network",totalDownloads:370,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Down Syndrome is a genetic condition that occurs when there is an extra copy of a chromosome 21 in the newly formed fetus. EIF is observed as one of the possible symptoms of DS. But in comparison to the other symptoms like nasal bone hypoplasia, increased thickness in the nuchal fold, EIF is very much less prone to DS. Hence, recommending the pregnant women with EIF to undergo the diagnostic process like amniocentesis, CVS and PUBS is not always a right choice as these diagnostic processes suffer serious drawbacks like miscarriage, uterine infections. This chapter “Ultrasonic Detection of Down Syndrome Using Multiscale Quantiser With Convolutional Neural Network” presents a new ultrasonic method to detect EIF that can cause DS. Ultrasonic Detection of Down Syndrome Using Multiscale Quantiser with Convolutional Neural Network entails two stages namely i) training phase and ii) testing phase. Training phase aims at learning the features of EIF that can cause DS whereas testing phase classifies the EIF into DS positive or DS negative based on the knowledge cluster formed during the training phase. A new algorithm Multiscale Quantiser with the convolutional neural network is used in the training phase. Enhanced Learning Vector Classifier is used in the testing phase to differentiate the normal EIF from EIF causing DS. The performance of the proposed system is analysed in terms of sensitivity, accuracy and specificity.",book:{id:"9965",slug:"computational-optimization-techniques-and-applications",title:"Computational Optimization Techniques and Applications",fullTitle:"Computational Optimization Techniques and Applications"},signatures:"Michael Dinesh Simon and A.R. Kavitha",authors:[{id:"213441",title:"Dr.",name:"A.R.Kavitha",middleName:null,surname:"Balaji",slug:"a.r.kavitha-balaji",fullName:"A.R.Kavitha Balaji"},{id:"335252",title:"Dr.",name:"Michael",middleName:null,surname:"Dinesh Simon",slug:"michael-dinesh-simon",fullName:"Michael Dinesh Simon"}]},{id:"51131",title:"Survey of Meta-Heuristic Algorithms for Deep Learning Training",slug:"survey-of-meta-heuristic-algorithms-for-deep-learning-training",totalDownloads:3140,totalCrossrefCites:15,totalDimensionsCites:24,abstract:"Deep learning (DL) is a type of machine learning that mimics the thinking patterns of a human brain to learn the new abstract features automatically by deep and hierarchical layers. DL is implemented by deep neural network (DNN) which has multi-hidden layers. DNN is developed from traditional artificial neural network (ANN). However, in the training process of DL, it has certain inefficiency due to very long training time required. Meta-heuristic aims to find good or near-optimal solutions at a reasonable computational cost. In this article, meta-heuristic algorithms are reviewed, such as genetic algorithm (GA) and particle swarm optimization (PSO), for traditional neural network’s training and parameter optimization. Thereafter the possibilities of applying meta-heuristic algorithms on DL training and parameter optimization are discussed.",book:{id:"5165",slug:"optimization-algorithms-methods-and-applications",title:"Optimization Algorithms",fullTitle:"Optimization Algorithms - Methods and Applications"},signatures:"Zhonghuan Tian and Simon Fong",authors:[{id:"1952",title:"Dr.",name:"Simon",middleName:null,surname:"Fong",slug:"simon-fong",fullName:"Simon Fong"},{id:"186166",title:"MSc.",name:"Zhonghuan",middleName:null,surname:"Tien",slug:"zhonghuan-tien",fullName:"Zhonghuan Tien"}]},{id:"58127",title:"Particle Swarm Optimization Solution for Power System Operation Problems",slug:"particle-swarm-optimization-solution-for-power-system-operation-problems",totalDownloads:1663,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"Application of particle swarm optimization (PSO) algorithm on power system operation is studied in this chapter. Relay protection coordination in distribution networks and economic dispatch of generators in the grid are defined as two of power system-related optimization problems where they are solved using PSO. Two case study systems are conducted. The first case study system investigates applicability of PSO on providing proper overcurrent relay settings in the grid, while in the second case study system, the economic dispatch of a 15-unit system is solved where PSO successfully provides the optimum power output of generators with minimum fuel costs to satisfy the load demands and operation constraints. The simulation results in comparison with other methods show the effectiveness of PSO against other algorithms with higher quality of solution and less fuel costs on the same test system.",book:{id:"6363",slug:"particle-swarm-optimization-with-applications",title:"Particle Swarm Optimization with Applications",fullTitle:"Particle Swarm Optimization with Applications"},signatures:"Mostafa Kheshti and Lei Ding",authors:[{id:"120842",title:"Associate Prof.",name:"Mostafa",middleName:null,surname:"Kheshti",slug:"mostafa-kheshti",fullName:"Mostafa Kheshti"},{id:"213017",title:"Prof.",name:"Lei",middleName:null,surname:"Ding",slug:"lei-ding",fullName:"Lei Ding"}]},{id:"51209",title:"A Review and Comparative Study of Firefly Algorithm and its Modified Versions",slug:"a-review-and-comparative-study-of-firefly-algorithm-and-its-modified-versions",totalDownloads:2911,totalCrossrefCites:15,totalDimensionsCites:21,abstract:"Firefly algorithm is one of the well-known swarm-based algorithms which gained popularity within a short time and has different applications. It is easy to understand and implement. The existing studies show that it is prone to premature convergence and suggest the relaxation of having constant parameters. To boost the performance of the algorithm, different modifications are done by several researchers. In this chapter, we will review these modifications done on the standard firefly algorithm based on parameter modification, modified search strategy and change the solution space to make the search easy using different probability distributions. The modifications are done for continuous as well as non-continuous problems. Different studies including hybridization of firefly algorithm with other algorithms, extended firefly algorithm for multiobjective as well as multilevel optimization problems, for dynamic problems, constraint handling and convergence study will also be briefly reviewed. A simulation-based comparison will also be provided to analyse the performance of the standard as well as the modified versions of the algorithm.",book:{id:"5165",slug:"optimization-algorithms-methods-and-applications",title:"Optimization Algorithms",fullTitle:"Optimization Algorithms - Methods and Applications"},signatures:"Waqar A. Khan, Nawaf N. Hamadneh, Surafel L. Tilahun and Jean\nM. T. Ngnotchouye",authors:[{id:"180330",title:"Dr.",name:"Surafel",middleName:null,surname:"Tilahun",slug:"surafel-tilahun",fullName:"Surafel Tilahun"},{id:"180784",title:"Dr.",name:"Waqar Ahmed",middleName:null,surname:"Khan",slug:"waqar-ahmed-khan",fullName:"Waqar Ahmed Khan"},{id:"185148",title:"Dr.",name:"Nawaf",middleName:null,surname:"Hamadneh",slug:"nawaf-hamadneh",fullName:"Nawaf Hamadneh"},{id:"185149",title:"Dr.",name:"Jean M. T.",middleName:null,surname:"Ngnotchouye",slug:"jean-m.-t.-ngnotchouye",fullName:"Jean M. T. Ngnotchouye"}]}],onlineFirstChaptersFilter:{topicId:"969",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:319,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:133,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:16,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
\r\n\r\n\t
\r\n\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
\r\n\r\n\t
\r\n\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
\r\n\r\n\t
\r\n\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
\r\n\r\n\t
\r\n\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
",coverUrl:"https://cdn.intechopen.com/series/covers/24.jpg",latestPublicationDate:"July 5th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"262440",title:"Prof.",name:"Usha",middleName:null,surname:"Iyer-Raniga",slug:"usha-iyer-raniga",fullName:"Usha Iyer-Raniga",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRYSXQA4/Profile_Picture_2022-02-28T13:55:36.jpeg",biography:"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. Usha has been a keynote speaker as well as an invited speaker at national and international conferences, seminars and workshops. Her teaching experience includes teaching in Asian countries. She has advised Austrade, APEC, national, state and local governments. She serves as a reviewer and a member of the scientific committee for national and international refereed journals and refereed conferences. She is on the editorial board for refereed journals and has worked on Special Issues. Usha has served and continues to serve on the Boards of several not-for-profit organisations and she has also served as panel judge for a number of awards including the Premiers Sustainability Award in Victoria and the International Green Gown Awards. Usha has published over 100 publications, including research and consulting reports. Her publications cover a wide range of scientific and technical research publications that include edited books, book chapters, refereed journals, refereed conference papers and reports for local, state and federal government clients. She has also produced podcasts for various organisations and participated in media interviews. She has received state, national and international funding worth over USD $25 million. Usha has been awarded the Quarterly Franklin Membership by London Journals Press (UK). Her biography has been included in the Marquis Who's Who in the World® 2018, 2016 (33rd Edition), along with approximately 55,000 of the most accomplished men and women from around the world, including luminaries as U.N. Secretary-General Ban Ki-moon. In 2017, Usha was awarded the Marquis Who’s Who Lifetime Achiever Award.",institutionString:null,institution:{name:"RMIT University",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:5,paginationItems:[{id:"91",title:"Sustainable Economy and Fair Society",coverUrl:"https://cdn.intechopen.com/series_topics/covers/91.jpg",isOpenForSubmission:!0,annualVolume:11975,editor:{id:"181603",title:"Dr.",name:"Antonella",middleName:null,surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo",profilePictureURL:"https://mts.intechopen.com/storage/users/181603/images/system/181603.jpg",biography:"Antonella Petrillo is a Professor at the Department of Engineering of the University of Naples “Parthenope”, Italy. She received her Ph.D. in Mechanical Engineering from the University of Cassino. Her research interests include multi-criteria decision analysis, industrial plant, logistics, manufacturing and safety. She serves as an Associate Editor for the International Journal of the Analytic Hierarchy Process. She is a member of AHP Academy and a member of several editorial boards. She has over 160 Scientific Publications in International Journals and Conferences and she is the author of 5 books on Innovation and Decision Making in Industrial Applications and Engineering.",institutionString:null,institution:{name:"Parthenope University of Naples",institutionURL:null,country:{name:"Italy"}}},editorTwo:null,editorThree:null},{id:"92",title:"Health and Wellbeing",coverUrl:"https://cdn.intechopen.com/series_topics/covers/92.jpg",isOpenForSubmission:!0,annualVolume:11976,editor:{id:"348225",title:"Prof.",name:"Ann",middleName:null,surname:"Hemingway",slug:"ann-hemingway",fullName:"Ann Hemingway",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035LZFoQAO/Profile_Picture_2022-04-11T14:55:40.jpg",biography:"Professor Hemingway is a public health researcher, Bournemouth University, undertaking international and UK research focused on reducing inequalities in health outcomes for marginalised and excluded populations and more recently focused on equine assisted interventions.",institutionString:null,institution:{name:"Bournemouth University",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null},{id:"93",title:"Inclusivity and Social Equity",coverUrl:"https://cdn.intechopen.com/series_topics/covers/93.jpg",isOpenForSubmission:!0,annualVolume:11977,editor:{id:"210060",title:"Prof. Dr.",name:"Ebba",middleName:null,surname:"Ossiannilsson",slug:"ebba-ossiannilsson",fullName:"Ebba Ossiannilsson",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6LkBQAU/Profile_Picture_2022-02-28T13:31:48.png",biography:"Professor Dr. Ebba Ossiannilsson is an independent researcher, expert, consultant, quality auditor and influencer in the fields of open, flexible online and distance learning (OFDL) and the 'new normal'. Her focus is on quality, innovation, leadership, and personalised learning. She works primarily at the strategic and policy levels, both nationally and internationally, and with key international organisations. She is committed to promoting and improving OFDL in the context of SDG4 and the future of education. Ossiannilsson has more than 20 years of experience in her current field, but more than 40 years in the education sector. She works as a reviewer and expert for the European Commission and collaborates with the Joint Research Centre for Quality in Open Education. Ossiannilsson also collaborates with ITCILO and ICoBC (International Council on Badges and Credentials). She is a member of the ICDE Board of Directors and has previously served on the boards of EDEN and EUCEN. Ossiannilsson is a quality expert and reviewer for ICDE, EDEN and the EADTU. She chairs the ICDE OER Advocacy Committee and is a member of the ICDE Quality Network. She is regularly invited as a keynote speaker at conferences. She is a guest editor for several special issues and a member of the editorial board of several scientific journals. She has published more than 200 articles and is currently working on book projects in the field of OFDL. Ossiannilsson is a visiting professor at several international universities and was recently appointed Professor and Research Fellow at Victoria University of Wellington, NZ. Ossiannilsson has been awarded the following fellowships: EDEN Fellows, EDEN Council of Fellows, and Open Education Europe. She is a ICDE OER Ambassador, Open Education Europe Ambassador, GIZ Ambassador for Quality in Digital Learning, and part of the Globe-Community of Digital Learning and Champion of SPARC Europe. On a national level, she is a quality developer at the Swedish Institute for Standards (SIS) and for ISO. She is a member of the Digital Skills and Jobs Coalition Sweden and Vice President of the Swedish Association for Distance Education. She is currently working on a government initiative on quality in distance education at the National Council for Higher Education. She holds a Ph.D. from the University of Oulu, Finland.",institutionString:"Swedish Association for Distance Education, Sweden",institution:null},editorTwo:null,editorThree:null},{id:"94",title:"Climate Change and Environmental Sustainability",coverUrl:"https://cdn.intechopen.com/series_topics/covers/94.jpg",isOpenForSubmission:!0,annualVolume:11978,editor:{id:"61855",title:"Dr.",name:"Yixin",middleName:null,surname:"Zhang",slug:"yixin-zhang",fullName:"Yixin Zhang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYWJgQAO/Profile_Picture_2022-06-09T11:36:35.jpg",biography:"Professor Yixin Zhang is an aquatic ecologist with over 30 years of research and teaching experience in three continents (Asia, Europe, and North America) in Stream Ecology, Riparian Ecology, Urban Ecology, and Ecosystem Restoration and Aquatic Conservation, Human-Nature Interactions and Sustainability, Urbanization Impact on Aquatic Ecosystems. He got his Ph.D. in Animal Ecology at Umeå University in Sweden in 1998. He conducted postdoc research in stream ecology at the University of California at Santa Barbara in the USA. After that, he was a postdoc research fellow at the University of British Columbia in Canada to do research on large-scale stream experimental manipulation and watershed ecological survey in temperate rainforests of BC. He was a faculty member at the University of Hong Kong to run ecological research projects on aquatic insects, fishes, and newts in Tropical Asian streams. He also conducted research in streams, rivers, and caves in Texas, USA, to study the ecology of macroinvertebrates, big-claw river shrimp, fish, turtles, and bats. Current research interests include trophic flows across ecosystems; watershed impacts of land-use change on biodiversity and ecosystem functioning; ecological civilization and water resource management; urban ecology and urban/rural sustainable development.",institutionString:null,institution:{name:"Soochow University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null},{id:"95",title:"Urban Planning and Environmental Management",coverUrl:"https://cdn.intechopen.com/series_topics/covers/95.jpg",isOpenForSubmission:!0,annualVolume:11979,editor:{id:"181079",title:"Dr.",name:"Christoph",middleName:null,surname:"Lüthi",slug:"christoph-luthi",fullName:"Christoph Lüthi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHSqQAO/Profile_Picture_2022-04-12T15:51:33.png",biography:"Dr. Christoph Lüthi is an urban infrastructure planner with over 25 years of experience in planning and design of urban infrastructure in middle and low-income countries. He holds a Master’s Degree in Urban Development Planning from the University College of London (UCL), and a Ph.D. in Urban Planning & Engineering from TU Berlin. He has conducted applied research on urban planning and infrastructure issues in over 20 countries in Africa and Asia. In 2005 he joined Eawag-Sandec as Leader of the Strategic Environmental Sanitation Planning Group. 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He collaborates with the Environmental Resources Analysis Research Group (ARAM), University of Extremadura (UEx), Spain; VALORIZA - Research Center for the Enhancement of Endogenous Resources, Polytechnic Institute of Portalegre (IPP), Portugal; Centre for Tourism Research, Development and Innovation (CITUR), Madeira, Portugal; and AQUAGEO Research Group, University of Campinas (UNICAMP), Brazil.",institutionString:"University of Johannesburg, South Africa and WSB University, Poland",institution:{name:"University of Johannesburg",institutionURL:null,country:{name:"South Africa"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:58,paginationItems:[{id:"81961",title:"Antioxidants as an Adjuncts to Periodontal Therapy",doi:"10.5772/intechopen.105016",signatures:"Sura Dakhil Jassim and Ali Abbas Abdulkareem",slug:"antioxidants-as-an-adjuncts-to-periodontal-therapy",totalDownloads:3,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Dental Trauma",coverURL:"https://cdn.intechopen.com/books/images_new/11567.jpg",subseries:{id:"2",title:"Prosthodontics and Implant Dentistry"}}},{id:"82357",title:"Caries Management Aided by Fluorescence-Based Devices",doi:"10.5772/intechopen.105567",signatures:"Atena Galuscan, Daniela Jumanca and Aurora Doris Fratila",slug:"caries-management-aided-by-fluorescence-based-devices",totalDownloads:4,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Dental Caries - The Selection of Restoration Methods and Restorative Materials",coverURL:"https://cdn.intechopen.com/books/images_new/11565.jpg",subseries:{id:"1",title:"Oral Health"}}},{id:"81894",title:"Diet and Nutrition and Their Relationship with Early Childhood Dental Caries",doi:"10.5772/intechopen.105123",signatures:"Luanna Gonçalves Ferreira, Giuliana de Campos Chaves Lamarque and Francisco Wanderley Garcia Paula-Silva",slug:"diet-and-nutrition-and-their-relationship-with-early-childhood-dental-caries",totalDownloads:11,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Dental Caries - The Selection of Restoration Methods and Restorative Materials",coverURL:"https://cdn.intechopen.com/books/images_new/11565.jpg",subseries:{id:"1",title:"Oral Health"}}},{id:"81595",title:"Prosthetic Concepts in Dental Implantology",doi:"10.5772/intechopen.104725",signatures:"Ivica Pelivan",slug:"prosthetic-concepts-in-dental-implantology",totalDownloads:27,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg",subseries:{id:"2",title:"Prosthodontics and Implant Dentistry"}}}]},overviewPagePublishedBooks:{paginationCount:8,paginationItems:[{type:"book",id:"6668",title:"Dental Caries",subtitle:"Diagnosis, Prevention and Management",coverURL:"https://cdn.intechopen.com/books/images_new/6668.jpg",slug:"dental-caries-diagnosis-prevention-and-management",publishedDate:"September 19th 2018",editedByType:"Edited by",bookSignature:"Zühre Akarslan",hash:"b0f7667770a391f772726c3013c1b9ba",volumeInSeries:1,fullTitle:"Dental Caries - Diagnosis, Prevention and Management",editors:[{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. 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