Specification of single‐beam echo sounder Simrad EK15.
\\n\\n
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"10006",leadTitle:null,fullTitle:"Remote Sensing",title:"Remote Sensing",subtitle:null,reviewType:"peer-reviewed",abstract:"This Edited Volume is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Remote Sensing. The book comprises single chapters authored by various researchers and edited by an expert active in this research area. All chapters are complete in themselves but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on this field of study, and open new possible research paths for further novel developments.",isbn:"978-1-83880-979-9",printIsbn:"978-1-83880-978-2",pdfIsbn:"978-1-83880-980-5",doi:"10.5772/intechopen.87829",price:119,priceEur:129,priceUsd:155,slug:"remote-sensing",numberOfPages:140,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"ccf3326511ecfc48a7b5b7a4fa15e6c5",bookSignature:"Andrew Hammond and Patrick Keleher",publishedDate:"December 8th 2021",coverURL:"https://cdn.intechopen.com/books/images_new/10006.jpg",numberOfDownloads:2365,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:1,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:1,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 20th 2020",dateEndSecondStepPublish:"June 10th 2020",dateEndThirdStepPublish:"August 9th 2020",dateEndFourthStepPublish:"October 28th 2020",dateEndFifthStepPublish:"December 27th 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"259487",title:"Dr.",name:"Andrew",middleName:null,surname:"Hammond",slug:"andrew-hammond",fullName:"Andrew Hammond",profilePictureURL:"https://mts.intechopen.com/storage/users/259487/images/system/259487.jpg",biography:"Dr. Hammond is a Senior Lecturer in Geoscience within the School of Engineering & Technology at Central Queensland University’s Rockhampton Campus, Central Queensland, Australia. He holds undergraduate degrees in Geology and Geography from the University of Tasmania and postgraduate degrees, Master of Applied Science in Pedology from the University of Canterbury, and Ph.D. in Earth Science from Massey University, both in New Zealand. His research interests are basin tectonics and stratigraphy, sedimentology, soil/regolith geology, hydrogeology, geohazards, mining education, and the use and interpretation of geospatial imagery for environmental assessment and land resource management. He has over 30 years\\' geoscience consultancy, research, and teaching experience having worked in a range of geological landscapes within Australia and New Zealand. He held senior research scientist positions in State (Tasmania) and Australian Government agencies and as a researcher in Queensland university research centers.",institutionString:"Central Queensland University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Central Queensland University",institutionURL:null,country:{name:"Australia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"320735",title:"Dr.",name:"Patrick",middleName:null,surname:"Keleher",slug:"patrick-keleher",fullName:"Patrick Keleher",profilePictureURL:"https://mts.intechopen.com/storage/users/320735/images/system/320735.jpg",biography:"Dr. Patrick Keleher has qualifications in physics, mathematics, education, robotics and management psychology. His career has focused on developing and delivering innovative curriculum in the areas of physics, mathematics, maintenance engineering, chemistry, Futures Studies, control systems and environmental science. Dr. Keleher has conducted research, including the supervision of undergraduate and postgraduate candidates, into the areas of maintenance engineering, environmental monitoring, management practices and work-integrated learning. He has served as a visiting professor and/or a keynote speaker at the Open University, Milton Keynes, United Kingdom, the Duale Hochschule Baden-Württemberg Co-operative University (DHBW), Ravensburg, Germany and at Beijing University of Technology, Beijing, China. Delivering workshops and keynotes on such diverse topics as Work Integrated Learning, Futures Studies, Corporate Governance, Intercultural Management and Engineering Professional Standards. Dr. Keleher has been the recipient of a CQUniversity Vice Chancellor’s Awards for Outstanding Contributions to Learning and Teaching for the design and delivery of two undergraduate first-year physics units. He has been acknowledged as a distinguished scholar, as a Fellow of the Practice-Based Professional Learning Centre for Excellence in Teaching and Learning (CETL), at The Open University, Milton Keynes, United Kingdom.",institutionString:"Central Queensland University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Central Queensland University",institutionURL:null,country:{name:"Australia"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"637",title:"Spatial Analysis",slug:"spatial-analysis"}],chapters:[{id:"74625",title:"Lidar Observations in South America. Part I - Mesosphere and Stratosphere",doi:"10.5772/intechopen.95038",slug:"lidar-observations-in-south-america-part-i-mesosphere-and-stratosphere",totalDownloads:368,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"South America covers a large area of the globe and plays a fundamental function in its climate change, geographical features, and natural resources. However, it still is a developing area, and natural resource management and energy production are far from a sustainable framework, impacting the air quality of the area and needs much improvement in monitoring. There are significant activities regarding laser remote sensing of the atmosphere at different levels for different purposes. Among these activities, we can mention the mesospheric probing of sodium measurements and stratospheric monitoring of ozone, and the study of wind and gravity waves. Some of these activities are long-lasting and count on the support from the Latin American Lidar Network (LALINET). We intend to pinpoint the most significant scientific achievements and show the potential of carrying out remote sensing activities in the continent and show its correlations with other earth science connections and synergies. In Part I of this chapter, we will present an overview and significant results of lidar observations in the mesosphere and stratosphere. Part II will be dedicated to tropospheric observations.",signatures:"Eduardo Landulfo, Alexandre Cacheffo, Alexandre Calzavara Yoshida, Antonio Arleques Gomes, Fábio Juliano da Silva Lopes, Gregori de Arruda Moreira, Jonatan João da Silva, Vania Andrioli, Alexandre Pimenta, Chi Wang, Jiyao Xu, Maria Paulete Pereira Martins, Paulo Batista, Henrique de Melo Jorge Barbosa, Diego Alves Gouveia, Boris Barja González, Felix Zamorano, Eduardo Quel, Clodomyra Pereira, Elian Wolfram, Facundo Ismael Casasola, Facundo Orte, Jacobo Omar Salvador, Juan Vicente Pallotta, Lidia Ana Otero, Maria Prieto, Pablo Roberto Ristori, Silvina Brusca, John Henry Reina Estupiñan, Estiven Sanchez Barrera, Juan Carlos Antuña-Marrero, Ricardo Forno, Marcos Andrade, Judith Johanna Hoelzemann, Anderson Guimarães Guedes, Cristina Tobler Sousa, Daniel Camilo Fortunato dos Santos Oliveira, Ediclê de Souza Fernandes Duarte, Marcos Paulo Araújo da Silva and Renata Sammara da Silva Santos",downloadPdfUrl:"/chapter/pdf-download/74625",previewPdfUrl:"/chapter/pdf-preview/74625",authors:[{id:"144711",title:"Dr.",name:"Eduardo",surname:"Landulfo",slug:"eduardo-landulfo",fullName:"Eduardo Landulfo"},{id:"329343",title:"Dr.",name:"Alexandre",surname:"Cacheffo",slug:"alexandre-cacheffo",fullName:"Alexandre Cacheffo"},{id:"334022",title:"Dr.",name:"Pablo",surname:"Ristori",slug:"pablo-ristori",fullName:"Pablo Ristori"},{id:"334023",title:"Dr.",name:"Juan-Carlos",surname:"Antuña-Marrero",slug:"juan-carlos-antuna-marrero",fullName:"Juan-Carlos Antuña-Marrero"},{id:"337104",title:"Dr.",name:"Paulo",surname:"Batista",slug:"paulo-batista",fullName:"Paulo Batista"},{id:"337105",title:"Dr.",name:"Alexandre",surname:"Pimenta",slug:"alexandre-pimenta",fullName:"Alexandre Pimenta"},{id:"337106",title:"Dr.",name:"Maria",surname:"Martins",slug:"maria-martins",fullName:"Maria Martins"},{id:"337107",title:"Dr.",name:"Vania",surname:"Andrioli",slug:"vania-andrioli",fullName:"Vania Andrioli"},{id:"337108",title:"Dr.",name:"Chi",surname:"Wang",slug:"chi-wang",fullName:"Chi Wang"},{id:"337109",title:"Dr.",name:"Jiyao",surname:"Xu",slug:"jiyao-xu",fullName:"Jiyao Xu"},{id:"337185",title:"Dr.",name:"Boris",surname:"Barja González",slug:"boris-barja-gonzalez",fullName:"Boris Barja González"},{id:"337186",title:"Dr.",name:"Diego Alves",surname:"Gouveia",slug:"diego-alves-gouveia",fullName:"Diego Alves Gouveia"},{id:"337187",title:"Dr.",name:"Eduardo",surname:"Quel",slug:"eduardo-quel",fullName:"Eduardo Quel"},{id:"337189",title:"Prof.",name:"Felix",surname:"Zamorano",slug:"felix-zamorano",fullName:"Felix Zamorano"},{id:"337190",title:"Prof.",name:"Gregori Arruda",surname:"Moreira",slug:"gregori-arruda-moreira",fullName:"Gregori Arruda Moreira"},{id:"337846",title:"Prof.",name:"Henrique",surname:"Barbosa",slug:"henrique-barbosa",fullName:"Henrique Barbosa"},{id:"337848",title:"Dr.",name:"Jacobo",surname:"Salvador",slug:"jacobo-salvador",fullName:"Jacobo Salvador"},{id:"337850",title:"Dr.",name:"Lidia",surname:"Otero",slug:"lidia-otero",fullName:"Lidia Otero"},{id:"337851",title:"Prof.",name:"Marcos",surname:"Andrade",slug:"marcos-andrade",fullName:"Marcos Andrade"},{id:"337852",title:"Prof.",name:"Ricardo",surname:"Forno",slug:"ricardo-forno",fullName:"Ricardo Forno"},{id:"337853",title:"Prof.",name:"John",surname:"Reina",slug:"john-reina",fullName:"John Reina"},{id:"337854",title:"Dr.",name:"Estivén",surname:"Sanchez",slug:"estiven-sanchez",fullName:"Estivén Sanchez"},{id:"337855",title:"Prof.",name:"Alexandre",surname:"Yoshida",slug:"alexandre-yoshida",fullName:"Alexandre Yoshida"},{id:"337857",title:"Prof.",name:"Fabio",surname:"Lopes",slug:"fabio-lopes",fullName:"Fabio Lopes"},{id:"338860",title:"Dr.",name:"Facundo",surname:"Casasola",slug:"facundo-casasola",fullName:"Facundo Casasola"},{id:"338873",title:"Dr.",name:"Clodomira",surname:"Pereyra",slug:"clodomira-pereyra",fullName:"Clodomira Pereyra"},{id:"338875",title:"Dr.",name:"Maria",surname:"Prietro",slug:"maria-prietro",fullName:"Maria Prietro"},{id:"338876",title:"Dr.",name:"Silvina",surname:"Brusca",slug:"silvina-brusca",fullName:"Silvina Brusca"},{id:"339163",title:"Dr.",name:"Cristina",surname:"Sousa",slug:"cristina-sousa",fullName:"Cristina Sousa"},{id:"339164",title:"MSc.",name:"Daniel",surname:"Santos",slug:"daniel-santos",fullName:"Daniel Santos"},{id:"339166",title:"Dr.",name:"Ediclê",surname:"Duarte",slug:"edicle-duarte",fullName:"Ediclê Duarte"},{id:"339167",title:"Dr.",name:"Elena",surname:"Montilla-Rosero",slug:"elena-montilla-rosero",fullName:"Elena Montilla-Rosero"},{id:"339169",title:"Prof.",name:"Judith",surname:"Hoelzemann",slug:"judith-hoelzemann",fullName:"Judith Hoelzemann"},{id:"339170",title:"MSc.",name:"Marcos",surname:"Araujo",slug:"marcos-araujo",fullName:"Marcos Araujo"},{id:"339171",title:"Dr.",name:"Jonatan",surname:"Da Silva",slug:"jonatan-da-silva",fullName:"Jonatan Da Silva"},{id:"339172",title:"Dr.",name:"Juan",surname:"Pallotta",slug:"juan-pallotta",fullName:"Juan Pallotta"},{id:"339173",title:"Dr.",name:"Eliam",surname:"Wolfram",slug:"eliam-wolfram",fullName:"Eliam Wolfram"},{id:"339174",title:"Dr.",name:"Facundo",surname:"Orte",slug:"facundo-orte",fullName:"Facundo Orte"},{id:"339175",title:"BSc.",name:"Renata",surname:"Sammara",slug:"renata-sammara",fullName:"Renata Sammara"},{id:"339176",title:"MSc.",name:"Antonio",surname:"Arleques",slug:"antonio-arleques",fullName:"Antonio Arleques"}],corrections:null},{id:"74607",title:"Lidar Observations in South America. Part II - Troposphere",doi:"10.5772/intechopen.95451",slug:"lidar-observations-in-south-america-part-ii-troposphere",totalDownloads:444,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In Part II of this chapter, we intend to show the significant advances and results concerning aerosols’ tropospheric monitoring in South America. The tropospheric lidar monitoring is also supported by the Latin American Lidar Network (LALINET). It is concerned about aerosols originating from urban pollution, biomass burning, desert dust, sea spray, and other primary sources. Cloud studies and their impact on radiative transfer using tropospheric lidar measurements are also presented.",signatures:"Eduardo Landulfo, Alexandre Cacheffo, Alexandre Calzavara Yoshida, Antonio Arleques Gomes, Fábio Juliano da Silva Lopes, Gregori de Arruda Moreira, Jonatan João da Silva, Vania Andrioli, Alexandre Pimenta, Chi Wang, Jiyao Xu, Maria Paulete Pereira Martins, Paulo Batista, Henrique de Melo Jorge Barbosa, Diego Alves Gouveia, Boris Barja González, Felix Zamorano, Eduardo Quel, Clodomyra Pereira, Elian Wolfram, Facundo Ismael Casasola, Facundo Orte, Jacobo Omar Salvador, Juan Vicente Pallotta, Lidia Ana Otero, Maria Prieto, Pablo Roberto Ristori, Silvina Brusca, John Henry Reina Estupiñan, Estiven Sanchez Barrera, Juan Carlos Antuña-Marrero, Ricardo Forno, Marcos Andrade, Judith Johanna Hoelzemann, Anderson Guimarães Guedes, Cristina Tobler Sousa, Daniel Camilo Fortunato dos Santos Oliveira, Ediclê de Souza Fernandes Duarte, Marcos Paulo Araújo da Silva and Renata Sammara da Silva Santos",downloadPdfUrl:"/chapter/pdf-download/74607",previewPdfUrl:"/chapter/pdf-preview/74607",authors:[{id:"144711",title:"Dr.",name:"Eduardo",surname:"Landulfo",slug:"eduardo-landulfo",fullName:"Eduardo Landulfo"},{id:"329343",title:"Dr.",name:"Alexandre",surname:"Cacheffo",slug:"alexandre-cacheffo",fullName:"Alexandre Cacheffo"},{id:"334022",title:"Dr.",name:"Pablo",surname:"Ristori",slug:"pablo-ristori",fullName:"Pablo Ristori"},{id:"337104",title:"Dr.",name:"Paulo",surname:"Batista",slug:"paulo-batista",fullName:"Paulo Batista"},{id:"337105",title:"Dr.",name:"Alexandre",surname:"Pimenta",slug:"alexandre-pimenta",fullName:"Alexandre Pimenta"},{id:"337106",title:"Dr.",name:"Maria",surname:"Martins",slug:"maria-martins",fullName:"Maria Martins"},{id:"337107",title:"Dr.",name:"Vania",surname:"Andrioli",slug:"vania-andrioli",fullName:"Vania Andrioli"},{id:"337108",title:"Dr.",name:"Chi",surname:"Wang",slug:"chi-wang",fullName:"Chi Wang"},{id:"337109",title:"Dr.",name:"Jiyao",surname:"Xu",slug:"jiyao-xu",fullName:"Jiyao Xu"},{id:"337185",title:"Dr.",name:"Boris",surname:"Barja González",slug:"boris-barja-gonzalez",fullName:"Boris Barja González"},{id:"337186",title:"Dr.",name:"Diego Alves",surname:"Gouveia",slug:"diego-alves-gouveia",fullName:"Diego Alves Gouveia"},{id:"337189",title:"Prof.",name:"Felix",surname:"Zamorano",slug:"felix-zamorano",fullName:"Felix Zamorano"},{id:"337190",title:"Prof.",name:"Gregori Arruda",surname:"Moreira",slug:"gregori-arruda-moreira",fullName:"Gregori Arruda Moreira"},{id:"337846",title:"Prof.",name:"Henrique",surname:"Barbosa",slug:"henrique-barbosa",fullName:"Henrique Barbosa"},{id:"337851",title:"Prof.",name:"Marcos",surname:"Andrade",slug:"marcos-andrade",fullName:"Marcos Andrade"},{id:"337852",title:"Prof.",name:"Ricardo",surname:"Forno",slug:"ricardo-forno",fullName:"Ricardo Forno"},{id:"337853",title:"Prof.",name:"John",surname:"Reina",slug:"john-reina",fullName:"John Reina"},{id:"337854",title:"Dr.",name:"Estivén",surname:"Sanchez",slug:"estiven-sanchez",fullName:"Estivén Sanchez"},{id:"337855",title:"Prof.",name:"Alexandre",surname:"Yoshida",slug:"alexandre-yoshida",fullName:"Alexandre Yoshida"},{id:"337857",title:"Prof.",name:"Fabio",surname:"Lopes",slug:"fabio-lopes",fullName:"Fabio Lopes"},{id:"338873",title:"Dr.",name:"Clodomira",surname:"Pereyra",slug:"clodomira-pereyra",fullName:"Clodomira Pereyra"},{id:"338875",title:"Dr.",name:"Maria",surname:"Prietro",slug:"maria-prietro",fullName:"Maria Prietro"},{id:"338876",title:"Dr.",name:"Silvina",surname:"Brusca",slug:"silvina-brusca",fullName:"Silvina Brusca"},{id:"339163",title:"Dr.",name:"Cristina",surname:"Sousa",slug:"cristina-sousa",fullName:"Cristina Sousa"},{id:"339166",title:"Dr.",name:"Ediclê",surname:"Duarte",slug:"edicle-duarte",fullName:"Ediclê Duarte"},{id:"339169",title:"Prof.",name:"Judith",surname:"Hoelzemann",slug:"judith-hoelzemann",fullName:"Judith Hoelzemann"},{id:"339172",title:"Dr.",name:"Juan",surname:"Pallotta",slug:"juan-pallotta",fullName:"Juan Pallotta"},{id:"339173",title:"Dr.",name:"Eliam",surname:"Wolfram",slug:"eliam-wolfram",fullName:"Eliam Wolfram"},{id:"339174",title:"Dr.",name:"Facundo",surname:"Orte",slug:"facundo-orte",fullName:"Facundo Orte"},{id:"339175",title:"BSc.",name:"Renata",surname:"Sammara",slug:"renata-sammara",fullName:"Renata Sammara"},{id:"343929",title:"Ph.D. Student",name:"Antonio",surname:"Gomes",slug:"antonio-gomes",fullName:"Antonio Gomes"},{id:"343930",title:"Dr.",name:"Jonatan João",surname:"da Silva",slug:"jonatan-joao-da-silva",fullName:"Jonatan João da Silva"},{id:"343931",title:"Dr.",name:"Eduardo",surname:"Quel",slug:"eduardo-quel",fullName:"Eduardo Quel"},{id:"343932",title:"Dr.",name:"Facundo Ismael",surname:"Casasola",slug:"facundo-ismael-casasola",fullName:"Facundo Ismael Casasola"},{id:"343934",title:"Dr.",name:"Jacobo Omar",surname:"Salvador",slug:"jacobo-omar-salvador",fullName:"Jacobo Omar Salvador"},{id:"343935",title:"Dr.",name:"Lidia Ana",surname:"Otero",slug:"lidia-ana-otero",fullName:"Lidia Ana Otero"},{id:"343936",title:"Dr.",name:"Juan Carlos",surname:"Antuña-Marrero",slug:"juan-carlos-antuna-marrero",fullName:"Juan Carlos Antuña-Marrero"},{id:"343937",title:"Dr.",name:"Anderson",surname:"Guedes",slug:"anderson-guedes",fullName:"Anderson Guedes"},{id:"343938",title:"Dr.",name:"Daniel Camilo Fortunato",surname:"dos Santos Oliveira",slug:"daniel-camilo-fortunato-dos-santos-oliveira",fullName:"Daniel Camilo Fortunato dos Santos Oliveira"},{id:"343939",title:"Dr.",name:"Marcos Paulo",surname:"Araújo da Silva",slug:"marcos-paulo-araujo-da-silva",fullName:"Marcos Paulo Araújo da Silva"}],corrections:null},{id:"74569",title:"Application of Remote Sensing in Natural Sciences",doi:"10.5772/intechopen.94468",slug:"application-of-remote-sensing-in-natural-sciences",totalDownloads:132,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Generally, the term biomass is used for all materials originating from photosynthesis. However, biomass can equally apply to animals. Conservation and management of biomass is very important. There are various ways and methods for biomass evaluation. One of these methods is remote sensing. Remote sensing provides information about biomass, but also about biodiversity and environmental factors estimation over a wide area. The great potential of remote sensing has received considerable attention over the last few decades in many different areas in biological sciences including nutrient status assessment, weed abundance, deforestation, glacial features in Arctic and Antarctic regions, depth sounding of coastal and ocean depths, and density mapping.",signatures:"Ehsan Atazadeh and Mostafa Mahdavifard",downloadPdfUrl:"/chapter/pdf-download/74569",previewPdfUrl:"/chapter/pdf-preview/74569",authors:[{id:"27584",title:"Dr.",name:"Ehsan",surname:"Atazadeh",slug:"ehsan-atazadeh",fullName:"Ehsan Atazadeh"}],corrections:null},{id:"73665",title:"Assessment of Ecological Disturbance Caused by Flood and Fire in Assam Forests, India, Using MODIS Time Series Data of 2001-2011",doi:"10.5772/intechopen.94282",slug:"assessment-of-ecological-disturbance-caused-by-flood-and-fire-in-assam-forests-india-using-modis-tim",totalDownloads:378,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The forest area of Assam State is known for its rich biodiversity. In the present study, the disturbance regime within the Assam forest area caused by periodic flood and forest fire, was assessed using the Moderate Resolution Imaging Spectroradiometer (MODIS) time-series (2001–2011) data. The MODIS Global Disturbance Index (MGDI) images were generated using MODIS derived Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) images. The temporal intensity of flood and forest fire in sixteen representative forests was analyzed to develop the MGDI based thresholds for detecting the disturbed area. The threshold for the non-instantaneous disturbance, i.e. flood, was found to be 107% whereas it was 111% for instantaneous disturbance, i.e. forest fire. The thresholds were applied on the MGDI images to delineate disturbed caused by flood and fire, separately for each year. The time-series disturbance areas were integrated over the years (2001–2011) to generate the classified disturbance prone maps.",signatures:"Dibyendu Dutta, Akanksha Balha, Prabir Kumar Das, Pragyan Jain, Libeesh Lukose and Wasim Akram",downloadPdfUrl:"/chapter/pdf-download/73665",previewPdfUrl:"/chapter/pdf-preview/73665",authors:[{id:"290483",title:"Dr.",name:"Dibyendu",surname:"Dutta",slug:"dibyendu-dutta",fullName:"Dibyendu Dutta"},{id:"330054",title:"Ms.",name:"Akanksha",surname:"Balha",slug:"akanksha-balha",fullName:"Akanksha Balha"},{id:"330055",title:"Mr.",name:"Prabir Kumar",surname:"Das",slug:"prabir-kumar-das",fullName:"Prabir Kumar Das"},{id:"330057",title:"Mr.",name:"Pragyan",surname:"Jain",slug:"pragyan-jain",fullName:"Pragyan Jain"},{id:"330058",title:"Mr.",name:"Libeesh",surname:"Lukose",slug:"libeesh-lukose",fullName:"Libeesh Lukose"},{id:"330059",title:"Mr.",name:"Wasim",surname:"Akram",slug:"wasim-akram",fullName:"Wasim Akram"}],corrections:null},{id:"73560",title:"Delineation of Open-Pit Mining Boundaries on Multispectral Imagery",doi:"10.5772/intechopen.94120",slug:"delineation-of-open-pit-mining-boundaries-on-multispectral-imagery",totalDownloads:348,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"During the last decades, monitoring the spatial growth of open-pit mining areas has become a common procedure in an effort to comprehend the influence that mining activities have on the adjacent land-use/land-cover types. Various case studies have been presented, focusing on land-cover mapping of complex mining landscapes. They highlight that a rapid as well as accurate approach is critical. This paper presents a methodological framework for a rapid delineation of open-pit mining area boundaries. For that purpose an Object-Based Image Analysis (OBIA) methodology is implemented. Sentinel-2 data were obtained and the Mean-Shift segmentation algorithm was employed. Among the many methods that have been presented in literature in order to evaluate the performance of an image segmentation, an unsupervised approach is carried out. A quantitative evaluation of segmentation accuracy leads to a more targeted selection of segmentation parameter values and as a consequence is of utmost importance. The proposed methodology was mainly conducted through python scripts and may constitute a guide for relevant studies.",signatures:"Ioannis Kotaridis and Maria Lazaridou",downloadPdfUrl:"/chapter/pdf-download/73560",previewPdfUrl:"/chapter/pdf-preview/73560",authors:[{id:"323304",title:"Associate Prof.",name:"Maria",surname:"Lazaridou",slug:"maria-lazaridou",fullName:"Maria Lazaridou"},{id:"323305",title:"MSc.",name:"Ioannis",surname:"Kotaridis",slug:"ioannis-kotaridis",fullName:"Ioannis Kotaridis"}],corrections:null},{id:"76031",title:"Stereoscopic Precision of the Large Format Digital Cameras",doi:"10.5772/intechopen.97125",slug:"stereoscopic-precision-of-the-large-format-digital-cameras",totalDownloads:209,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Stereoscopic vision is fundamental in the task of photogrammetric restitution (stereo compilation) in which, by inserting a floating mark in the 3D observation of pairs of images, it is possible to draw the elements of the terrain in space and obtain cartography of a part of the land cover from aerial images. Initially with film photographs, which were later scanned, and finally with large format digital cameras that began in the 2000s, photogrammetry has undergone a series of technological revolutions up to the present time. In this chapter, after a brief exposition of the basic principles of photogrammetric restitution, a review of current large-format digital cameras and their main implications in restitution is made, which, despite the advances and other similar semi-automatic products (DTM, orthophoto) is still manual and must be operated by a person with the implications that this entails in stereoscopic vision.",signatures:"Benjamin Arias-Perez",downloadPdfUrl:"/chapter/pdf-download/76031",previewPdfUrl:"/chapter/pdf-preview/76031",authors:[{id:"100713",title:"Dr.",name:"Benjamin",surname:"Arias-Perez",slug:"benjamin-arias-perez",fullName:"Benjamin Arias-Perez"}],corrections:null},{id:"73376",title:"Remote Sensing Applications in Disease Mapping",doi:"10.5772/intechopen.93652",slug:"remote-sensing-applications-in-disease-mapping",totalDownloads:489,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Disease mapping utilizes disease maps as visual representations of sophisticated geographic data that provide a general overview of the disease situation in a defined geographic area. Epidemiology is concerned with investigating the causes of diseases, and often, these causes vary in frequency and in space. This variation in space gave a niche to remote sensing to find its way into the public health domain as disease researchers sought to investigate the explaining environmental and climatic factors. Studies have demonstrated the potential offered by remote sensing application to disease mapping and epidemiology and to support surveillance and control efforts. We used some examples from a case study conducted in Eswatini in Southern Africa. Remote sensing imagery when combined with GIS spatial analyses techniques could support and guide existing disease surveillance and control programs at local, regional, and even continental scales. Researchers have also studied factors influencing the patterns and distributions of vector-borne diseases at a variety of landscape scales. However, successful application of remote sensing technology depends on the ability of nonexperts’ remotely sensed data and end users to access, retrieve, and analyze the data captured from satellites. 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Underwater acoustics technologies are frequently used to measure the abundance and biomass of fish [1]. The quantitative relationship between the size of a fish and its target strength (TS) and the intensity of the echo returned from the fish are important [2]. The swim bladder of fish is responsible for most of the reflected sounds [3]. TS of fish was determined also by size and shape of swim bladder [4, 5]. The acoustic target strength of a fish is required to enable the performance of present and future sonar equipment to be determinates for fish targets. Target strength is a logarithmic measure of the energy scattered by an object back toward the source and is a function of the size, shape, orientation, and material properties of the target [6].
A physical‐based model of the acoustic scattering from the targets is required to convert acoustic backscatter measurements into units of fish density and biomass [7]. The physics‐based scattering model requires input parameters describing the acoustic frequency of echo sounder system and the target (shape, length, orientation relative to the acoustic wave, and material properties) [8]. The properties of fish for acoustic modeling are ratio of fish density and seawater density (g) and ratio of the speed of sound in fish and the sound speed of seawater (h) [9, 10]. One purpose of this study was to examine the influence of material properties, specifically
Acoustic data were collected in the water tank of the Ocean Acoustics Laboratory Department of Marine Science and Technology Bogor Agricultural University. The echo sounder used in the studies was 200‐kHz single‐beam SIMRAD EK15. For the numerical model of distorted‐wave born approximation (DWBA) purpose, we combine this instrument with 50 kHz. The specification of single‐beam echo sounder was shown in Table 1. The echo sounder was calibrated with standard copper spheres as recommended by the manufacturer. The program designed was used to calibrate the single‐beam units. Single‐beam data were analyzed using Sonar 5 software (developed by Helge Balk and T. Lindem, Institute of Physics, the University of Oslo, Norway) and Matlab. This program used the algorithm to derive fish target‐strength distributions from the measured distribution of peak voltage response from single‐fish echoes (40 log R TVG function) [11]. Single‐fish echoes are defined as echoes with less than twice the pulse length [11]. Due to the echo sounder‐hardware noise and software limitation, we used −55 dB as the smallest target‐strength group for the single‐beam sonar. The method provides information for species identification, makes it possible to measure the fish length of individual fish, and provides information on fish behavior. Flow of research was shown in Figure 1. Beam pattern of transducer
Frequency [kHz] | 200 |
Pulse duration [μs] | 80 |
Ping rate [Hz] | 40 |
Ping interval [ms] | 500 |
Beam width [degrees] | 26 |
Output power [W] | 45 |
Bandwidth [Hz] | 3088 |
Specification of single‐beam echo sounder Simrad EK15.
Flowchart of data acquisition system.
The theoretical scattering model used was distorted wave born approximation (DWBA). The DWBA model was originally used for weak scatterers such as zooplankton and micronecton. However, it has also been applied to fish. The DWBA model is valid for all acoustic frequencies, can be evaluated for all angles of orientation [12, 13], and can be applied to arbitrary shapes. DWBA model is valid when the incident acoustic wave is higher than the scattered value. Formulation of this model involved the incident acoustic wave number inside the integral. The amplitude of fish backscattering is given by
The terms
where
This formulation is simplified to a line integral for underwater target that is axis symmetric at any point along the deformed axis. The line integral for finite‐length cylinders is given by Refs. [14, 15]
where
where
Beam pattern of transducer in linear and decibel scales were shown in Figure 2. The main lobe has a higher power of about 40 dB from the first side lobes. This pattern is determined by acoustic frequency, size, shape, and phase of transducer. Maximum sensitivity of transducer along the main acoustic axis is 0 dB. Amplitude of side lobes is ranged from −80.0 to −40.0 dB. The maximum detection range of the echo sounder has been computed using signal to noise ratio, TS, frequency, electro acoustic efficiency, and acoustic power [16]. Figure 3 shows that the detection range of echo sounder is about 220 m in depth and detectable breadth is 8 m from the acoustic axis. The noise resulted by research vessel is the largest because of the propeller noise. Signal to noise ratio (SNR) is the ratio of the echo power of the fish to the received noise power. Theoretical sphere target strength was numerically simulated for a 38.1‐mm‐diameter sphere of tungsten carbide. Theoretical and measurement of sphere ball target strength were shown in Figure 4. This figure explains that the measurement was suitable with theoretical value. Transmission loss measurement was shown in Figure 5. Increasing sound propagation range was followed by increasing transmission loss. The acoustic intensity/energy loss is due to spherical or geometrical spreading and attenuation. Acoustic ray propagation and its sound intensity level in several transducer depths were shown in Figures 6 and 7. The refraction of sound was caused by temperature gradients in the water, reflection from sea surface, sea bottom, and position of the target. Small changes in the temperature have significant influence on sound propagation. Acoustic detection of fish and seabed in the raw signal echogram and after filtering were shown in Figures 8 and 9, respectively. Target strength of fish ranged between −53.0 and −32.9 dB was shown in Figures 10 and 11, and volume backscattering signal was shown in Figure 12.
Beam pattern of transducer in linear (left) and decibel scale (right).
Detection range and detectable breadth of transducer.
Measurement (*) and theoretical target strength (−).
Sound transmission loss.
Acoustic ray propagation.
Sound intensity level for transmitter depth of 0.5, 1.5, 2, 3.0, 4.0, and 5.0 m.
Raw data echogram.
Echogram filtered.
Target strength histogram.
Target strength versus depth.
Volume backscattering (SV) signal.
Measurement of target strength (TS) in laboratory was conducted using 10 dead fish. The TS value for fish was determined by the tilt angle and acoustic frequency. The values of TSmax and TSavg as functions of linear value of fish length are plotted in Figure 13. The values of TSmax and the TSavg at 50 kHz were higher than those at 200 kHz. Positive correlation was found between TS values and fish length at both 50 and 200 kHz. The best fit regression lines of TSave are TSave = 19.81 log (FL) − 98.2,
Relationship between TS and fish length (FL).
Threshold application for SV and SA modes.
Single echo detector for TS detection.
Typical examples of TS as a function of incidence angle at frequencies 50 and 200 kHz are shown in Figure 16. The variations of TS value with incidence angle are displayed at 0° (main lobe) at both frequencies. The side lobes are displayed at a small discrepancy at two frequencies. The peaks were sharp, suggesting that slight changes in the incidence angles of fish have a major effect on the TS value.
DWBA numerical model (‐) and measurement (●) of TS values as a function of tilt angle at 50 (upper) and 200 kHz (lower).
Target strength of fish is important for fish stock estimation. The measurement of fish density uses TS as a scaling factor and instrument parameters. In fact, individual TS depends upon physical and biological factors such as tilt angle, length, acoustic frequency, physiology, and morphology [17].
Acoustic backscattering using the DWBA model requires accurate values of sound speed and density of fish. This is caused by a weakly scattering organism whose material properties vary from surrounding water. Acoustic scattering predictions with the tilt angle are measured for fish of angle increment from 0 to 360o. The comparison between DWBA model and measurement was agreed upon on the main lobe, but in the side lobe, there is some discrepancy. It was found the acoustic backscattering is strongly dependent on incidence angle and frequency. This result is suitable for the previous research using DWBA for zooplankton and squid applications [18, 19]. Target strength for several fish were shown to increase significantly from 0° to 90° and from 180° to 270° for all frequencies. In the future, the phase parameter of DWBA should be included in TS computation. This is the first research to measure the incidence angle of Indonesian fish in an experimental water tank and ocean field to apply a theoretical target scattering model using DWBA. We confirm that application of single‐beam echo sounder is possible for accurate TS measurement.
The results indicated that TS of fish was determined by incidence angle of acoustic wave, fish length, and frequency of sonar instrument. TS will increase with the length of the animal. TS information are useful for quantifying fish stock in the field using quantitative echo sounder. The validation of DWBA model to measure target strength is confirmed with the laboratory experiment using single‐beam echo sounder.
We acknowledge the Ministry of Research, Technology, and Higher Education Indonesia for financial support of this research.
Poor soil fertility is the major biophysical factor affecting crop production in the world [1]. It is a major threat to food security considering the ever-increasing growth rate in human population which is projected to reach about 10 billion by 2050 [2]. In times of old, forests and marginal lands were converted to farmlands to meet the food demands of the growing population. This practice caused the extinction and endangerment of many plant and animal species; hence it is frowned upon by many stakeholders. As such, today, it would not be prudent to encroach land reserves and other marginal lands for agricultural purposes. It is therefore imperative that we improve soil fertility and health of the available land, to increase food production and to ensure the world’s food security under the current and projected climate change.
Previously, the use of mineral fertilizer was thought of as the most appropriate remedy to soil fertility problems due to its rapid nutrient release [3]. However, mineral fertilizer lacks the ability to improve the soil’s physical properties causing fertility improvement by fertilizers alone to be unsustainable. Over-reliance on mineral fertilizer without due diligence to the organics may lead to increased soil erosion, surface and groundwater contamination, increased greenhouse gas emission and reduced biodiversity [4]. In addition, mineral fertilizers are expensive, and many farmers may not have the purchasing power to acquire it [5]. As a result, the attention of various stakeholders has been drawn to use of organic resources [6]. The application of organic fertilizers presents a more sustainable method of food production. There is unending literature reporting the efficiency and effectiveness of organic nutrient sources in maintaining soil quality (physical, biological and chemical properties), improving crop yields and sustaining productivity [6, 7, 8]. The benefits of applying organic fertilizers to the soil are elaborated in this chapter.
Organic nutrient sources are specifically derived from plant and animal origins [9]. They include plant residues, animal wastes and biofertilizers. In this era where climate change and the COVID-19 pandemic has impacted agricultural production and the financial capabilities of all workforces including farmers, farmers could use organic fertilizers available to them for soil fertility purposes because they are cheaper and more environmentally friendly when they are locally available [10].
Organic fertilizers include poultry manure, cattle manure, green manure (often legumes), field crop residues, composts, bone meal, household waste, blood meal, slurry, cocoa pod husks, palm kernel cake, among others. Biofertilizers are products containing single micro-organisms or combinations of them which when applied help fix atmospheric N, solubilize nutrients, mobilize nutrients, or secrete growth promoting substances to aid crop growth. These products do not supply nutrients themselves but enhance the activities of soil microbes to make more nutrients available to crops. They are categorized into N-fixing biofertilizers, phosphorus solubilizing biofertilizers, composting accelerators and plant growth promoting rhizobacteria [9]. Most of the plant and animal residues are often by-products and nuisance to the environment. Using them as nutrient sources would help reduce waste and greenhouse gas emission.
Organic fertilizers supply all essential crop nutrients (N, P, K, S, Ca, Mg, B, Cl, Cu, Fe, Mn, Mo, Ni and Zn) in balanced forms, including micronutrients. This is often not the case for any one inorganic fertilizer. Since all these nutrients make up the biomass of organic residues, they are released during the decomposition process into the soil. The downside to applying organic fertilizers alone is that they contain very minimal amounts of these nutrients and as such must be applied in bulky quantities to meet crop nutrient demands [11]. Also, the fact that only a fraction of the nutrients in organic fertilizers can be released per season must be factored in when applying organic fertilizers. On the average, as a rule of thumb, only about 50% of nutrients in organic fertilizers are mineralized in the first season of application [12]. Usually, the focal nutrient used to calculate the amount of organic fertilizer to apply is its nitrogen (N) concentration. For example, 30% decomposed cattle manure (DCM) contains about 2% N [13]. Assuming a farmer grows maize, which requires about 90 kg/ha N, that means:
Therefore, to supply 90 kg N = (90 × 100)/2 = 4500 kg DCM.
Since the applied DCM will only supply half the amount of N required in a season, the amount must be doubled to make
To supply same amount of N through mineral fertilizer, a farmer would only need about 200 kg Urea, however, in organic applications, other nutrients are concurrently being applied. Since a large amount of DCM would supply the required N and other nutrients, it must be available to the farmer. Hence advocates of organic fertilizers must emphasize on ways to raise such large amounts of materials for application locally if sole organic production is desired.
Aside the balanced nutrient supply, organic fertilizers add organic matter to the soil if a long-term application is practiced. Organic matter improves the nutrient holding capacity of the soil because it contains organic acids that increase the H+ ions and surface charge of the soil, causing the soil’s cation exchange capacity to increase [15]. Thus, the soil’s ability to hold more cations (nutrients) at exchange sites is increased and hence the nutrient holding capacity of the soil is also improved. Organic matter also improves the buffer capacity of the soil and increases the soil’s ability to resist a change in pH, which in turn affects nutrient loss or gain to the soil [16]. Organic fertilizers increase microbial activity in the soil, causing increased nutrient mineralization rates for the benefit of crops. They stimulate the activities of aerobic and anaerobic bacteria [17] and arbuscular mycorrhizae fungi that form networks of root extension for extensive nutrient availability to crops. Upon the lysis and decomposition of soil microbes, nutrients retained in their biomass are made available in the soil and to crops.
Soil structure, texture, bulk density, and organic matter content are the controls on soil water holding capacity; therefore, any management practice that improves these soil properties, in turn, improves water holding capacity (WHC) of the soil. Soil moisture content is largely dependent on the specific surface area of the soil and the thickness of films of water surrounding the pores [18]. The addition of organic matter through organic fertilizer application improves soil aggregation and increases the surface area of the soil, presenting the soil with more room for soil particles to be surrounded by films of water. As a result, the soil can hold more water against the pull of gravity which drains water from the soil.
While soil organic matter binds soil particles, it also stimulates the activity of soil microfauna whose movement create micro and macropores in the soil, creating extra room for water infiltration [19]. Thus, soil water holding capacity can be improved by the addition of organic fertilizers. In the wake of climate change, where unexpected droughts may be imminent, improving the water holding capacities of the soil with the application of organic fertilizer is the way to go. Also, the physical presence of organic materials on the soil serves as mulch that reduces evaporation and retains moisture in the soil. It also reduces the speed of runoff water and allows rain or irrigation water to infiltrate the soil at favorable speed, thereby reducing erosion, soil and nutrient loss [19].
The soil binding properties of organic matter and improvement in soil aggregation helps to improve soil structure [20]. The addition of organic matter also improves soil texture and aeration. Soils with improved structure and texture allow easy air, water, and root movement to support healthy crop growth.
Many research works have observed extra crop yields with organic fertilizer application compared to when its nutrient equivalents are applied through mineral fertilizer [21, 22, 23]. Various mechanisms have been proposed to explain this added crop yields from organic fertilizer application. Some of which include
Under the improved nutrient synchrony mechanism proposed by Vanlauwe et al. [23], when organic fertilizers are applied, they supply microbes with energy from the carbon they contain, to drive decomposition processes. This leads to temporal immobilization of soil N [24, 25] to build their body tissues. The immobilized N is made available at a later stage of plant growth when the microbes have decomposed the organic material to make nutrients available and/or some microbes have lysed and released their nutrients to the plant when it needs nutrients most. In effect, the peak of nutrient supply coincides with highest crop nutrient demand point when crops have matured, so that the nutrients are efficiently utilized, and little is lost to the environment. Kapkiyai et al. [26] reported that a combination of organic and mineral nutrient sources has been shown to result into synergy and improved synchronization of nutrient release and nutrient demand and uptake by plants leading to higher yields.
The general fertility improvement mechanism [23] is based on the theory that organic matter, aside its addition of nutrients to the soil, improves other physical properties of the soil that helps to perpetuate the nutrient addition effect in real time. Some of these benefits include the improvement of soil structure, water and nutrient holding capacities as discussed above. It also adds micronutrients which is usually not the focus of inorganic fertilizer application.
Priming effect is another mechanism proposed by Kuzyakov et al. [27], in which organic fertilizers affect additional crop yields. Priming refers to strong short - term changes in the turnover of soil nutrients caused by the addition of easily decomposable organic materials. Changes may be positive or negative depending on whether nutrients are rapidly mineralized or immobilized. Under this mechanism, a sum of nutrients available in the soil after harvest and nutrients in crops from the field are higher than a sum of the initial soil nutrients and nutrients in the organic materials. Thus, the additional unaccountable nutrient is the result of organic fertilizer precursing a more rapid mineralization rate and dissolution of previously unavailable/fixed nutrients into solution. This is made effective by the improvement in microbial population, diversity and activity affected by the organic material addition.
These mechanisms, though proposed by different authors, all point to the fact that organic fertilizers are beneficial to the soil and consequently, crops.
Despite the benefits of organic fertilizers to the soil, organic resources application is limited by the large amounts required to meet nutrient demand [28]. Hence locally available organic resources must be used to overcome this limitation. In areas where animal production is common, feedlot manure is the most available organic fertilizer resource. Crop residue retention and cash crop- cover crops rotation is an option to increase on-farm residue production. One other option that has proven to be effective is an integrated nutrient management approach where organic and inorganic fertilizers are applied in right quantities [29]. This approach helps to harness the mechanisms underlying the effects of organic fertilizer application on crops, resulting in synergy in terms of crop yields.
In times when climate change is imminent and its effect on agriculture tends to endanger food security, it is paramount that farmers and other stakeholders use strategies and resources that adapt farming systems to the changing climate. Climate change is mainly driven by natural and anthropogenic activities that pump greenhouse gases (examples CO2, CH4, N2O) into the atmosphere [30, 31]. It may lead to extreme droughts or extreme floods, which may have devastating impacts on food production and agriculture. In this light, organic fertilizers are a great resort due to their replenishing effects on soil physical and chemical properties. Aside the benefits of organic fertilizers discussed above which may adapt the soil to drought conditions, soils should be well drained and loose in flood prone areas in wait of climate change. In compact and poorly drained soils, the addition of organic fertilizers would improve soil particle aggregation and structure to give the soil more room to infiltrate water without settling on the top for too long to cause floods. The addition of organic matter reduces the inventory of greenhouse gasses contributed to climate change by agriculture. This is achieved by the sequestration of carbon into the soil from organic fertilizers applied. The carbon would have been lost to the atmosphere as CO2 or CH4 if it had not been incorporated into the soil [32]. As a result, the application of organic fertilizers to the soil helps to reduce greenhouse gas emission leading to global warming and a consequent climate change and helps adapt the soil to the current and future changes in the climate.
Since organic materials are diverse in type and nutrient composition, it is difficult to give a general recommendation of an organic material. The lignin, polyphenol and nitrogen contents of organic material are important controls on its nutrient mineralization, once applied. It is important to evaluate the carbon to nitrogen (C:N) ratio of an organic material to determine if application of the material will lead to N mineralization or immobilization. A C:N ratio of 25 would enhance decomposition and mineralization by soil microbes while a C:N ratio above that would enhance N immobilization [14]. Hence the lower the C:N ratio, the more rapidly nutrients will be made available to the soil. Organic materials high in lignin (>15%) and polyphenol (>5%) contents usually have high C:N ratios and are resistant to microbial decomposition; hence will decompose slowly. If the N content of the material is 2.5% or more, it would likely decompose and mineralize faster [33].
The effectiveness of an organic material as a fertilizer is also dependent on how it is applied. Surface application of organic fertilizer enhances the loss of N through ammonia volatilization or loss of N and P through runoff and erosion. Judicious methods by which organic materials may be applied to reduce wastage and nutrient losses include band spreading, trailing hose method, burying method, rapid soil incorporation, and the addition of nitrogen inhibitors [34].
Band spreading is the application of the organic material(s) in narrow bands usually a few centimeters away from the crops. This reduces the surface area of the material to the atmosphere so that ammonia volatilization is reduced. To reduce the rate of denitrification as well, band spreading should be done during cool weather with no excessive soil moisture and at right rates. The crop canopies also serve as a physical barrier that further reduces the rate of ammonia volatilization from band spreading applications.
Slurries or liquefied organic fertilizers could be applied in these narrow bands through trailing hoses which hang down from a boom and run along or just above the surface of the soil.
Organic amendments could also be buried at about 5-30 cm depth depending on the crop establishment. Deeper depth burying can be practiced before crops are grown while shallower depth is suited for already established crop fields. This method greatly reduced N loss through ammonia volatilization and the loss of material through erosion.
Manure could be rapidly incorporated into the soil during soil tillage (before planting) or with hand implements to reduce N and P losses in volatilization and runoff.
Under conditions with high denitrification potential, nitrification inhibitors could be added to organic fertilizers to delay the rate at which ammonium is converted to nitrates, which is a suitable substrate that precursors the denitrification process. It is important to apply organic fertilizers at cool times of the day and at the right rates to reduce nutrient losses.
The sole application of organic fertilizers has proved to be a slow means of nutrient supply to the soil. Hence the combined use of organic and inorganic nutrient sources has been proposed [29]. Such applications harness the benefits of synergistic interaction between the organic and inorganic nutrient sources. The main objective of this research was to increase maize yield with the application of organic manure or a combination of it with mineral fertilizer. To arrive at this objective, the yield of maize following varying rates of combined manure and mineral fertilizer applications were estimated at harvest, synergistic benefits of combined applications were quantified and the effect on soil nutrient stocks were analyzed.
A field experiment was conducted at the plantation section of the Kwame Nkrumah University of Science and Technology under rain-fed conditions. Nine treatments (three levels of mineral fertilizer at 0, 50 and 100% of the 90-60-70 kg/ha NPK recommended rate (RR) by three levels of manure at 0, 50, 100% of 5 t/ha RR) were applied on the field in a factorial fashion arranged in Randomized Complete Block Design (RCBD) with three replications. The land was slashed and burned and later plowed and harrowed to a fine tilt. Plot layouts were done with lines and pegs with each plot measuring 3 m by 2 m. There were 2 m alleys between replications and 1 m alleys between plots. Initial soil and manure sampling and analyses were done to characterize them. Randomized manure treatments units were allocated to their designated plots. The Akposoe maize variety developed by the Crops Research Institute of Ghana was planted 2 weeks after manure allocation. Weeding was done manually when necessary. Mineral fertilizer application was done 2 weeks after planting (WAP). The fertilizers were applied as urea, triple superphosphate and murate of potash. The urea was split applied in the first fertilizer application (2 WAP). The other half of the urea was applied 6 WAP. The manure was spread in the plots and raked in to about 5 cm depth. The fertilizer was applied by the band placement method, about 5 cm away from the maize plants. A final soil analysis was done after harvest to determine soil nitrogen (N), phosphorus (P) and potassium (K) levels. Data was subjected to analysis of variance (ANOVA) with the GENSTAT statistical package and significant means were separated with least significant difference at 5%.
Note: Rains were quite erratic at the start of the experiment until an unexpected shortage during the reproductive stage of maize growth. Though unfortunate, this was a good situation to determine if manure applied to the soil would help maintain more soil moisture and consequently impact maize yield.
The lack of rains crippled any effect of the manure alone or its combinations with mineral fertilizer to create differences in the yield of maize. Limited soil moisture has been reported to constraint maize yield [35], because all the processes involved in nutrient movement to roots, uptake by roots and translocation through the transpiration stream use water [36].
After harvest, soil and statistical analysis showed that plots receiving 50 and 100% rates of manure had a significant 20% more total soil N than the control and mineral fertilizer rates. It is possible that due to the rapid nutrient release mechanism of mineral fertilizer, most of its nutrients was released during the early stages of the maize growth, subject to rapid loss from the soil system. The C:N ratio of the manure was 23.08, which is an indication that N was being mineralized [35] into the soil system over a long period, even after the shortage of rains. A combined use of the full rate of manure and full rate of mineral fertilizer also had 20% more total soil N than each individual nutrient source. It is evident that combining organic and inorganic inputs creates a balance between increasing N availability for plant uptake over sole organic application and decreasing N availability for potential system losses compared to fertilizer alone [37].
The rather erratic rains at the beginning of the experiment might have caused soil P and K to leach beyond root zone, hence the lack of differences between the effects of sole manure and mineral fertilizer applications or their combinations at the end of the experiment.
Overall, it was concluded that organic manure had the potential to hold nutrients in the soil longer than inorganic fertilizers. In the advent of climate change, it could be a very useful tool especially in areas was droughts are expected.
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Baguley and Euphemia Leung",authors:[{id:"45751",title:"Prof.",name:"Bruce",middleName:null,surname:"Baguley",slug:"bruce-baguley",fullName:"Bruce Baguley"},{id:"45766",title:"Dr.",name:"Ephemia",middleName:null,surname:"Leung",slug:"ephemia-leung",fullName:"Ephemia Leung"}]},{id:"53532",doi:"10.5772/66989",title:"Nanobiotechnology for Breast Cancer Treatment",slug:"nanobiotechnology-for-breast-cancer-treatment",totalDownloads:2790,totalCrossrefCites:7,totalDimensionsCites:11,abstract:"Despite many technological breakthroughs, even the best breast cancer treatments available today are not 100% effective. Chemotherapy has improved, but many drugs still do not reach the tumor site at effective doses and are often associated with high systemic toxicity and poor pharmacokinetics. Moreover, for many malignancies, diagnosis is obtainable only in metastatic stages of development, reducing the overall effectiveness of treatment. The choice of available treatments depends on tumor characteristics such as biomarkers, tumor size, metastatic disease, ligands, and antigen or endocrine receptor expression. Combined with surgical resection, chemotherapy and radiation remain the first line of treatment for patients with cancer. Even with these treatments, however, cancer continues to have high fatality rates and current therapeutic modalities have yet to significantly improve the often dismal prognosis of this disease. Nanotechnology is a highly focused approach, which may provide more effective and less toxic treatment when compared to chemotherapy. This area of research has emerged as cancer treatment in the form of new drugs and has reached promising results in preclinical and clinical trials proving its value as a potential tumor therapy.",book:{id:"5431",slug:"breast-cancer-from-biology-to-medicine",title:"Breast Cancer",fullTitle:"Breast Cancer - From Biology to Medicine"},signatures:"Márcia Rocha, Natalia Chaves and Sônia Báo",authors:[{id:"147895",title:"Dr.",name:"Sônia Nair",middleName:null,surname:"Báo",slug:"sonia-nair-bao",fullName:"Sônia Nair Báo"},{id:"190527",title:"MSc.",name:"Natalia",middleName:null,surname:"Chaves",slug:"natalia-chaves",fullName:"Natalia Chaves"},{id:"190529",title:"MSc.",name:"Marcia",middleName:null,surname:"Oliveira Da Rocha",slug:"marcia-oliveira-da-rocha",fullName:"Marcia Oliveira Da Rocha"}]}],mostDownloadedChaptersLast30Days:[{id:"53856",title:"Early-Stage Progression of Breast Cancer",slug:"early-stage-progression-of-breast-cancer",totalDownloads:1684,totalCrossrefCites:4,totalDimensionsCites:4,abstract:"Breast cancer can be defined as a group of diseases with heterogeneous origins, molecular profiles and behaviors characterized by uncontrolled proliferation of cells within the mammary tissue. Around one in eight women in the US will develop breast cancer in their lifetime, making it the second most frequently diagnosed cancer behind skin cancer [1]. In 2015, an estimated 231,840 cases of invasive carcinoma were diagnosed, and over 40,000 deaths were caused by breast cancer which accounts for almost 7% of all cancer mortality each year. In 2015, 60,290 cases of in situ breast cancer were diagnosed, representing over 14% of all new cancer cases among women and men. The steep increase in diagnosis of early‐stage breast cancer over the past 10 years is believed to be a result of more frequent mammography. However, since over half of these in situ lesions will not progress to invasive breast cancer, controversies have arisen about approaches to treatment and prevention of progression of early‐stage in situ breast cancer. Understanding the mechanisms of transition of normal breast to in situ pre‐neoplastic lesions and invasive breast cancer is currently a major focus of breast cancer research with implications for preventive and clinical management of breast cancer. In this review, we give an overview of current knowledge on the molecular and pathological changes that occur during early‐stage progression of breast cancer and describe some of the current models that are used to study this process.",book:{id:"5431",slug:"breast-cancer-from-biology-to-medicine",title:"Breast Cancer",fullTitle:"Breast Cancer - From Biology to Medicine"},signatures:"William Kietzman, Anna T. 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Fentiman",authors:[{id:"119147",title:"Prof.",name:"Ian",middleName:null,surname:"Fentiman",slug:"ian-fentiman",fullName:"Ian Fentiman"}]},{id:"52969",title:"Histopathological Characteristics: Clinical Course of Breast Cancer Subtypes Depending on the ER(+) (−)/PR(+) (−) Receptor Status",slug:"histopathological-characteristics-clinical-course-of-breast-cancer-subtypes-depending-on-the-er-pr-r",totalDownloads:1890,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Breast cancer patients were divided into separate groups, which were the estrogen receptor (ER)+/progesterone receptor (PR)+ HER2−, the ER or PR+ HER2−, the ER+/PR+ HER2+, the ER or PR+ HER2+, the ER−/PR− HER2−, and the ER−/PR− HER2+ groups. Patients with the ER/PR(+)/HER2− subtype breast cancers show better clinical prognosis compared to the hormone-negative, triple-negative (TN), and HER2+ subtypes. TN, HER2+ tumors in postmenopausal women were of higher grade, showing lymph node and lymphovascular invasion with poor prognosis in all case series. However, the ER+/PR−/HER2+ subgroup had the lowest survival rates in 2- and 5-year follow-ups. Comparison between the ER+PR+HER2+ and ER+PR−HER2− subgroups showed that HER2− status is an indicator of improved prognosis in long-term follow-up. Single hormone receptor (HR)(+) status, particularly HER2(−) cases, was in between the favorable and poor survival subgroups. The ER−, PR−, and HER2+ properties were found to be risk factors for frequent recurrences. In this chapter, breast cancer subtypes are compared with each other. Results from different studies highlight the importance of ER/PR/HER2 receptor variations in the choice of treatment and prognosis of breast cancer.",book:{id:"5431",slug:"breast-cancer-from-biology-to-medicine",title:"Breast Cancer",fullTitle:"Breast Cancer - From Biology to Medicine"},signatures:"Nilufer Bulut",authors:[{id:"189255",title:"Associate Prof.",name:"Nilufer",middleName:null,surname:"Bulut",slug:"nilufer-bulut",fullName:"Nilufer Bulut"}]},{id:"42313",title:"HER2-Driven Carcinogenesis: New Mouse Models for Novel Immunotherapies",slug:"her2-driven-carcinogenesis-new-mouse-models-for-novel-immunotherapies",totalDownloads:4490,totalCrossrefCites:2,totalDimensionsCites:2,abstract:null,book:{id:"2883",slug:"oncogene-and-cancer-from-bench-to-clinic",title:"Oncogene and Cancer",fullTitle:"Oncogene and Cancer - From Bench to Clinic"},signatures:"Cristina Marchini, Lucia Pietrella, Cristina Kalogris, Chiara Garulli, Federico Gabrielli, Elena Quaglino, Manuela Iezzi, Serenella M. 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