\r\n\r\n \r\n\r\nThis work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 634476 for project with acronym TREASURE. The content of this book reflects only the authors\' view and the European Union Agency is not responsible for any use that may be made of the information it contains.\r\n',isbn:"978-1-78985-408-4",printIsbn:"978-1-78985-407-7",pdfIsbn:"978-1-83962-011-9",doi:"10.5772/intechopen.83749",price:139,priceEur:155,priceUsd:179,slug:"european-local-pig-breeds-diversity-and-performance-a-study-of-project-treasure",numberOfPages:318,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"182fe65256f9a0bbc25b0b7576412b0e",bookSignature:"Marjeta Candek-Potokar and Rosa M. Nieto Linan",publishedDate:"February 6th 2019",coverURL:"https://cdn.intechopen.com/books/images_new/9356.jpg",numberOfDownloads:22793,numberOfWosCitations:37,numberOfCrossrefCitations:35,numberOfCrossrefCitationsByBook:14,numberOfDimensionsCitations:62,numberOfDimensionsCitationsByBook:19,hasAltmetrics:1,numberOfTotalCitations:134,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"December 21st 2018",dateEndSecondStepPublish:"January 11th 2019",dateEndThirdStepPublish:"March 12th 2019",dateEndFourthStepPublish:"May 31st 2019",dateEndFifthStepPublish:"July 30th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:'
This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 634476 for project with acronym TREASURE. The content of this book reflects only the authors\' view and the European Union Agency is not responsible for any use that may be made of the information it contains.
',editors:[{id:"23161",title:"Dr.",name:"Marjeta",middleName:null,surname:"Čandek-Potokar",slug:"marjeta-candek-potokar",fullName:"Marjeta Čandek-Potokar",profilePictureURL:"https://mts.intechopen.com/storage/users/23161/images/8255_n.jpg",biography:"Marjeta Čandek Potokar is a researcher at the Agricultural Institute of Slovenia. She graduated in Animal Science and has a PhD in Food Science. Her main research area is meat science. Current research topics comprise: (1) the local Krškopolje pig breed, (2) castration issues (boar taint, immunocastration, nutrition, product quality), (3) dry cured products, (4) carcass classification methods, and (5) use of NIRS for meat quality assessment. She has led seven national projects and participated in many EU projects (EUPIGCLASS, YOUNG-TRAIN, PIGCAS, TRUEFOOD, COST FAIM, COST IPEMA, ERA-NET SUSI); presently she coordinates H2020 project TREASURE. She is habilitted at the Faculty of Agriculture and Life Sciences of the University of Maribor as a lecturer of technology of animal products. She has authored over 60 SCI papers, numerous professional articles, conference contributions, and book chapters.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Agricultural institute of Slovenia",institutionURL:null,country:{name:"Slovenia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"290236",title:"Dr.",name:"Rosa",middleName:"Maria",surname:"Nieto",slug:"rosa-nieto",fullName:"Rosa Nieto",profilePictureURL:"https://mts.intechopen.com/storage/users/290236/images/8256_n.jpg",biography:"Rosa M. Nieto is a researcher at the Spanish National Research Council. She graduated in Biological Sciences and has a PhD in Animal Nutrition. Her research activity is nutrient metabolism of livestock (mainly swine), focusing on protein deposition in muscle. Over the last few years she has concentrated on Iberian pig metabolic characterization, investigating nutritional requirements (particularly amino acids and energy) during different growth phases. Her research interests include the effects of immunocastration on productivity and meat quality, links between amino acid and lipid metabolism, and consequences on meat quality. She has participated in nearly 30 research projects and contracts with international (including H2020 project TREASURE), national, and regional funding, in many of them as a research leader. She has authored over 70 SCI papers and many professional articles and congress contributions.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"297",title:"Animal Science",slug:"animal-science"}],chapters:[{id:"65254",title:"Introductory Chapter: Concept and Ambition of Project TREASURE",doi:"10.5772/intechopen.84246",slug:"introductory-chapter-concept-and-ambition-of-project-treasure",totalDownloads:1074,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:0,abstract:null,signatures:"Marjeta Čandek-Potokar, Luca Fontanesi, Bénédicte Lebret, José M. Gil,\nCristina Ovilo, Rosa Nieto, Ana Fernandez, Carolina Pugliese,\nMaria-Angels Oliver and Riccardo Bozzi",downloadPdfUrl:"/chapter/pdf-download/65254",previewPdfUrl:"/chapter/pdf-preview/65254",authors:[{id:"23161",title:"Dr.",name:"Marjeta",surname:"Čandek-Potokar",slug:"marjeta-candek-potokar",fullName:"Marjeta Čandek-Potokar"}],corrections:null},{id:"65363",title:"Alentejano Pig",doi:"10.5772/intechopen.83757",slug:"alentejano-pig",totalDownloads:1106,totalCrossrefCites:3,totalDimensionsCites:4,hasAltmetrics:0,abstract:"The present chapter presents the history and current status of Alentejano pig breed, a Portuguese autochthonous swine breed. A review of literature regarding reproductive and productive traits was carried out. Reproductive performance includes sow age at first parturition and at culling, litters per sow and per year, piglets born alive per litter, percentage of stillborn per litter, piglets birth weight, mortality rate until weaning, piglet weaned per litter, duration of lactation and farrowing interval. Growth performance includes average daily gain and average daily feed intake during lactation, early, middle and late growing stages and fattening stage. Carcass traits were evaluated using age and weight at slaughter, hot carcass weight, carcass yield, lean meat content, back fat thickness at withers and at the level of the last rib, muscle thickness at the cranial edge of gluteus medius muscle and loin eye area. Meat and fat quality traits of longissimus muscle were evaluated by means of pH at 45 min and 24 hours after slaughter, objective colour (CIE L*, a* and b*), intramuscular fat content and fatty acid composition of intramuscular fat. However, a considerable number of studies on Alentejano pig, data on reproductive performance and some parameters of meat quality are still scarce.",signatures:"Rui Charneca, José Martins, Amadeu Freitas, José Neves, José Nunes, Hugo Paixim, Pedro Bento and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65363",previewPdfUrl:"/chapter/pdf-preview/65363",authors:[{id:"290234",title:"Dr.",name:"Rui",surname:"Charneca",slug:"rui-charneca",fullName:"Rui Charneca"}],corrections:null},{id:"65352",title:"Basque Pig",doi:"10.5772/intechopen.83758",slug:"basque-pig",totalDownloads:1133,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Local pig breeds are adapted to the specific local environment and fed with various locally available feedstuffs. Besides their genetic merit for agro-biodiversity, they represent the basis for sustainable local pork chains. The present chapter aims to present history and current status of the Basque pig breed, its exterior phenotypic characteristics, geographical location, production system and main products. This French autochthonous breed of pigs, which almost disappeared few decades ago, seems now consolidated, thanks to a chain organization and recognised high-quality products (Protected Designation of Origin). Reproductive performance data reviewed from the literature and estimated from the LIGERAL database (herdbook) are presented. Available data on production traits including growth (early, middle, late and overall growth), feed intake, body composition and carcass traits are also summarized. Meat quality traits (pH, colour, intramuscular fat content and fatty acid composition) and back fat tissue characteristics (fatty acid profile) are also described. Studies on the Basque pig breed are scarce. Different production systems, feeding regimes and feed composition used among studies can explain differences observed between studies, especially for productive traits. However, the current review gives insight into the reproduction, production and carcass and meat quality traits of this local pig breed.",signatures:"Marie-José Mercat, Bénédicte Lebret, Herveline Lenoir\nand Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65352",previewPdfUrl:"/chapter/pdf-preview/65352",authors:[{id:"290240",title:"Dr.",name:"Marie-Jose",surname:"Mercat",slug:"marie-jose-mercat",fullName:"Marie-Jose Mercat"}],corrections:null},{id:"65338",title:"Bísaro Pig",doi:"10.5772/intechopen.83759",slug:"b-saro-pig",totalDownloads:1121,totalCrossrefCites:3,totalDimensionsCites:3,hasAltmetrics:1,abstract:"Local pig breeds are adapted to the specific local environment and fed with various locally available feedstuffs. So besides their genetic merit for agro-biodiversity, they represent the foundations of sustainable local pork chains. Thus, the aim of the current chapter is to present the history and current status of the Bísara breed (Bísaro pig), its exterior phenotypic characteristics, geographical location, production system and main products from this Portuguese autochthonous breed of pigs. Moreover, a collection and review of available literature data, set until August 2017, on reproductive and productive traits (growth, carcass, meat and fat quality) of Bísaro pig breed were carried out. Reproductive performance has been estimated by means of sow’s age at the first parturition, annual litters per sow, piglets alive per litter, piglet live birth and weaning weight, percentage of stillborn per litter, mortality to weaning, lactation length and farrowing interval. Growth performance has been estimated through the average daily gain and feed intake in both the growing stage and the early, middle, late and overall fattening stage. Carcass traits have been evaluated by means of age and weight at slaughter, hot carcass weight, carcass yield, lean meat content, backfat thickness at withers, last rib, above the muscle gluteus medius and the loin eye area. Meat and fat quality traits of longissimus muscle have been evaluated by means of pH at 45 minutes and 24 h after slaughter, objective colour (CIE L*), intramuscular fat content and fatty acid composition of intramuscular fat. Although a considerable number of studies on Bísaro pig were included in the current review, data on meat and fat quality are scarce.",signatures:"João Santos Silva, José Pedro Araújo, Joaquim Orlando Cerqueira,\nPreciosa Pires, Carla Alves and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65338",previewPdfUrl:"/chapter/pdf-preview/65338",authors:[{id:"283731",title:"Ph.D.",name:"José Pedro",surname:"Araújo",slug:"jose-pedro-araujo",fullName:"José Pedro Araújo"},{id:"290241",title:"Dr.",name:"Joao",surname:"Santos Silva",slug:"joao-santos-silva",fullName:"Joao Santos Silva"}],corrections:null},{id:"65269",title:"Apulo-Calabrese Pig",doi:"10.5772/intechopen.83760",slug:"apulo-calabrese-pig",totalDownloads:973,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The aim of the present chapter is to present history and current status of Apulo-Calabrese pig breed, one of the local pig breeds investigated in the project TREASURE. Apulo-Calabrese breed is one of the Italian autochthonous pig breeds. Its origin dates back to the Roman times, but it suffered a drastic decline during the past century and the recovery started in the 1990s. A herd book for this breed was established in 2001, but its performances and products are practically untapped. There are 45 registered farms with around 500 breeding sows and 100 boars. Apulo-Calabrese pig is characterised by black coat colour. On average sows of Apulo-Calabrese pig breed have 1.7 litters per year with 6.9 piglets. Regarding growth performances, the potential of Apulo-Calabrese pigs in ad libitum conditions of feeding is high (≈762 g/day in middle fattening stage) although information on feed intake and feed nutritional value was scarce, which limits the evaluation of growth potential. Data on body composition, carcass traits and meat and fat quality are scarce. The present review gives a first insight into this local pig breed.",signatures:"Riccardo Bozzi, Maurizio Gallo, Claudia Geraci, Luca Fontanesi\nand Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65269",previewPdfUrl:"/chapter/pdf-preview/65269",authors:[{id:"290243",title:"Dr.",name:"Riccardo",surname:"Bozzi",slug:"riccardo-bozzi",fullName:"Riccardo Bozzi"}],corrections:null},{id:"65310",title:"Cinta Senese Pig",doi:"10.5772/intechopen.83762",slug:"cinta-senese-pig",totalDownloads:942,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Cinta Senese is an Italian autochthonous pig breed, one of the local pig breeds investigated in the project TREASURE. The present chapter aims to present history and status of Cinta Senese pig breed, its phenotypic characteristics, geographical location, production system and the quality of its main products. Reproductive performance was estimated by several data: sow age at first parturition, litters/sow/year, piglets alive/litter, weaning weight, stillborn/litter, death rate percentage at weaning, duration of lactation, length of farrowing and sow age at culling. Growth performance was estimated by means of average daily gain in lactation and from birth to slaughter, growing at early, middle, late and overall fattening stage and average daily feed intake in late and overall fattening stage. Carcass traits were evaluated by means of age and weight at slaughtering, hot carcass weight, carcass yield, loin eye area and back fat thickness at the first thoracic vertebra, last rib and above gluteus medius muscle. Meat quality traits of the longissimus muscle were evaluated by means of the following: pH at 45 minutes and 24 hours after slaughtering, instrumental measurements of colour (CIE L*, a*, b*) and intramuscular fat content. Fatty acid composition was evaluated in back fat tissue.",signatures:"Carolina Pugliese, Riccardo Bozzi, Maurizio Gallo,\nClaudia Geraci, Luca Fontanesi and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65310",previewPdfUrl:"/chapter/pdf-preview/65310",authors:[{id:"290244",title:"Dr.",name:"Carolina",surname:"Pugliese",slug:"carolina-pugliese",fullName:"Carolina Pugliese"}],corrections:null},{id:"65370",title:"Black Slavonian (Crna slavonska) Pig",doi:"10.5772/intechopen.83763",slug:"black-slavonian-crna-slavonska-pig",totalDownloads:985,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:1,abstract:"Black Slavonian (Crna slavonska) pig was created during the second part of the nineteenth century using planned crossing between four pig breeds. It is an autochthonous pig breed in the Republic of Croatia and one of the local pig breeds investigated in the project TREASURE. The present chapter aims to present history and current status of Black Slavonian pig breed, its exterior phenotypic characteristics, reproductive traits, geographical location, production system and main products from this breed of pigs. Also, a collection and review of available literature data, available until August 2017, on productive traits of Black Slavonian pig breed were carried out. Growth performance was estimated utilising average daily gain and average daily feed intake in the overall fattening stage as this was the information mostly provided in considered studies. Carcass traits were evaluated by means of age and weight at slaughter, hot carcass weight, carcass yield, muscularity and back fat thickness. Meat quality traits of the longissimus muscle evaluated were objective colour and intramuscular fat content. Although a considerable number of studies on Black Slavonian pig were included in the current review, data on growth performance and some parameters of carcass, meat and fat quality are scarce.",signatures:"Vladimir Margeta, Kristina Gvozdanović, Goran Kušec, Ivona Djurkin Kušec and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65370",previewPdfUrl:"/chapter/pdf-preview/65370",authors:[{id:"290245",title:"Dr.",name:"Vladimir",surname:"Margeta",slug:"vladimir-margeta",fullName:"Vladimir Margeta"},{id:"292865",title:"Dr.",name:"Goran",surname:"Kušec",slug:"goran-kusec",fullName:"Goran Kušec"}],corrections:null},{id:"65335",title:"Gascon Pig",doi:"10.5772/intechopen.83764",slug:"gascon-pig",totalDownloads:1079,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The present chapter aims to present history and current status of Gascon pig breed, one of the local pig breeds investigated in the project TREASURE. This French autochthonous breed of pigs, which almost disappeared, now enjoys a new boom. The quality of its product is recognized by the consumers and by official quality labels (Protected Designation of Origin). Exterior phenotypic characteristics of the breed, geographical location, production system and main products are described. Reproductive performance data available in the literature and estimated from the LIGERAL database (herdbook) are presented. Literature data on production traits are also summarized for growth (early, middle, late and overall growth), feed intake, body composition and carcass traits. Meat quality traits (pH, colour, intramuscular fat content and composition) and fat tissue characteristics (fatty acid profile) are also described. Studies on Gascon pig breed are scarce and variability between studies, especially regarding productive traits, can be explained by differences in production systems, feeding regimes and feed composition according to studies. Nevertheless, the current review gives updated insights into the reproduction, production and quality traits of this local pig breed.",signatures:"Marie-José Mercat, Bénédicte Lebret, Herveline Lenoir\nand Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65335",previewPdfUrl:"/chapter/pdf-preview/65335",authors:[{id:"290240",title:"Dr.",name:"Marie-Jose",surname:"Mercat",slug:"marie-jose-mercat",fullName:"Marie-Jose Mercat"},{id:"293176",title:"Dr.",name:"Benedicte",surname:"Lebret",slug:"benedicte-lebret",fullName:"Benedicte Lebret"}],corrections:null},{id:"65300",title:"Ibérico (Iberian) Pig",doi:"10.5772/intechopen.83765",slug:"ib-rico-iberian-pig",totalDownloads:1340,totalCrossrefCites:9,totalDimensionsCites:15,hasAltmetrics:1,abstract:"The main characteristics of the Iberian breed, an autochthonous pig breed of the Iberian Peninsula, are presented in this chapter along with the results of a literature review on productive traits. Reproductive performance was estimated by sow age at first parturition, litters per sow and year, piglets alive per litter, piglet weight at birth and at weaning, percentage of stillborn per litter, mortality at weaning, lactation length and farrowing interval. For growth performance, average daily gain and daily feed intake during lactation and in different growing phases are provided. Carcass traits were evaluated by age and weight at slaughter, hot carcass weight, carcass yield, backfat thickness measurements, muscle thickness and loin eye area. Meat quality traits of longissimus muscle (pH, objective colour measurements and intramuscular fat) were also assessed. The main part of the studies considered simulated practical production conditions in Iberian pig rearing although others evaluated a defined growing period, sometimes quite far from the usual commercial slaughter weight of this breed. Therefore, some figures should be interpreted with caution. Although a considerable number of studies on Iberian pig were included in the current review, scientific papers on reproductive performance and some meat quality parameters are still rather scarce.",signatures:"Rosa Nieto, Juan García-Casco, Luis Lara, Patricia Palma-Granados,\nMercedes Izquierdo, Francisco Hernandez, Elena Dieguez,\nJuan Luis Duarte and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65300",previewPdfUrl:"/chapter/pdf-preview/65300",authors:[{id:"290236",title:"Dr.",name:"Rosa",surname:"Nieto",slug:"rosa-nieto",fullName:"Rosa Nieto"},{id:"292183",title:"Dr.",name:"Mercedes",surname:"Izquierdo",slug:"mercedes-izquierdo",fullName:"Mercedes Izquierdo"},{id:"292271",title:"Dr.",name:"Juan",surname:"García-Casco",slug:"juan-garcia-casco",fullName:"Juan García-Casco"},{id:"292278",title:"Dr.",name:"Elena",surname:"Dieguez",slug:"elena-dieguez",fullName:"Elena Dieguez"}],corrections:null},{id:"65260",title:"Krškopoljski prašič (Krškopolje Pig)",doi:"10.5772/intechopen.83767",slug:"kr-kopoljski-pra-i-kr-kopolje-pig-",totalDownloads:1097,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"This chapter presents the history and the current state-of-the-art in the only Slovenian autochthonous pig breed - Krškopolje pig. A review of literature regarding productive traits was carried out. The reproductive performance includes sow age at first parturition and at culling, litters per sow per year, number of live born and percentage of stillborn piglets per litter, piglet birth and weaning weight, mortality at weaning, duration of lactation and length of farrowing interval. Growth performance was evaluated as average daily gain in lactation, post-weaning, and early, mid, or late fattening. Daily feed intake in different stages was also assessed. Review also addresses age and weight at slaughter, and carcass traits: hot carcass weight, carcass yield, lean meat content, backfat and muscle thickness, and loin eye area. Meat quality traits considered were Longissimus muscle pH, objective colour parameters and intra muscular fat content. Additionally, fatty acid composition of intramuscular fat and backfat tissue was considered. Although studies on Krškopolje pig are scarce and the results on productive traits should be interpreted with precaution, due to different production systems and feeding strategies used in considered studies, the current review gives the first overview on this local pig breed in its current phenotype.",signatures:"Nina Batorek Lukač, Urška Tomažin, Martin Škrlep, Andrej Kastelic, Klavdija Poklukar and Marjeta Čandek-Potokar",downloadPdfUrl:"/chapter/pdf-download/65260",previewPdfUrl:"/chapter/pdf-preview/65260",authors:[{id:"23161",title:"Dr.",name:"Marjeta",surname:"Čandek-Potokar",slug:"marjeta-candek-potokar",fullName:"Marjeta Čandek-Potokar"}],corrections:null},{id:"65316",title:"Lietuvos Vietinė (Lithuanian Indigenous Wattle) Pig",doi:"10.5772/intechopen.83768",slug:"lietuvos-vietin-lithuanian-indigenous-wattle-pig",totalDownloads:922,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Lietuvos vietinė pigs were developed in Lithuanian ethnic lands following natural selection and introduction of some imported pigs. Earlier, no purposeful selection was carried out for this old Lithuanian pig breed. Lietuvos vietinė pigs as other local pig breeds are adapted to the specific local environment and could be fed with various locally available feedstuffs. So besides their genetic merit for agro-biodiversity, they represent the basis for sustainable local pork chains. The present chapter aims to present history and current status of Lietuvos vietinė pig breed, its exterior phenotypic characteristics, geographical location, production system and main products from this Lithuanian autochthonous breed of pigs, one of the local pig breeds investigated in the project TREASURE. Moreover, a collection and review of available literature data, available until August 2017, on reproductive and productive traits of Lietuvos vietinė pig breed were carried out. Reproductive and growth performance was estimated in different stages. Lean meat content was measured by ultrasonic equipment Piglog on the side of live pigs at the position of 12 ribs. Measurements of backfat thickness were taken with a ruler on the left side of carcasses at the dorsal line of the mid-back at the last rib and loin area at the 1/2 lumbar vertebra by digital camera EX-Z110 and afterwards were planimetrically measured by means of the “SCAN-STAR K” planimetrical system. Meat quality traits of the longissimus muscle were evaluated by means of pH at 45 min and 24 hours after slaughter.",signatures:"Violeta Razmaitė, Rūta Šveistienė, Virginija Jatkauskienė,\nRemigijus Juška, Raimondas Leikus and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65316",previewPdfUrl:"/chapter/pdf-preview/65316",authors:[{id:"290248",title:"Dr.",name:"Violeta",surname:"Razmaite",slug:"violeta-razmaite",fullName:"Violeta Razmaite"}],corrections:null},{id:"65280",title:"Lietuvos Baltosios Senojo Tipo (Lithuanian White) Pig",doi:"10.5772/intechopen.83771",slug:"lietuvos-baltosios-senojo-tipo-lithuanian-white-pig",totalDownloads:929,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Lietuvos Baltosios senojo tipo pigs are remaining purebred pigs of local Lithuanian pig breed (Lietuvos Baltosios) adapted to the specific local environment and locally available feedstuffs. Although previously Lietuvos Baltosios was the main dam pig breed in Lithuania, regarding scientific substantiation, their performances and products are, as in the case of Lietuvos Baltosios remains (senojo tipo-old type) pigs, practically untapped. Thus, the present chapter aims to present history and current status of Lietuvos Baltosios senojo tipo pig breed, its exterior phenotypic characteristics, geographical location, production system and main products from this Lithuanian breed of pigs, one of the local pig breeds investigated in the project TREASURE. Moreover, a collection and review of available literature data, available until August 2017, on reproductive and productive traits of Lietuvos Baltosios senojo tipo pig breed were carried out. Reproductive and growth performance, and feed intake in different stages was estimated. Lean meat content was measured by ultrasonic equipment Piglog on the side of live pigs at the position of 12 ribs. Measurements of backfat thickness were taken with a ruler on the left side of carcasses at dorsal line of the mid-back at the last rib and loin area at the 1/2 lumbar vertebra by digital camera EX-Z110 and, afterwards, were planimetrically measured by means of the “SCAN-STAR K” planimetrical system. Meat quality traits of the longissimus muscle were evaluated using pH at 45 min and 24 h after slaughter, objective colour (CIE L*, a*, b*) and intramuscular fat content.",signatures:"Violeta Razmaitė, Rūta Šveistienė, Virginija Jatkauskienė,\nRaimondas Leikus, Remigijus Juška and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65280",previewPdfUrl:"/chapter/pdf-preview/65280",authors:[{id:"290248",title:"Dr.",name:"Violeta",surname:"Razmaite",slug:"violeta-razmaite",fullName:"Violeta Razmaite"}],corrections:null},{id:"65311",title:"Mangalitsa (Swallow-Belly Mangalitsa) Pig",doi:"10.5772/intechopen.83773",slug:"mangalitsa-swallow-belly-mangalitsa-pig",totalDownloads:1151,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:1,abstract:"Autochthonous pig breed is adapted to the specific local environment, fed with various locally available feedstuffs and well adapted to extensive conditions of housing. Their genes represent safety in the production of food in future times, in which the greater importance will be attributed to the resistance and adaptability of the breed. In terms of scientific substantiation, their performances and products are, as in the case of Mangalitsa pig, practically untapped. Thus, the aim of the present chapter is to present history and current status of Mangalitsa pig breed, its exterior phenotypic characteristics, geographical distribution, production management and main products from this Serbian autochthonous breed of pigs, one of the local pig breeds investigated in the project TREASURE. Moreover, a collection and review of available literature data, available until August 2017, on reproductive and productive traits of Mangalitsa pig breed were carried out. Mangalitsa is a late and extremely fatty pig breed with low fertility, long suckling period and a very weak-slow growth. Although studies on Mangalitsa pig are scarce, the current review gives the first insight into this local pig breed.",signatures:"Čedomir Radović, Radomir Savić, Milica Petrović, Marija Gogić,\nMiloš Lukić, Dragan Radojković and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65311",previewPdfUrl:"/chapter/pdf-preview/65311",authors:[{id:"290251",title:"Dr.",name:"Cedomir",surname:"Radovic",slug:"cedomir-radovic",fullName:"Cedomir Radovic"}],corrections:null},{id:"65313",title:"Mora Romagnola Pig",doi:"10.5772/intechopen.83775",slug:"mora-romagnola-pig",totalDownloads:1010,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Mora Romagnola breed, one of the Italian local pig breeds, owes its name to its colour, dark brown tending to black. Currently 31 farms are registered in the herdbook started in 2001 with about 270 breeding females and 67 boars. During the 1990s, only 18 animals were left, all concentrated in one single farm. The breed was investigated within the H2020 project TREASURE, and a collection and review of available literature data on reproductive and productive traits of Mora Romagnola pig breed were carried out. The average age of sows at first parturition was 22 months, whereas age at culling was 58 months. On average, Mora Romagnola pig breed has 8.0 piglets per parity with 1.4 parities per year. Slaughter weight was on average 163 kg with a dressing yield of 80%. Few information is available for meat quality traits. Although studies on Mora Romagnola pig are scarce, the current review gives the first insight into this local pig breed.",signatures:"Riccardo Bozzi, Maurizio Gallo, Claudia Geraci, Luca Fontanesi and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65313",previewPdfUrl:"/chapter/pdf-preview/65313",authors:[{id:"290243",title:"Dr.",name:"Riccardo",surname:"Bozzi",slug:"riccardo-bozzi",fullName:"Riccardo Bozzi"}],corrections:null},{id:"65299",title:"Moravka Pig",doi:"10.5772/intechopen.83777",slug:"moravka-pig",totalDownloads:962,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Indigenous breeds of pigs are adapted to the specific areas in which they were created. In terms of scientific substantiation, their production potential and the products obtained from them are, as in the case of Moravka pig, practically untapped. The main objective of the present chapter is to present history and current status of this breed, breeding area, its performance, production systems and main products from this local breed of pigs. Reproductive traits were estimated by means of sow age at first farrowing, litter size, weaning weight, duration of lactation and length of the farrowing interval. Growth performance was estimated by means of average daily gain and average daily feed intake in the early, middle, late and overall fattening stage. Carcass performance was evaluated by means of slaughter weight, hot carcass weight, carcass yield, lean meat content, loin eye area, the back fat thickness at the level of the last rib and withers and the back fat and muscle thickness above the gluteus medius muscle. Meat quality traits of the longissimus muscle were evaluated by means of pH at 45 min and 24 h after slaughter, objective colour (CIE L*, a* b*), intramuscular fat content and fatty acid content of intramuscular fat.",signatures:"Radomir Savić, Čedomir Radović, Milica Petrović, Marija Gogić,\nDragan Radojković and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65299",previewPdfUrl:"/chapter/pdf-preview/65299",authors:[{id:"290252",title:"Dr.",name:"Radomir",surname:"Savic",slug:"radomir-savic",fullName:"Radomir Savic"}],corrections:null},{id:"65387",title:"Negre Mallorquí (Majorcan Black) Pig",doi:"10.5772/intechopen.84434",slug:"negre-mallorqu-majorcan-black-pig",totalDownloads:976,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Negre Mallorquí pig is a native breed from Mallorca, characterized by its high rusticity and adaptation to the Mediterranean climatic conditions. The present chapter presents the history and current status of this breed, its phenotypic characteristics, the particularities of its production system and main products from this Mediterranean native pig breed. Data come from the scarce literature about Porc Negre Mallorquí breed, adding non-published data obtained during the TREASURE project. Reproductive performance was estimated by means of sow age at first parturition, litters per sow per year, piglets alive per litter, piglets birth and weaning weights, percentage of stillborn per litter, death rate percentage from birth to weaning, duration of lactation and farrowing interval. Growth performance was estimated by means of average daily gain and daily feed intake in several production periods. Carcass traits were evaluated by means of age and weight at slaughter, hot carcass weight, carcass yield and back fat thickness in several points. Meat quality traits were evaluated by means of pH at 45 min and 24 h after slaughter, objective colour, intramuscular fat content and fatty acid composition of intramuscular fat and back fat. The current chapter defines a first review about this local pig breed.",signatures:"Joan Tibau, Neus Torrentó, Raquel Quintanilla Aguado, Joel González,\nMaria Angels Oliver, Marta Gil, Jaume Jaume and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65387",previewPdfUrl:"/chapter/pdf-preview/65387",authors:[{id:"291770",title:"Dr.",name:"Joan",surname:"Tibau",slug:"joan-tibau",fullName:"Joan Tibau"},{id:"292184",title:"Dr.",name:"Joel",surname:"Gonzalez",slug:"joel-gonzalez",fullName:"Joel Gonzalez"}],corrections:null},{id:"65267",title:"Nero Casertano Pig",doi:"10.5772/intechopen.83778",slug:"nero-casertano-pig",totalDownloads:951,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The present chapter aims to present the history, current status and information of Nero Casertano pig breed investigated in the project TREASURE. As for most of the other Italian local pig breed conservation program started in 2001 and in 2015, 20 farms of Nero Casertano pigs with about 545 breeding sows and 20 boars were registered. The average age of sows at the first parturition is 16 months, whereas age at culling is 59 months. On average Nero Casertano pigs have 1.2 litters per year with 7.6 piglets. The farrowing interval (305 days on average) is prolonged compared to modern pig breeds. The fattening phase of Nero Casertano pigs is generally characterised by slower growth, and the animals were slaughtered at around 375 days of age, with an average live weight of 154 kg and a dressing yield of 81%. The breed is characterised by a high level of backfat thickness. The breed is traditionally raised with the semi-extensive system, and the most recognised trait of the Nero Casertano pig is the ‘marbling’ of the meat. This current review provides a comprehensive insight into the information for this local pig breed.",signatures:"Riccardo Bozzi, Maurizio Gallo, Claudia Geraci,\nLuca Fontanesi and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65267",previewPdfUrl:"/chapter/pdf-preview/65267",authors:[{id:"290243",title:"Dr.",name:"Riccardo",surname:"Bozzi",slug:"riccardo-bozzi",fullName:"Riccardo Bozzi"},{id:"292268",title:"Dr.",name:"Maurizio",surname:"Gallo",slug:"maurizio-gallo",fullName:"Maurizio Gallo"},{id:"292269",title:"Dr.",name:"Luca",surname:"Fontanesi",slug:"luca-fontanesi",fullName:"Luca Fontanesi"}],corrections:[{id:"66683",title:"Corrigendum to: Nero Casertano Pig",doi:null,slug:"corrigendum-to-nero-casertano-pig",totalDownloads:null,totalCrossrefCites:null,correctionPdfUrl:null}]},{id:"65298",title:"Nero Siciliano Pig",doi:"10.5772/intechopen.84438",slug:"nero-siciliano-pig",totalDownloads:1008,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Origins of Nero Siciliano pig date to Carthaginian domination and its rearing, after a setback during the Arab period, was rather diffused throughout Sicily. Breed rearing is nowadays limited from the farmed area to the wooded hills of north-eastern Sicily. The latest available status (2015) reported 87 registered farms with about 1100 breeding sows and 124 boars enrolled in the herdbook started in 2001, as well as the conservation programme. Coat colour is mainly black but white face and wattles are accepted. Nero Siciliano pigs have on average 7.6 piglets of 1.4 kg live body weight and the average daily gain during fattening period was on average 346 g/day for the overall fattening stage. Slaughter age of Nero Siciliano breed was on average 390 days, at an average live weight of 95 kg. Average intramuscular fat content was 4.6% and as regards fatty acid composition, average values obtained for SFA, MUFA and PUFA were 37.5, 54.2 and 8.3% in longissimus muscle and 39.0, 49.4 and 11.7% in back fat tissue, respectively. This review gives an exhaustive review of the information available for this local Italian breed.",signatures:"Riccardo Bozzi, Maurizio Gallo, Claudia Geraci, Luca Fontanesi\nand Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65298",previewPdfUrl:"/chapter/pdf-preview/65298",authors:[{id:"290243",title:"Dr.",name:"Riccardo",surname:"Bozzi",slug:"riccardo-bozzi",fullName:"Riccardo Bozzi"}],corrections:null},{id:"65297",title:"Sarda Pig",doi:"10.5772/intechopen.84437",slug:"sarda-pig",totalDownloads:951,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Sarda pig breed (a.k.a. Suino Sardo) is a local breed from Sardinia Island (Italy) with its ancestors dating back to the Nuragic period. It is the most recent breed interested by a conservation programme among the six Italian autochthonous pig breeds investigated by the H2020 project TREASURE and could be considered untapped in terms of information on its performances and products. Thirteen farms were registered at the last census (2015) including sixty-one breeding sows and twenty boars. It is a small size breed with black, grey, tawny or spotted coat colour. On average, age at parturition is 15.7 months, with 1.6 litters per year and 7.8 piglets per parity. Average piglet mortality is rather high in the considered studies (16.1%). The average daily gain for Sarda pig within the considered studies was 423 g/day. On average, daily feed intake in the overall fattening stage was 2.3 kg/day. Sarda pigs were slaughtered at approximately 686 days of age, at an average live weight of 193 kg. Sporadic information is available for meat quality traits. Although studies on Sarda pig are scarce, the current review gives the first insight into this local pig breed.",signatures:"Riccardo Bozzi, Maurizio Gallo, Claudia Geraci, Luca Fontanesi and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65297",previewPdfUrl:"/chapter/pdf-preview/65297",authors:[{id:"290243",title:"Dr.",name:"Riccardo",surname:"Bozzi",slug:"riccardo-bozzi",fullName:"Riccardo Bozzi"}],corrections:null},{id:"65315",title:"Schwäbisch-Hällisches Pig",doi:"10.5772/intechopen.83780",slug:"schw-bisch-h-llisches-pig",totalDownloads:960,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The traditional, local breed Schwäbisch-Hällisches Schwein is originally located in the region of Hohenlohe in Baden-Württemberg, which still is the main breeding area. The breed was developed since nearly 200 years ago by the local farmers and is well adapted to the regional conditions. Next to the genetic value of the old breed in terms of biodiversity, it is the basement for a sustainable local pork chain. In terms of scientific substantiation, their performances and products are mainly untapped. Thus the aim of the present chapter is to present history and current status of Schwäbisch-Hällisches pig breed, its exterior phenotypic characteristics, geographical location, production system and main products from this German autochthonous breed of pigs, one of the local pig breeds investigated in the project TREASURE. Moreover, a collection and review of available literature data, available until August 2017, on reproductive and productive traits of Schwäbisch-Hällisches pig breed were carried out. Meat quality of longissimus muscle completed the conventional productive traits as it is of great interest in autochthonous breeds. Although studies on Schwäbisch-Hällisches pig are scarce, current review gives the first insight into this local pig breed.",signatures:"Matthias Petig, Christoph Zimmer, Rudolf Bühler and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65315",previewPdfUrl:"/chapter/pdf-preview/65315",authors:[{id:"290257",title:"Dr.",name:"Matthias",surname:"Petig",slug:"matthias-petig",fullName:"Matthias Petig"},{id:"292143",title:"Mr.",name:"Christoph",surname:"Zimmer",slug:"christoph-zimmer",fullName:"Christoph Zimmer"}],corrections:null},{id:"65288",title:"Turopolje Pig (Turopoljska svinja)",doi:"10.5772/intechopen.83782",slug:"turopolje-pig-turopoljska-svinja-",totalDownloads:936,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Turopolje pig is a fatty-type pig breed created during the Middle Ages in Turopolje region in Central Croatia. Due to its modest demands, resilience and good adaptation to outdoor rearing, the Turopolje pig has been an important food source for the local population for centuries. However, with the transition from extensive to intensive pig production in the middle of the twentieth century, this autochthonous pig breed almost disappeared. Currently, despite the state support, Turopolje pig is still endangered, with a population of only 116 sows and 14 boars. Hence, to preserve Turopolje pig breed in a more sustainable way, the breed needs to be more economically exploited and scientifically explored. Thus, the aim of this chapter is to present history and current status of Turopolje pig breed, its exterior phenotypic characteristics, geographical location, production system and main products. Moreover, a collection and review of available literature data (available until August 2017) on reproductive and productive traits, including growth performance, carcass traits and meat and fat qualities of Turopolje pig breed, were carried out. Although studies on Turopolje pig are scarce, the present review gives the first comprehensive insight into this still untapped local breed of pigs investigated in the project TREASURE.",signatures:"Danijel Karolyi, Zoran Luković, Krešimir Salajpal, Dubravko Škorput, Ivan Vnučec, Željko Mahnet, Vedran Klišanić and Nina Batorek-Lukač",downloadPdfUrl:"/chapter/pdf-download/65288",previewPdfUrl:"/chapter/pdf-preview/65288",authors:[{id:"290258",title:"Dr.",name:"Danijel",surname:"Karolyi",slug:"danijel-karolyi",fullName:"Danijel Karolyi"}],corrections:null},{id:"65224",title:"Analytical Review of Productive Performance of Local Pig Breeds",doi:"10.5772/intechopen.84214",slug:"analytical-review-of-productive-performance-of-local-pig-breeds",totalDownloads:1188,totalCrossrefCites:8,totalDimensionsCites:15,hasAltmetrics:0,abstract:"Traits of interest concerning reproductive performance, growth performance, carcass and meat quality of local pig breeds involved in H2020 project TREASURE were collected from the available literature, unpublished data available to partners or results recorded in the experiments within the project. The survey revealed great variability in the availability and quality of information. Reproductive performance of local pig breeds is lower than in conventional modern pig breeds, not only due to their genetic background but also due to the management. Data on growth rates reflect the heterogeneity of different production systems and feeding regimes used. The growth potential of the majority of local pig breeds is not well exploited, and their nutritional requirements are not known. Generally, local pig breeds show low muscular development and high potential for fat tissue deposition and are slaughtered at older age and weight, which results in higher intramuscular fat and more intense colour of meat. However, considerable differences exist between them and their potentials, not only in their production systems. For many local pig breeds studied in the project, the collected information provides the first in-depth overview of their productive performance in their preserved, present-day phenotype.",signatures:"Marjeta Čandek-Potokar, Nina Batorek Lukač, Urška Tomažin, Martin Škrlep and Rosa Nieto",downloadPdfUrl:"/chapter/pdf-download/65224",previewPdfUrl:"/chapter/pdf-preview/65224",authors:[{id:"23161",title:"Dr.",name:"Marjeta",surname:"Čandek-Potokar",slug:"marjeta-candek-potokar",fullName:"Marjeta Čandek-Potokar"}],corrections:null}],productType:{id:"3",title:"Monograph",chapterContentType:"chapter",authoredCaption:"Authored by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6384",title:"Animal Husbandry and Nutrition",subtitle:null,isOpenForSubmission:!1,hash:"45e3ab6f834a3efc7836eb8b3c8e3427",slug:"animal-husbandry-and-nutrition",bookSignature:"Banu Yücel and Turgay Taşkin",coverURL:"https://cdn.intechopen.com/books/images_new/6384.jpg",editedByType:"Edited by",editors:[{id:"191429",title:"Prof.",name:"Banu",surname:"Yucel",slug:"banu-yucel",fullName:"Banu Yucel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5987",title:"Goat Science",subtitle:null,isOpenForSubmission:!1,hash:"35f3a7d6f517410f6581d265f17ee7c9",slug:"goat-science",bookSignature:"Sándor Kukovics",coverURL:"https://cdn.intechopen.com/books/images_new/5987.jpg",editedByType:"Edited by",editors:[{id:"25894",title:"Dr.",name:"Sándor",surname:"Kukovics",slug:"sandor-kukovics",fullName:"Sándor Kukovics"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6206",title:"Ruminants",subtitle:"The Husbandry, Economic and Health Aspects",isOpenForSubmission:!1,hash:"2f4344b633afc742eb0cfc50413c928b",slug:"ruminants-the-husbandry-economic-and-health-aspects",bookSignature:"Muhammad Abubakar",coverURL:"https://cdn.intechopen.com/books/images_new/6206.jpg",editedByType:"Edited by",editors:[{id:"112070",title:"Dr.",name:"Muhammad",surname:"Abubakar",slug:"muhammad-abubakar",fullName:"Muhammad Abubakar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6993",title:"Bovine Science",subtitle:"A Key to Sustainable Development",isOpenForSubmission:!1,hash:"fe7bdc1a2e1aa960e1f51dae7c705002",slug:"bovine-science-a-key-to-sustainable-development",bookSignature:"Sadashiv S. 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by",editors:[{id:"112070",title:"Dr.",name:"Muhammad",surname:"Abubakar",slug:"muhammad-abubakar",fullName:"Muhammad Abubakar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],ofsBooks:[]},correction:{item:{id:"79356",slug:"corrigendum-to-review-of-liquid-filled-optical-fibre-based-temperature-sensing",title:"Corrigendum to Review of Liquid-Filled Optical Fibre-Based Temperature Sensing",doi:null,correctionPDFUrl:"https://cdn.intechopen.com/pdfs/65367.pdf",downloadPdfUrl:"/chapter/pdf-download/65367",previewPdfUrl:"/chapter/pdf-preview/65367",totalDownloads:null,totalCrossrefCites:null,bibtexUrl:"/chapter/bibtex/65367",risUrl:"/chapter/ris/65367",chapter:{id:"63471",slug:"review-of-liquid-filled-optical-fibre-based-temperature-sensing",signatures:"Fintan McGuinness, Gabriel Leen, Elfed Lewis, Gerard Dooly, Daniel Toal\nand Dinesh Babu Duraibabu",dateSubmitted:"May 22nd 2018",dateReviewed:"August 1st 2018",datePrePublished:"November 5th 2018",datePublished:"April 24th 2019",book:{id:"8271",title:"Applications of Optical Fibers for Sensing",subtitle:null,fullTitle:"Applications of Optical Fibers for Sensing",slug:"applications-of-optical-fibers-for-sensing",publishedDate:"April 24th 2019",bookSignature:"Christian Cuadrado-Laborde",coverURL:"https://cdn.intechopen.com/books/images_new/8271.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"220902",title:"Dr.",name:"Christian",middleName:null,surname:"Cuadrado-Laborde",slug:"christian-cuadrado-laborde",fullName:"Christian Cuadrado-Laborde"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"27036",title:"Dr.",name:"Daniel",middleName:null,surname:"Toal",fullName:"Daniel Toal",slug:"daniel-toal",email:"daniel.toal@ul.ie",position:null,institution:{name:"University of 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1. Introduction
The Amazon or Amazon Rainforest is the largest remnant of tropical forest in the world, occupying a region of approximately 6.7 million/km2, covering nine countries in South America: Ecuador (≅ 2%), Suriname (≅ 2%), Bolivia (≅ 4%), Venezuela (≅ 4%), Guyana (≅ 3%), French Guiana (≅ 2%), Colombia (≅ 10%), Peru (≅ 13%), and Brazil (≅ 60%) (Figure 1) [1, 2]. In Brazil, the Amazon biome, also known as “Legal Amazon” occupies approximately 49% of its territory, covering the states of Acre, Amapá, Amazonas, Mato Grosso, Pará, Rondônia, Roraima, Tocantins and Maranhão (Figure 1). The Brazilian Amazon is known for its high richness of landscapes composed of 23 ecoregions, whose main domain is the humid rainforest (≅ 78%). Due to this heterogeneity, the Amazon has an immeasurable amount of essential habitats for the maintenance of flora and fauna, represented with high biological diversity, which is regarded as the largest in the world [3, 4] The Amazon has approximately 45,000 species of flora (39,474 species) and fauna (5,526 species) [2, 5]. However, even with this expressive diversity and the numerous faunal studies carried out in the region, there are still many gaps in the biological diversity of the Amazon. Due to its enormous extension and high degree of preservation (e.g., unexplored areas), new bioecological associations and new species are discovered every year. In the past 20 years, more than 1,200 new species have been described in the Amazon region from which we can highlight 16 birds, 39 mammals, 55 reptiles and ≅ 100 amphibians [2]. However, anthropic action has negatively impacted the animal-forest relationships for decades, resulting in the extinction of ecologically demanding species and, at the same time, the appearance of opportunistic and/or generalist species [6].
Figure 1.
Diversity of reptiles, amphibians, birds and mammals in Brazil, including the Brazilian Amazon.
Many domestic and wild animals are responsible for the maintenance and dispersion of ticks in nature. In addition, vertebrates act as amplifiers and/or reservoirs for viruses, protozoa and bacteria transmitted by these ectoparasites. The antropic action affects the population dynamics of both ticks and their wild hosts directly or indirectly, and consequently, the epidemiology of tick-borne diseases once restricted to wild fauna can reach domestic animal and humans interfaces [7]. Ticks are responsible for more than 100,000 cases of diseases in humans and animals worldwide [8], therefore a concern for public health professional. In Brazil, ticks are vectors of diseases such as babesiosis, ehrlichiosis, anaplasmosis and rickettsioses, including Brazilian Spotted Fever (BSF) [9, 10].
Ticks belong to the Sub-Class Acari, Super-Order Parasitiformes, Order Ixodida, and four families: Ixodidae, Argasidae, Nuttallielidae and Deinocrotonidae [11, 12], the latter extinct. Of these, only the Ixodidae and Argasidae families occur in Brazil, with nine genera and 75 species [11, 13, 14, 15, 16]. Ixodidae family is the most diverse with 51 species and five genera: Amblyomma (33 species), Ixodes (12 species), Rhipicephalus (two species), Haemaphysalis (three species) and Dermacentor (one species). Argasidae family is represented by 24 species and four genera: Ornithodoros (18 species), Antricola (three species), Argas (one species) and Nothoaspis (two species). In general, the immature stages (larvae and nymphs) of two or three host ticks feed on small mammals and birds, while adults exploit medium to large-sized hosts [17]. One-host species Dermacentor nitens and Rhipicephalus microplus, complete the life cycle mainly on large animals such as horses and cattle, respectively. Second Esser et al. [18] the diversity of ticks increases with the increase of diversity of hosts, inasmuch as these hematophagous arthropods rely on the hosts to complete their life cycles. Therefore, if we take into account the high diversity of hosts living in this biome and the amount of unexplored ecoregions, it is reasonable to infer that the diversity of ticks in the Amazon biome is insufficiently addressed. Thus, a review on the subject is necessary to point out the existing gaps and encourage new studies on ticks in the Brazilian Amazon.
2. Hard ticks associated with amphibians and reptiles
The class Amphibia includes the orders Anura, Caudata, Gymnophiona, whereas the class Reptilia includes the orders Squamata, Testudines and Crocodylia. There are 331 amphibian and 550 reptile species in the Brazilian Amazon (Figure 1), although that faunal records are far from complete [2, 19]. Brazil has witnessed an increasing number of reports on tick parasitism of amphibians and reptiles over the past few years [20, 21, 22, 23, 24]. However, knowledge of this tick fauna as their hosts remains incomplete. To date, major tick-amphibian associations reported in Brazil are the ixodids Amblyomma dissimile, Amblyomma rotundatum, Amblyomma humerale, Amblyomma fuscum and Amblyomma goeldii [20, 21, 22, 23, 24], and the argasids Ornithodoros saraivai and Ornithodoros faccinii associated with species Cycloramphus boraceiensis and Thoropa miliaris, respectively [25, 26]. Occasional records on reptiles have also been reported for Ornithodoros mimon and Ornithodoros rietcorreai [22]. However, none of these argasids have been reported in the Amazon biome. Although the Brazilian Amazon has a high diversity of amphibians and reptiles, studies on ticks in association with these hosts are still rare, with a dominance of species A. dissimile, A. rotundatum and A. humerale [21, 22, 23, 27, 28].
The tick A. dissimile is constantly misidentified with the morphologically similar A. rotundatum. Recently, the distribution of A. dissimile in the country was reorganized, showing that this tick is restricted to the Pantanal and Amazon biomes [28]. Therefore, reports outside these biomes are considered misidentifications and must be viewed with caution. Most publications on this species are simple records of occurrence with some authors including data on prevalence and intensity of infestation both in the Amazon biome and elsewhere. According to Luz et al. [29] 12 (54.5%) out of 22 Rhinella marina toads captured in Amapá state, were parasitized by a total of 97 ticks (6 males, 39 females, 31 nymphs, 21 larvae) and mean intensity of 8.1 ticks per infested toad. In the Amazonian biome, A. dissimile is common on R. marina (Anura) and Boidae (Squamata) (Table 1). The experimental life cycle including pre-attachment periods for each parasitic stage lasts approximately 350 days, as reported by Schumaker et al. [43] who started a colony from one engorged female collected from the Amazonian biome. Ogrzewalska et al. [37] reported Rickettsia bellii and ‘Candidatus Rickettsia colombianensi’ in ticks collected from Bothrops atrox from Pará state. Luz et al. [29] reported ‘Ca. R. colombianensi’ in ticks collected on R. marina from Amapá state.
Hosts of Amblyomma dissimile and Amblyomma rotundatum in the Brazilian Amazon.
The tick A. rotundatum is an obligate parthenogenetic species, although there are six reports of adult males, two males in the laboratory [44] and six in the Amazon region parasitizing Tropidurus sp., Boa constrictor, Iguana iguana, Chelonoidis denticulatus and B. atrox [30, 36, 44, 45, 46, 47]. Most publications on A. rotundatum are simple records of its occurrence with some additional data on prevalence and intensity of infestation in the Cerrado, Atlantic forest and Amazon biomes [22, 23, 31, 34, 48]. In the Brazilian Amazon, the families Bufonidae (Amphibian) and Boidae (Reptilia) are the most frequently parasitized by A. rotundatum, but there are reports on other species of Amphibian and Reptiles (Table 1). Recently, Gianizella et al. [31] reported A. rotundatum in different municipalities of the Amazonas state, on B. constrictor and several unknown hosts. The bioecology of this species under quasi-natural environment demonstrated a peak of larvae and nymphs in the dry season and females in the rainy season; however, there is a hypothesis of the absence of seasonality in this tick [48, 49]. Although A. rotundatum is a three-host tick on amphibians, it can behave as a two-host tick when feeding on snakes [50]. The complete experimental life cycle, including pre-attachment periods for each parasitic stage, ranged from 126 to 228 days on toads [51] or 56 to 163 days on snakes [50] and ulcerative lesions and hemorrhages after A. rotundatum feeding [48] were reported for ticks collected on toads from the Cerrado biome. Transmission of the hemogregarine Hemolivia stellata by R. marina collected in Belém, state of Pará was reported by Petit et al. [52]. This tick has also been found infected with R. bellii in the state of Amazon in the municipalities of Cacaulândia and Monte Negro, in the state of Rondônia; in the municipalities of Amapá (Ilha de Maracá) and Santana, in the state of Amapá; and in the municipality of Rio Branco, in the state of Acre [29, 53, 54].
Most reports of A. humerale mention the adult stage parasitizing species of tortoises, namely the “yellow-footed tortoise” C. denticulatus and the “red-footed tortoise” Chelonoidis carbonarius [27, 55]. There is also a record of A. humerale on Rhinoclemmys punctularia in central Amazon [56]. Labruna et al. [27] collected 215 adult ticks from six C. denticulatus and nine Chelonoidis sp. from state of Rondônia, with mean infestation of 14.3 ± 12.0 ticks per tortoise. In addition, seven engorged nymphs were collected on lizards. Morais et al. [57] collected 120 adult ticks from 18 (75%) out of 24 C. denticulatus captured in a transitional area between the biomes Cerrado and southwestern Amazon rainforest, in the state of Mato Grosso. The mean intensity of infestation was 6.7 ticks/tortoise. In both surveys, male ticks were mostly attached in clusters on the carapace whereas females were found attached to the tortoise skin. The sex ratio (males:females) for A. humerale were different in both surveys, 10.3:1 [27] and 1.1:1 [57]. There is one additional record of two nymphs on Paleosuchus trigonatus (Crocodylia) [32]. The life-cycle in the laboratory, including pre-feeding periods for each of the parasitic stages, could be completed in an average period of ca. 200 days [58]. Rickettsia bellii and Rickettsia amblyommatis have been detected in A. humerale [42, 53]. The records of A. fuscum in association with amphibians and reptiles are rare in Brazil. Dantas-Torres et al. [59] collected one male tick in one out of 490 caimans (Caiman latirostris and Paleosuchus palpebrosus) trapped in the Atlantic rainforest biome in Pernambuco state, north-eastern Brazil. Amblyomma goeldii has been recorded only in the Amazonas state. Martins et al. [60] reported two males collected on B. constrictor and recovery of ≈100 (20%) engorged larvae out of ≈500 unfed larvae experimentally infested on a B. constrictor.
3. Hard ticks associated with wild birds
The importance of birds to maintain biodiversity and ecological balance of nature is notorious [61]. Due to migration, wild birds are of concern to human and animal health worldwide [62] because they can carry infected ticks over long distances, directly influencing the epidemiology of tick-borne diseases in animals and humans. In addition, wild birds themselves can be reservoirs of Borrelia burgdorferi sensu lato, and potentially to Anaplasma phagocytophilum and Rickettsia spp. [62, 63]. Wild birds play an important role in maintaining and dispersing immatures (larvae and nymphs) of several tick species into new locations [61, 64].
Of the total genera of ticks described in Brazil, five have at least one species recorded in association with wild birds. The most common are the hard ticks of the genera Amblyomma, Haemaphysalis and Ixodes [61, 64]. There are also occasional reports of the genera Rhipicephalus and Ornithodoros. Ticks of the genus Amblyomma are the most common on wild birds in the Brazil including the Amazon biome, exclusively for the larvae and nymphs [61, 64]. Adult ticks are only occasionally found on wild birds, with the exception of Ixodes paranaensis and Ixodes auritulus, which have the entire cycle synchronized with birds [65]. In Brazil, there are no reports of wild birds as a source of pathogens transmitted by ticks to humans, but they can serve as disperser hosts for vectors of Brazilian Spotted Fever (BSF) as Amblyomma sculptum, Amblyomma aureolatum and Amblyomma ovale, in the larvae and nymph stages [64]. Therefore, wild birds act indirectly in the epidemiology of BSF by dispersing and maintaining their vectors in nature.
Over more than 1,900 birds recorded in Brazil, approximately 1,300 reside in the Brazilian Amazon, with a 20% of endemism [66] (Figure 1). Of these, approximately 7% are migrants from the northern hemisphere and southern South America, including migrations from other Brazilian biomes [67]. To date, 86 bird species of Brazilian Amazonian have been recorded in association with at least one tick species (Table 2). This is equivalent to approximately only 7% of bird species found in this biome and 5% of the total birds recorded in Brazil (Table 2). Similar to other studies regarding tick-bird associations in Brazil [73, 74, 75], Passeriformes birds were the most parasitized in the Amazon biome, including 14 families and 72 species (Figure 2 and Table 2). In this group, the greatest diversity of parasitized birds was Thamnophilidae (20 species) followed by Dendrocolaptidae (16 species) and Tyrannidade (10 species) (Figure 2). The least parasitized families were Conopophagidae, Furnariidae, Xenopidae, Tityridae, Cardinalidae, Columbidae, Cuculidae, Momotidae, Capitonidae, Ramphastidae, Psittacidae, Accipitridae and Falconidae with only one species of parasitized bird each (Figure 2 and Table 2). Non-Passerines were represented by 10 different orders and 11 families, with emphasis on Bucconidae with three species (Figure 2 and Table 2). To date, approximately 1,068 specimens of ticks have been collected from birds in the Brazilian Amazon, in the stages of larvae (884/83%), nymphs (184/17%) and no adults (Figure 3). These are included in the genera Amblyomma and Haemaphysalis. The genus Amblyomma was the dominant with eight species (Table 2). The greatest diversity of ticks was reported for the Thamnophilidae family with seven species: A. longirostre, A. nodosum, A. humerale, A. calcaratum, A. geayi, A. coelebs and Haemaphysalis juxtakochi. The Dendrocolaptidae family was the second with five species: A. longirostre, A. nodosum, A. humerale, A. calcaratum and A. geayi (Figure 2 and Table 2).
Ticks identified on wild birds in the Brazilian Amazon biome.
Figure 2.
Diversity of hard ticks parasitizing wild birds from the Brazilian Amazon.
Figure 3.
Distribution of studies reporting the association of hard ticks on wild birds from the Brazilian Amazon.
Overall, A. longirostre and A. nodosum are the two most common species on wild birds in the Brazilian Amazon [68, 69, 70, 71] (Figure 4 and Table 2). The tick A. longirostre was the most common, recorded in 12 families and 40 species of birds (36 Passerines and 4 non-Passerines) (Figure 2). Amblyomma longirostre has been treated as an arboreal tick, with immatures parasitizing birds and adults parasitizing rodents Erethizontidae (e.g., Sphiggurus spp.) [73, 76]. This tick was also the most abundant with 110 larvae and 39 nymphs. Amblyomma longirostre was found in co-infestation with the following species: A. calcaratum, A. nodosum, A. coelebs, A. humerale, A. geayi and H. juxtakochi (Table 2). In addition, as it is frequent on birds, A. longirostre is popularly known as “bird tick” or “bird earring” [77]. Amblyomma nodosum was the second most common species collected on 12 families and 22 species of birds. This tick was recorded in co-infestation with A. longirostre, A. coelebs, A. humerale and A. geayi (Table 2 and Figures 2 and 4). The birds most infested by A. nodosum were Rhynchocyclus olivaceus and Ramphocelus carbo with 17 and 15 nymphs, respectively. These birds inhabit the forest understory and visit the soil occasionally [67]. As Xenartha mammals (Myrmecophaga tridactyla, Tamandua tetradactyla) are the primary hosts of A. nodosum [17], it is believed that the low areas of the understory are a major source of infestation. Interestingly, T. tetradactyla may have arboreal habits [78], which helps to explain the presence of A. nodosum also on birds of different forest strata.
Figure 4.
Hard tick species parasitizing wild birds from the Brazilian Amazon.
To date, of the total of ticks collected, 736 (70%) were larvae identified as Amblyomma sp. due to lack of reliable tools for larval identification, thus, indicating that the diversity of ticks on birds of the Amazon may be underestimated. Luz et al. [75], using molecular biology, identified more than 90% of the larvae collected from birds in the Atlantic Forest biome, reporting the greatest diversity of ticks on birds in a single study in Brazil and description of the new tick Amblyomma romarioi [14]. Therefore, the identification of all larvae by molecular biology in addition to morphological identification is extremely important to ascertain the diversity of ticks in the Amazon biome.
4. Hard ticks associated with wild and domestic mammals
The fauna of wild mammals in Brazil is quite diverse and more than half lives in the Amazon biome [79]. Like birds, amphibians and reptiles, mammals play an important role in preserved or anthropized ecosystems. Therefore, the knowledge of the local diversity of wild mammals, and their relationship with ticks is considered an important tool for public conservation policies and consequently for public health. The alteration of wild habitats can determine changes in the patterns of parasitic specificity, inducing tick species to seek new groups of hosts, increasing the risk of disease transmission [79, 80]. Some wild mammals (small, medium and large) are directly or indirectly involved in the transmission cycles of many tick-borne pathogens worldwide, including Anaplasma spp., Babesia spp., Borrelia spp., and Rickettsia spp. [80, 81]. In Brazil, the main zoonosis transmitted by ticks is Brazilian Spotted Fever caused by the bacterium Rickettsia rickettsii, which has the rodent Hydrochoerus hydrochaeris as its main amplifier. In addition, there is evidence that marsupials and small rodents can serve as amplifier hosts for R. rickettsii in nature [82].
In Brazil there are approximately 755 species of mammals distributed in all its six biomes, including the Amazon biome [78, 79]. Of the total mammal species, 41% (≅ 311 species) occur in the Amazon biome (Figure 1) [2, 76]. These vertebrates are distributed in 11 orders, 51 families and 249 genera [78, 79]. Among the families, Cricetidae is the most diverse, with 144 species [78, 79]. The vast majority of tick species, including all life stages, in Brazil have records on wild mammals of different sizes [17]. In general, small mammals of the orders Rodentia and Didelphimorphia are those that have a greater number of studies in association with ticks, especially the families Cricetidae and Didelphidae [17, 82]. In general, medium and large mammals are parasitized by ticks in all stages (larva, nymph and adult), while in small mammals the stages of larva and nymph are more common. In this last group of hosts we can highlight the cricetids Akodon spp., Calomys spp., Oligoryzomys spp. and Nectomys spp. as the most parasitized by immature ticks in nature.
Nine orders and 24 families of wild mammals have representatives in association with ticks in the Brazilian Amazon (Figure 5). Rodentia was the most diverse with 16 species of mammals, followed by the orders Carnivora (13 species) and Didelphimorphia (12 species) (Figure 5). However, it was the family Didelphidae that presented a greater number of parasitized species, followed by Dasyproctidae (seven species) and Mustelidae (four species). These records corroborate with numerous studies of tick parasitism on wild animals from South America, with emphasis on the orders Rodentia and Didelphimorphia [17, 82, 83].
Figure 5.
Diversity of hard ticks parasitizing wild mammals from the Brazilian Amazon.
Hard ticks parasitizing wild mammals in the Brazilian Amazon are represented by five genera: Amblyomma, Ixodes, Haemaphysalis, Dermacentor and Rhipicephalus. Of these, the genus Amblyomma was more frequently recorded with 23 species (Figure 5). The orders Rodentia, Pilosa and Didelphimorphia are hosts for highest diversity to Amblyomma species 17, 15 and eight, respectively. All these species are also recorded on a variety of wild mammals in Brazil [83, 84, 85, 86, 87], except for A. rotundatum and A. dissimile, which are more specific ticks of cold-blooded animals (Amphibians and Reptiles), although there are occasional reports on mammals in South America [20, 83]. Amblyomma humerale, of which the adult stage is more specific to tortoises, immature stages have been found on a variety of small mammals, reptiles and birds [17, 68, 71, 83].
The second most common genus in the Amazon is Ixodes, with six reported species: Ixodes amarali, Ixodes bocatorensis, Ixodes lasallei, Ixodes luciae, Ixodes schulzei and Ixodes spinosus (Table 3). Although there are two exclusive species on birds in Brazil [65], all species recorded in the Brazilian Amazon parasitize mainly wild mammals [13, 16, 31, 32, 88, 99, 102]. Ixodes spp. were found on families Didelphidae, Dasyproctidae, Cricetidae, Myrmecophagidae, Bradypodidae and Cyclopedidae (Figure 5 and Table 3). In general Ixodes ticks mainly parasitize rodents (e.g., Cricetidae) in the larvae and nymph stages, with adults feeding mostly on marsupials (e.g., Didelphis spp., Monodelphis spp.) [17, 83], and agoutis (e.g., Dasyprocta) [13, 16]. Most species were found parasitizing Monodelphis glirina (I. amarali, I. schulzei, I. luciae) and Monodelphis touan (I. amarali, I. schulzei), with some reports of I. amarali on the rodent Hylaeamys megacephalus [30, 38, 92, 99, 100]. Also on rodents the species I. spinosus, I. lasallei and I. bocatorensis have been recorded [30, 31, 38], although these previous records referred to them erroneously as Ixodes fuscipes, which according to more recent data, does not occur in the Amazon biome (Figure 5 and Table 3) [13, 16].
Records of ticks in the Amazon biome, Brazil, according to tick species, hosts (domestic and wild animals), states, references.
Acre – AC.
Amapá – AP.
Amazonas – AM.
Maranhão – MA.
Mato Grosso – MT.
Pará – PA.
Rondônia – RO.
Roraima – RR.
Tocantins – TO.
In general, the greatest diversity of ticks was recorded on T. tetradactyla with 10 species, followed by the rodent H. hydrochaeris with nine species. These records indicates the importance of these hosts for maintaining local tick diversity, in addition to act as dispersers of these ectoparasites. Additional hosts have also been shown to be important in maintaining diversity of tick in the Amazon: Tapirus terrestris, Tayassu pecari, Pecari tajacu, Agouti paca, Dasyprocta fuliginosa, Bradypus tridactylus, Bradypus variegatus, Panthera onca, Nasua nasua, Choleopus didactylus, Choloepus hoffmanni, Cyclopes didactylus, Dasyprocta azarae, Dasyprocta leporina, Philander opossum, M. glirina, M. touan, Mazama gouazoubira, Mazama americana and M. tridactyla (Table 3), because they are parasitized by more than one species of ticks. There is also a record of A. cajennense s.s. on Pteronura brasiliensis a semi-aquatic animal [89].
Interestingly, three species of ticks commonly found on domestic animals have also been found parasitizing wild animals: Rhipicephalus sanguineus sensu lato, R. microplus and D. nitens. Although occasional, the encounter of these species of ticks on wild animals is possible, especially when wild animals coexist with domestic animals infested by ticks (e.g., pastures, corrals, houses). A total of 11 species of ticks have been recorded parasitizing domestic animals in Amazon (Table 3).
5. Hard ticks associate with humans
Spotted fevers caused by R. rickettsii and Rickettsia parkeri are currently the only confirmed tick-borne disease affecting humans in the country, and A. sculptum, A. aureolatum, A. ovale are the main vectors. The disease is severe and highly lethal when caused by the bacterium R. rickettsii (vectors A. sculptum and A. aureolatum) and moderate, non-lethal, when caused by R. parkeri, vectored mainly by A. ovale [10]. Only A. sculptum and A. ovale have been recorded in the Brazilian Amazon, the first in rare reports and the second frequently recorded and populations established in this biome. In fact, considering only the tick adult stage, A. ovale has been reported as the most common human-biting tick in the Amazon [38].
In the last century, papers about ticks on human beings have been published in the Brazilian Amazon, however these studies are fragmented and scarce. At least 14 species of hard ticks have already been found and documented parasitizing humans within the limits of the Brazilian Amazon. Of these, the vast majority (11 species) belong to the genus Amblyomma: A. cajennense s.s., A. coelebs, A. dissimile, A. latepunctatum, A. naponense, A. oblongoguttatum, A. ovale, A. romitii, A. rotundatum, A. scalpturatum and A. sculptum. The other three species belong to the genus Rhipicephalus, including R. microplus and R. sanguineus s.l., and the genus Haemaphysalis with only H. juxtakochi. The public health importance of human–tick associations in the Amazon biome is unclear and further research are needed to clarify the issue.
Nymphs of H. juxtakochi have been reported on humans in the states of Rondônia (municipality not precisely indicated) and Amazonas, in the municipality of Santa Isabel do Rio Negro [31, 38]. H. juxtakochi has been found infected with the bacterium Rickettsia rhipicephali in the Amazon region, more precisely in the municipalities of Monte Negro and Confresa, states of Rondônia and Mato Grosso, respectively [42, 93]. Human parasitism by R. microplus was expected, since this species can parasitize humans when it comes into direct contact with domestic cattle, as reported by [38]. Therefore, its importance is much more economical, causing severe losses to livestock in the country than for public health.
Despite sporadic records of R. sanguineus s.l. on humans in Brazil, this association in the Brazilian Amazon requires confirmation. Records of approximately 4,020 R. sanguineus s.l. (larva, nymph, and adult), supposedly collected on humans, in the state of Pará by Serra-Freire et al. [103] do not corroborate the common findings in country. The bioecology of this endophilic and introduced tick is well studied. In other countries, R. sanguineus s.l. is vector of some zoonotic agents for humans (Rickettsia conorii, Rickettsia massiliae and R. rickettsii) [83]. Adults of A. cajennense s.s. have been reported on humans in the municipality of Monte Alegre (Pará state) [90]. Reports of Amblyomma cajennense sensu lato parasitizing humans published by Martins et al. [90] in the municipalities of Sinop and Tucuruí in the states of Mato Grosso and Pará, is possibly A. cajennense s.s. taking into account the area of occurrence of this species. This tick is aggressive to humans. In the Amazon biome the R. bellii bacterium was detected in this species in Mato Grosso state and R. amblyommatis in Mato Grosso, Maranhão and Rondônia state [32, 42, 53, 83, 88, 90, 91, 104, 105].
Nymphs and adult of A. coelebs were found on humans in Rondônia state [38]. An adult of this tick was found on human in Roraima state, municipality of Caroebe [106]. The nymph and adult stages of A. colelebs were also found on humans in Amazonas state, in the municipalities of Coari, Fonte Boa, Presidente Figueiredo and Santa Isabel do Rio Negro [31, 107]. There are reports of infection by R. amblyommatis in A. coelebs in the Amazon region in the states of Rondônia and Mato Grosso, respectively [32, 53, 88]. Adult of A. dissimile was recorded on humans in the Maicurú River/Amazon biome, located in Pará state [106]. Adults of the species A. latepunctatum have been reported on humans in Coari and Santa Isabel do Rio Negro, both municipalities located in the state of Amazonas [31].
Adults of the tick A. naponense (published as Amblyomma mantiquirense) were found on humans in the state of Pará (municipality not reported) [108]. Human parasitism also by adults was later reported on the Maicurú River, located in this same state [106]. However, nymphs have been found on humans in the states of Rondônia (municipality not specified precisely) and Amazonas, in the municipalities of Coari and Santa Isabel do Rio Negro [31, 38]. The bacteria R. bellii and Rickettsia sp. strain PA were identified in this species in the Amazon region of the municipalities of Santarém and Rurópolis, in the state of Pará [42]. Rickettsia sp. strain Tapirapé was found in this tick in the municipalities of Confresa and Rio Branco, in the states of Mato Grosso and Acre, respectively [42, 54].
Adults of the species A. oblongoguttatum were recorded parasitizing humans in the state of Pará, in the Maicurú River and in the municipality of Uruará [106, 108, 109]. Human parasitism by nymphs and adults of this tick was recorded in the state of Rondônia (municipality not specified with precision) [38]. However, the nymphal stage of this species was later recorded on humans in the municipality of Monte Negro in the same state [106]. Human parasitism by adult of this tick was also recorded in the municipality of Caroebe, state of Roraima [106]. Nymphs and adults of this species have been recorded parasitizing humans in three municipalities (Coari, Manacapuru and Santa Isabel do Rio Negro), all located in the state of Amazonas [31, 106, 107]. On the other hand, the life cycle of this tick has already been studied under laboratory conditions [110]. The bacteria R. bellii and R. amblyommatis were detected in this species in the Amazon in the municipalities of Governador Jorge Teixeira and Pimenta Bueno, in the state of Rondônia [53, 105].
Adults of the tick A. ovale have been reported to parasitize humans in several areas of the state of Rondônia [38]. As previously reported in this chapter, adults of A. ovale parasitize mainly domestic and wild carnivores, while immature (larva and nymph) parasitize rodents of the families Cricetidae and Echimyidae, with sporadic reports on wild birds [17, 75, 83]. This preference for such host groups was observed in the laboratory [111]. This tick is a vector of the protozoan Hepatozoon canis and the bacterium R. parkeri, agents of importance in veterinary and human medicine, respectively [83]. In the Amazon region, the bacterium R. bellii was identified in this species in the municipalities of Governador Jorge Teixeira and Monte Negro, in the state of Rondônia; and in the municipality of Cururupu, in the state of Maranhão [53, 91].
The adult stage of the species A. romitii (published as Amblyomma tasquei) was found parasitizing humans in the north of the state of Pará (municipality not reported) [108]. In this same state, the larval and adult stages of this tick were found on humans in the municipality of Rurópolis [96, 112]. The life cycle of this tick was studied under laboratory conditions [113].
Parasitism by adults of A. rotundatum was recorded in the municipality of Belém in the state of Pará on a human who worked in frequent contact with reptiles in the Zoobotanical Park of the Museu Paraense Emílio Goeldi [114].
Adults of the A. scalpturatum have been reported to parasitize humans in the state of Pará (municipality not reported) [108], and in the Maicurú River located in this state [93, 106]. Human parasitism by the nymphal and adult stages of this species has been reported in the states of Mato Grosso (municipality of Jauru) and Rondônia (municipality not precisely indicated), however in this latter state it was not specified whether these adult ticks were fixed or walking on humans [38, 93]. The nymphal stage was also collected from a human who was probably infested with this tick in the municipality of Porto Velho in the state of Rondônia [115]. The nymph and adult stages of this species were also found parasitizing humans in the state of Amazonas, in the municipalities of Coari, Fonte Boa, Jutaí, Presidente Figueiredo and Santa Isabel Rio Negro [31, 107]. In the Amazon biome, two species of rickettsiae (R. bellii and R. amblyommatis) were detected in A. scalpturatum, in the municipalities of Governador Jorge Teixeira and Sinop, states of Rondônia and Mato Grosso, respectively [53, 88].
Human parasitism by adults of A. sculptum was recorded in the municipality of Jauru in the state of Mato Grosso [90]. The Jauru territory comprises 90% of the Amazon biome and 10% of the Cerrado biome, so this human record in this region is in accordance with the transition area of the occurrence of this species in sympatry with A. cajennense s. s. [90]. The bioecology of this native tick has been extensively studied due to its aggressive parasitism towards domestic animals and humans in the Brazilian territory. In the geographical area in which this species occurs, it completes an annual generation, with larvae occurring mostly during autumn, nymphs during winter, and adults during spring and summer, with larval behavioral diapause being the main regulating factor of its life cycle [116, 117]. Besides being considered a pest for domestic animals (dogs, cattle and horses), the species can transmit to humans the Brazilian Spotted Fever caused by the bacterium R. rickettsii, being this the most important zoonotic disease transmitted by ticks within the limits of the National territory. Additionally, A. sculptum has also been identified with the bacterium R. amblyommatis in the municipality of Pium, state of Tocantins [118].
There is a trend of seasonal behavior for some species of Amblyomma in the Amazon biome, with immatures predominating in the dry period (June to October), and adults in the rainy period (October to March) [119]. Similar to the pattern observed for A. sculptum in areas outside the Amazon biome [116].
6. Soft ticks in the Brazilian Amazon
Taxonomy of Argasidae is currently questionable and relies on five schemes that divide the family in up to ten genera [120]. Achieving a consensus between soft tick taxonomists depends now chiefly on the molecular characterization of early collected type specimens for some genera. For instance, elucidating the status of pivotal taxa such as Alectorobius is mandatory if we are to understand the systematics of the Argasidae, particularly in the American Continent. Considering a practical approach, in this chapter we adopt but not necessarily endorse the classification of soft ticks into five genera, namely: Antricola, Argas, Nothoaspis, Ornithodoros, and Otobius [121].
The fauna of argasid ticks in Brazil is currently composed by 24 species [15]. Ticks of this family parasitize terrestrial vertebrates including amphibians in this country [25, 26]. With the exception of larvae from an undetermined Ornithodoros sp. collected on Potus flavus (Procionidae) [84], reports of soft ticks parasitizing mammals in the Brazilian Amazon are few and almost restricted to larvae collected on bats. Adults and nymphs have been collected either inside bat-inhabited caves or over massive rock formations where bats shelter (Table 4).
Soft ticks and their respective hosts occurring in the Brazilian Amazon.
The first record of a soft tick in the Brazilian Amazon was published by North American entomologists Robert A. Cooley and Glen M. Kohls back in 1941. They received a tick collected inside a bat-inhabited three hole at Marajó Island (Pará state) and identified it as female of Ornithodoros hasei (mentioned as Ornithodoros dunni) [126]. Nowadays, we know that O. hasei is a wide spread species in Brazil and that three-roosting bats Artibeus planirostris and Noctilio spp. could act as main hosts [87, 130, 131, 132]. With the exception of recent collection of larvae on A. planirostris [87], knowledge on the distribution of O. hasei along the Brazilian Amazon is still poorly vague.
Tadarida laticaudata were the first bats reported to be parasitized by soft ticks in the Brazilian Amazon [133]. This report referred to Ornithodoros setosus, which was recently reclassified as Nothoaspis setosus [124]. In 1972, the bats Noctilio labialis and T. laticaudata were reported to be parasitized by Ornithodoros stageri in the Brazilian Amazon [129], which was recently confirmed [11]. A report in the Brazilian Amazon is a remarkable fact for O. stageri, since it also has distribution in Southern United States and Mexico [126, 134].
Bat inhabited caves constitute excellent niches to find argasid ticks. In particular, special, large colonies of insectivorous bats dwelling inside small chambers create high temperature conditions (28-40°C) where hundreds of Antricola, Nothoaspis and Ornithodoros ticks might occur [135]. Between 2004 to 2010 collections of ticks performed in hot caves from Porto Velho (Rondônia) fostered the description of two novel species (e.g., Nothoaspis amazoniensis and Ornithodoros rondoniensis) [122, 123]; the redescription of larvae and description of postlarval stages of Ornithodoros marinkellei [127], and the expansion of geographical distribution of Antricola delacruzi and Antricola guglielmonei into Brazilian Amazon [122]. At least for two species, O. marinkellei and O. rondoniensis, further collections performed in caves from Pará state underpined a larger distribution along the Amazon ecosystems [128].
Most amazing feature of soft ticks inhabiting hot caves, is that adaptation to this particular milieu seems to have modified their morphology and biology drastically. For instance, evidence showing that adults of Antricola ticks lack the capacity to digest blood has been gained after transcriptomic analyses of their saliva [136]. In fact, scoop-like short mouth parts suggest that adults of Antricola do not suck blood [137]. Moreover, adults of Antricola, O. marinkellei and O. rondoniensis possess huge spiracular plates [122, 127, 137], perhaps necessary to thrive in such hot and extremely humid environments.
Except for larvae of Ornithodoros kohlsi collected on the bat Molossops mattogrossensis [30], prospections performed by our group between 2016 and 2019 focused mainly in the search for soft ticks inside natural cavities over massive rock formations. During these expeditions, Ornithodoros cavernicolous and Ornithodoros peropteryx were collected for the first time in caves from Monte Negro (Rondônia), extending their distribution of both species to the Brazilian Amazon [125]. Furthermore, analyses performed on large larvae isolated from Molossus molossus bats clarified that O. setosus was incorrectly classified in its original description. Indeed, O. setosus matches morphologically and molecularly within the genus Nothoaspis therefore the statement of N. setosus n. comb. was proposed [124]. It is important to note that our last collections performed at Monte Negro included several morphotypes of Ornithodoros pending formal description. Consequently, the fauna of soft ticks occurring in the Brazilian Amazon is likely to increase soon.
7. Conclusion
Ticks parasitize a wide variety of vertebrates around the world such as amphibians, reptiles, mammals and birds, including humans. Although there are a variety of studies of parasitism by ticks on animals and humans in the different ecoregions of Brazil, in the Amazon biome they are scarce and fragmented. Because of this, it is possible to infer that the diversity of ticks in the Brazilian Amazon is underestimated. In the Amazon, amphibians and reptiles were important hosts for A. rotundatum, A. dissimile and A. humerale, hard ticks common in these hosts in other regions of the country. Birds and mammals, on the other hand, proved important for the maintenance and dispersion of over 30 species of hard ticks in the Amazon, but there are still many gaps between hosts and their ticks in this region. Interestingly, immature A. humerale appears to be frequent on wild birds in this biome. No soft ticks have been reported parasitizing amphibians, reptiles, birds and/or non-flying mammals (except for a single record of Ornithodoros sp. on P. flavus), possibly due to scarcity of more studies in this biome. Some studies show that bats seem to have an important role spreading soft tick populations along Amazonian caves and that the diversity described for this group is still very poor. Two vector species of spotted fevers were found in the Amazon biomes parasitizing humans (A. sculptum and A. ovale). However, to date, there are no reports of BSF in humans in the region. Finally, it is of paramount importance that researchers (acarologists and epidemiologists) direct their attention to the Amazon biome, in order to fill the numerous existing gaps in the diversity of ticks in Brazil and prevent possible outbreaks of diseases transmitted by these ectoparasites to animals and humans.
Conflict of interest
No conflict of interest declared.
\n',keywords:"Ixodida, domestic animals, wild animals, humans, Amazon, Brazil",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/74564.pdf",chapterXML:"https://mts.intechopen.com/source/xml/74564.xml",downloadPdfUrl:"/chapter/pdf-download/74564",previewPdfUrl:"/chapter/pdf-preview/74564",totalDownloads:458,totalViews:0,totalCrossrefCites:2,totalDimensionsCites:3,totalAltmetricsMentions:2,introChapter:null,impactScore:1,impactScorePercentile:55,impactScoreQuartile:3,hasAltmetrics:1,dateSubmitted:"July 5th 2020",dateReviewed:"November 1st 2020",datePrePublished:"December 23rd 2020",datePublished:"March 10th 2021",dateFinished:"December 23rd 2020",readingETA:"0",abstract:"Ticks are important ectoparasites and can transmit a wide variety of pathogens to animals and humans worldwide. These ectoparasites are the most important vectors of diseases causing pathogens in domestic and wild animals, and the second for man. In Brazil, Spotted Fever is the only disease transmitted to humans by ticks, while for animals we can highlight babesiosis, ehrlichiosis and anaplasmosis. Although ticks are found in all of Brazil’s biomes, little is known about its diversity and host-relations in the Amazon biome. The existing gaps and the lack of research indicate that the diversity of ticks and their possible pathogens are underestimated in the Brazilian Amazon. Therefore, in order to guide the next studies in the Amazon biome, we present in this chapter a compilation of the records of hard ticks and soft ticks parasitizing wild and domestic animals, and humans. We present the general list of ticks for this biome, their distribution, hosts and importance for public health and veterinary. Finally, the ixodofauna found in the Brazilian Amazon and presented here does not match the vertebrate diversity of this biome, which is one of the largest on the planet. Therefore, more acarologists and epidemiologists are needed in this region.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/74564",risUrl:"/chapter/ris/74564",book:{id:"10248",slug:"ecosystem-and-biodiversity-of-amazonia"},signatures:"Hermes R. Luz, Thiago F. Martins, Sebastián Muñoz-Leal, Francisco B. Costa, Sérgio L. Gianizella, João Luiz H. Faccini and Marcelo B. Labruna",authors:[{id:"307913",title:"Prof.",name:"Hermes",middleName:"R.",surname:"Luz",fullName:"Hermes Luz",slug:"hermes-luz",email:"hermesluz@usp.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Federal University of Maranhão",institutionURL:null,country:{name:"Brazil"}}},{id:"336673",title:"Dr.",name:"Thiago F.",middleName:null,surname:"Martins",fullName:"Thiago F. Martins",slug:"thiago-f.-martins",email:"thiagodogo@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Hospital Universitário da Universidade de São Paulo",institutionURL:null,country:{name:"Brazil"}}},{id:"336675",title:"Dr.",name:"Sebastián",middleName:null,surname:"Muñoz-Leal",fullName:"Sebastián Muñoz-Leal",slug:"sebastian-munoz-leal",email:"sebamunoz@udec.cl",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Fundação de Apoio à Universidade de São Paulo",institutionURL:null,country:{name:"Brazil"}}},{id:"336676",title:"Prof.",name:"Francisco B.",middleName:null,surname:"Costa",fullName:"Francisco B. Costa",slug:"francisco-b.-costa",email:"franc.borgesma@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Universidade Estadual do Maranhão",institutionURL:null,country:{name:"Brazil"}}},{id:"336677",title:"Prof.",name:"Sérgio L.",middleName:null,surname:"Gianizella",fullName:"Sérgio L. Gianizella",slug:"sergio-l.-gianizella",email:"sergio.gianizella@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Federal University of Amazonas",institutionURL:null,country:{name:"Brazil"}}},{id:"336678",title:"Prof.",name:"João Luiz H.",middleName:null,surname:"Faccini",fullName:"João Luiz H. Faccini",slug:"joao-luiz-h.-faccini",email:"faccinijlh@globo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Universidade Federal Rural do Rio de Janeiro",institutionURL:null,country:{name:"Brazil"}}},{id:"336679",title:"Prof.",name:"Marcelo B.",middleName:null,surname:"Labruna",fullName:"Marcelo B. Labruna",slug:"marcelo-b.-labruna",email:"labruna@usp.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Hard ticks associated with amphibians and reptiles",level:"1"},{id:"sec_3",title:"3. Hard ticks associated with wild birds",level:"1"},{id:"sec_4",title:"4. Hard ticks associated with wild and domestic mammals",level:"1"},{id:"sec_5",title:"5. Hard ticks associate with humans",level:"1"},{id:"sec_6",title:"6. Soft ticks in the Brazilian Amazon",level:"1"},{id:"sec_7",title:"7. Conclusion",level:"1"},{id:"sec_11",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Silva JMC, Rylands AB, Fonseca GAB. The fate of the Amazonian areas of endemism. Conservation Biology. 2005; 19: 689-694'},{id:"B2",body:'MMA. Ministério do Meio Ambiente. 2018. Acessed: 03/10/2120'},{id:"B3",body:'Vieira ICG, Toledo PM, Silva JMC, Higuchi H. Deforestation and threats to the biodiversity of Amazonia. Brazilian Journal of Biology. 2008; Suppl 0'},{id:"B4",body:'Evans KL, Newson SE, Storch D, Greenwood JJ, Gaston KJ. Spatial scale, abundance and the species-energy relationship in British birds. Journal of Animal Ecology. 2008; 77: 395-405'},{id:"B5",body:'Rylands AB. Amazonia. In: Wilderness: Earth’s last wild places. Agrupación Serra Madre, S. C. Mexico: CEMEX, 2002; 56–107'},{id:"B6",body:'Parrotta JA, Wildburger C, Mansourian S. Understanding relationships between biodiversity, carbon, forests and people: the key to achieving REDD+ objectives. 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Ticks and Tick Borne Diseases. 2019; 10: 101252'},{id:"B12",body:'Peñalver EA, Arillo X, Delclòs D, Peris DA, Grimaldi SR, Anderson PC. Nascimbene, and R. Pérez-de la Fuente. Ticks parasitised feathered dinosaurs as revealed by Cretaceous amber assemblages. Nature Communications.2017; 8: 1924'},{id:"B13",body:'LabrunaMB, OnofrioVC, Barros-Battesti, GianizellaSL, VenzalJM, GuglielmoneAA. Synonymy of Ixodes aragaoi with Ixodes fuscipes, and reinstatement of Ixodes spinosus (Acari: Ixodidae). Ticks and Tick-borne Diseases. 2020; 11: 101349'},{id:"B14",body:'Martins TF, Luz HR, Muñoz-Leal S, Ramirez DG, Milanelo L, Marques S, et al. A new species of Amblyomma (Acari: Ixodidae) associated with monkeys and passerines of the Atlantic rainforest Biome, southeastern Brazil. Ticks and Tick-borne Diseases, 2019; 10: 1-10'},{id:"B15",body:'Muñoz-Leal S, Martins MM, Nava S, Landulfo GA, Simons SM, Rodrigues VS, et al. Ornithodoros cerradoensis n. sp. (Acari: Argasidae), a member of the Ornithodoros talaje (Guérin-Méneville, 1849) group, parasite of rodents in the Brazilian Savannah, Ticks and Tick-borne Diseases. 2020; 11: Issue 5'},{id:"B16",body:'OnofrioVC, Guglielmone AA, BattestiDM, GianizellaSL, MarciliA, QuadrosRM, et al. Description of a new species of Ixodes (Acari: Ixodidae) and first report of Ixodes lasallei and Ixodes bocatorensis in Brazil. Ticks and Tick-borne Diseases. 2020; 11: 101423'},{id:"B17",body:'Guglielmone AA, Robbins RG, Apanaskevich DA, PetneyTN, Estrada-Peña A, Horak IG. The hard ticks of the world: (Acari: Ixodida: Ixodidae). London: Springer; 2014; 738 p'},{id:"B18",body:'Esser HJEA, Herre R, Kays YL, Jansen PA. “Local Host-Tick Coextinction in Neotropical Forest Fragments.” International Journal for Parasitology 2019; 49: 225–233'},{id:"B19",body:'Ferreira GC, Sturaro MJ, Peloso PLV. Amphibians and reptiles from Floresta Nacional de Pau-Rosa, Amazonas, Brazil: an important protected area at the heart of Amazonia. Acta Amazonica. 2017; 47: 259 – 268'},{id:"B20",body:'Luz HR, Faccini JLH. Parasitim on anurans in Brazil (in portuguese). Vet Zootec. 2013; 20: 100-111'},{id:"B21",body:'Horta MC, Saraiva DG, Oliveira GMB, Martins TF, Labruna MB. Rickettsia bellii in Amblyomma rotundatum ticks parasitizing Rhinella jimi from northeastern Brazil. Microbes Infect. 2015;17: 856–858'},{id:"B22",body:'Alcântara EP, Silva CF, Ávila RW, Pacheco RC, Martins TF, Muñoz-Leal S, et al. Ticks (Acari: Argasidae and Ixodidae) infesting amphibians and reptiles in Northeastern Brazil. Systematic and Applied Acarology. 2018; 23: 1497–1508'},{id:"B23",body:'Oda FH, Kitagawa C, Noronha JC, Rodrigues DJ, Martins TF, Valadão MC, et al. Amblyomma species infesting amphibians and reptiles in the seasonally dry Amazon forest, with new host records for Amblyomma rotundatum (Acari: Ixodida: Ixodidae). Systematic and Applied Acarology. 2018; 23: 387-392'},{id:"B24",body:'Fonseca, MS, Campanharo TB, Borges AAS, Castilho VO, Doria TB, ParanáSBM, et al. Ticks and Associated Pathogens From Rescued Wild Animals in Rainforest Fragments of Northeastern Brazil. Frontiers in Veterinary Science. 2020; 7: 177'},{id:"B25",body:'Barros-Battesti DM, Landulfo GA, Luz HR, Marcili A, Onofrio VC, Famadas KM. Ornithodoros faccinii n. sp. (Acari: Ixodida: Argasidae) parasitizing the frog Thoropa miliaris (Amphibia: Anura: Cycloramphidae) in Brazil. Parasites & Vectors 2015; 8: 268'},{id:"B26",body:'Muñoz-Leal S, Toledo LF, Venzal JM, Marcili A, Martins TF, Acosta ICL, et al. Description of a new soft tick species (Acari: Argasidae: Ornithodoros) associated with stream-breeding frogs (Anura: Cycloramphidae: Cycloramphus) in Brazil. Ticks and Tick-Borne Diseases. 2017; 8: 682-692'},{id:"B27",body:'Labruna MB, Camargo LMA, Terrassini FA, Schumaker TTS, Camargo EP, Notes on Parasitism by Amblyomma humerale (Acari: Ixodidae) in the State of Rondônia, Western Amazon, Brazil. Journal of Medical Entomology. 2002; 39: 814–817'},{id:"B28",body:'Polo G, Luz HR, Martins TF, Regolin AL, Silva HR, Winker G, et al. Distribution modeling of Amblyomma rotundatum and Amblyomma dissimile in Brazil: estimates of environmental suitability. Parasitology Research. 2020; https://doi.org/10.1007/s00436-020-06924-9s'},{id:"B29",body:'Luz HR, Silva-Santos E, Costa-Campos CE, Acosta I, Martins TF, Munhoz-Leal S, et al. Detection of Rickettsia spp. in ticks parasitizing toads (Rhinella marina) in the northern Brazilian Amazon. Experimental and Applied Acarology. 2018; 75: 309-318'},{id:"B30",body:'Martins TF, Venzal JM, Terrassini FA, Costa FB,; Marcili A, Camargo LMA, et al. New tick records from the state of Rondônia, western Amazon, Brazil. Experimental and Applied Acarology 2013; 62: 121-128'},{id:"B31",body:'Gianizella SL, Martins TF, Onofrio VC, Aguiar NO, Gravena W, Nascimento CAR, et al. Ticks (Acari: Ixodidae) of the state of Amazonas, Brazil. Experimental & Applied Acarology. 2018; 74: 177-183'},{id:"B32",body:'Witter R, Martins TF. Campos AK, Melo ALT, Correa SHR, Morgado TO, et al. Rickettsial infection in ticks (Acari: Ixodidae) of wild animals in midwestern Brazil. Ticks and Tick-borne Diseases. 2016; 7, 415–423'},{id:"B33",body:'Zimmermann NP, Aguirre AAR, Rodrigues VS, Garcia MV, Medeiros JF, Blecha IMZ, et al. Wildlife species, Ixodid fauna and new host records for ticks in an Amazon forest area, Rondônia, Brazil. Brazilian Journal Veteriany Parasitology. 2018; 27: 177-182'},{id:"B34",body:'Torres AC, Minervino AHH, Santos Júnior AP, Sarturi C, Martins TF, Vale WG, Morini AC, et al. Amblyomma ticks infesting amphibians and Squamata reptiles from the lower Amazon region, Brazil. Experimental & Applied Acarology. 2018; 75: 399–407'},{id:"B35",body:'Pedroso-Santos F, Santos ES, Sanches PR, Campos EC, Luz HR, Faccini JLH. First record of Amblyomma dissimile (Acari: Ixodidae) infesting the Granular Toad Rhinella major (Anura: Bufonidae) in the Eastern Amazon region. Herpetology Notes. 2020; 13:385-387'},{id:"B36",body:'Costa FB, Martins TF, Muñoz-Leal S, Serpa MC, OgrzewalskaM, Luz HR, et al. Retrospective and new records of ticks (Acari: Argasidae, Ixodidae) from the state of Maranhão, an Amazon-Cerrado transition area of Brazil Veterinary Plarasitology: Regional Studies and Reports. 2020; 21: 100413'},{id:"B37",body:'Ogrzewalska M, Machado CR, Forneas T, Cunha DLE, Lemos, ERS. Microorganisms in the ticks Amblyomma dissimile Koch 1844 and Amblyomma rotundatum Koch 1844 collected from snakes in Brazil. 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Ciência Rural. 2017; 47: 1-6'},{id:"B86",body:'Luz HR, Neto SFC, Weksler M, Gentile R, Faccini JLH. Ticks parasitizing wild mammals in Atlantic Forest areas in the state of Rio de Janeiro, Brazil. Brazilian Journal Veterinary Parasitology. 2018; 27:409–414'},{id:"B87",body:'Luz HR, Muñoz-Leal S, de Carvalho WD, Castro IJ, Xavier BS, Toledo JJ, et al. Detection of “Candidatus rickettsia wissemanii” in ticks parasitizing bats (Mammalia: Chiroptera) in the northern Brazilian Amazon. Parasitology Research. 2019; 118: 3185–3189'},{id:"B88",body:'Colle AC, Mendonça RFB, Maia MO, Freitas LC, Martins TF, Muñoz leal S, et al. Rickettsial survey and ticks infesting small mammals from the Amazon forest in midwestern Brazil. Systematic and Applied Acarology. 2020; 25:78–91'},{id:"B89",body:'Rosas FCW, Sicsu da Cruz TM, Gianizella SL, dos Santos Ramalheira C, Martins TF. A first record of ticks in free-ranging giant otter (Pteronura brasiliensis) in the Brazilian Amazon. 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Ectoparasitas de cães domiciliados e errantes do município de Rio Branco-Acre. Enciclopédia Biosfera. 2018; 15: 442-450'},{id:"B102",body:'Onofrio VC, Barros-Battesti DM, Labruna MB, Faccini JL. Diagnoses of and illustrated key to the species of Ixodes Latreille, 1795 (Acari: Ixodidae) from Brazil. Systematic and Applied Acarology. Parasitology. 2009; 72: 143–157'},{id:"B103",body:'Serra-Freire NM. Occurrence of ticks (Acari: Ixodidae) on human hosts, in three municipalities in the State of Pará, Brazil. Revista Brasileira de Parasitologia Veterinária. 2010; 19: 141–147'},{id:"B104",body:'Lopes LB, Guterres A, Rozental T, Carvalho de Oliveira R, Mares-Guia M, Fernandes J, et al. Rickettsia bellii, Rickettsia amblyommii, and Laguna Negra hantavirus in an Indian reserve in the Brazilian Amazon. Parasites & Vectors. 2014; 7: 191'},{id:"B105",body:'Aguirre A AR, Rodrigues VS, Costa IN, Garcia MV, Higa LOS, Medeiros JF, Andreotti R. Biological parameters of Amblyomma coelebs Neumann, 1906 (Acari: Ixodidae) under experimental conditions. Brazilian Journal Veterinary Parasitology. 2018; 27: 81-86'},{id:"B106",body:'Guglielmone AA, Beati L, Barros-Battesti DM, Labruna MB, Nava S, Venzal JM, et al. Ticks (Ixodidae) on humans in South America. Experimental & Applied Acarology. 2006; 40: 83–100'},{id:"B107",body:'Silva TKS, Blanco CM, Lemos ERS, Ogrzewalska M. Notes on parasitism and screening formicroorganism of ticks Amblyomma (Acari: Ixodidae), Amazon, Brazil. Virus Reviews & Research. 2016; 21: 41–44'},{id:"B108",body:'Aragão HB, Fonseca F. nota de ixodologia. VIII. Lista e chave para os representantes da fauna ixodológica brasileira. Memórias do Instituto Oswaldo Cruz. 1961; 59: 115–129'},{id:"B109",body:'Labruna MB, Homem VSF, Heinemann MB, Neto JSF. Ticks (Acari: Ixodidae) associated with rural dogs in Uruará, Eastern Amazon, Brazil. Journal of Medical Entomology. 2000; 37: 774–776'},{id:"B110",body:'Martins TF, Luz HR, Faccini JLH, Labruna MB. Life-cycle of Amblyomma oblongoguttatum (Acari: Ixodidae) under laboratory condition. Experimental & Applied Acarology. 2017; 71: 415–424'},{id:"B111",body:'Martins TF, Moura MM, Labruna MB. Life-cycle and host preference of Amblyomma ovale (Acari: Ixodidae) under laboratory conditions. Experimental & Applied Acarology. 2012; 56: 151–158'},{id:"B112",body:'Guglielmone AA, Robbins RG. Tick species found feeding on humans. In: Guglielmone AA, Robbins RG, editors. Hard ticks (Acari: Ixodida: Ixodidae) parasitizing humans: a global overview. 1st ed. London: Springer. 2018. 205 p'},{id:"B113",body:'Landulfo GA, Luz HR, Sampaio JS, Faccini JLH, Barros-Battesti DM. Life Cycle of Amblyomma romitii (Acari: Ixodidae) Under Laboratory Conditions. Journal of Medical Entomology. 2015; 53: 48-53'},{id:"B114",body:'Serra Freire NM, Peralta ASL, Teixeira RHF, Gazeta GS, Amorim M. Amblyomma rotundatum parasitando Homo sapiens no parque zoobotánico do MPEG e em Itaboraí. Arquivos da Sociedade de Zoológicos do Brasil. 1995; 16: 20'},{id:"B115",body:'Aguirre AAR, Rodrigues VS, Costa IN, Garcia MV, Csordas BG, Andreotti R, Medeiros JF. Amblyomma scalpturatum Neumann, 1906 (Acari: Ixodidae): confirmation in Acre State, Brazil, and description of parasitism in a human. Brazilian Journal of Veterinary Parasitology. 2019; 28: 473-478'},{id:"B116",body:'Labruna MB, Kasai N, Ferreira F, Faccini JL, Gennari SM. Seasonal dynamics of ticks (Acari: Ixodidae) on horses in the state of São Paulo Brazil. Veterinary Parasitology. 2002; 19: 65–77'},{id:"B117",body:'Labruna MB, Amaku M, Metzner JA, Pinter A, Ferreira F. Larval behavioral diapause regulates life cycle of Amblyomma cajennense (Acari: Ixodidae) in Southeast Brazil. Journal of Medical Entomology. 2003; 40: 170-178'},{id:"B118",body:'Bitencourth K, Amorim M, De Oliveira SV, Caetano, RL, Voloch CM, Gazêta GS. Amblyomma sculptum: genetic diversity and rickettsias in the Brazilian Cerrado biome. Medical and Veterinary Entomology. 2017; 3: 1-11'},{id:"B119",body:'Labruna MB, Terassini FA, Camargo LM. Notes on population dynamics of Amblyomma ticks (Acari: Ixodidae) inBrazil. Journal Parasitology. 2009; 95: 1016-8'},{id:"B120",body:'Mans BJ, Featherston J, Kvas M, Pillay K, de Klerk DG, Pienaar R, et al. Argasid and ixodid systematics: Implications for soft tick evolution and systematics, with a new argasid species list. Ticks and Tick-borne Diseases. 2019; 10: 219-240'},{id:"B121",body:'Hoogstraal H. Mint: Argasid and nuttalliellid ticks as parasites and vectors. Advances in Parasitology. 1985; 24: 135-238'},{id:"B122",body:'Labruna MB, Terassini FA, Camargo LMA, Brandão PE, Ribeiro AF, Estrada-Peña A. New reports of Antricola guglielmonei and Antricola delacruzi in Brazil, and a description of a new argasid species (Acari). Journal of Parasitology. 2008; 94: 788-792'},{id:"B123",body:'Nava S, Venzal JM, Terassini FA, Mangold AJ, Camargo LMA, Labruna MB. Description of a new argasid Tick (Acari: Ixodida) from bat caves in Brazilian Amazon. Journal of Parasitology. 2010; 96: 1089-1101'},{id:"B124",body:'Muñoz-Leal S, Terassini FA, Marcili A, Oliveira GMB, Camargo LMA, Labruna MB. A third species of Nothoaspis Keirans & Clifford, 1975 (Acari: Argasidae): Nothoaspis setosus (Kohls, Clifford & Jones, 1969) n. comb. Systematic Parasitology. 2019; 96 :595-602'},{id:"B125",body:'Muñoz-Leal S, Terassini FA, Luz HR, Fontana I, Camargo LMA, Labruna MB. First report of Ornithodoros peropteryx in Brazil, and the occurrence of Ornithodoros cavernicolous in the western Brazilian Amazon. Systematic & Applied Acarology. 2018; 23: 2113–2121'},{id:"B126",body:'Cooley RA, Kohls GM. The Argasidae of North America, Central America and Cuba, The American Midland Naturalist. Monograph N°1. 1944'},{id:"B127",body:'Labruna MB, Nava S, Terassini FA, Onofrio VC, Barros-Battesti D, et al. Description of adults and nymph, and resdescription of the larva, of Ornithodoros marinekellei (Acari: Argasidae), with data on its phylogenetic position. Journal of Parasitology. 2011; 97: 207-217'},{id:"B128",body:'Henrique-Simões M, Bernardi LFO, Ogrzewalska M, Labruna MB, Ferreira RL. New records of rare Ornithodoros (Acari: Argasidae) species in caves of the Brazilian Amazon. Persian Journal of Acarology. 2012; 1: 127-135'},{id:"B129",body:'Jones EK, Clifford CM, Keirans JE, Kohls GM. The ticks of Venezuela (Acarina: Ixodoidea) with a key to the species of Amblyomma in the Western Hemisphere. Brigham Young University Science Bulletin - Biological Series. 1972; 17: 1-40'},{id:"B130",body:'Muñoz-Leal S, Eriksson A, Santos CF, Fischer E, Almeida JC, Luz HR, Labruna MB. Ticks infesting bats (Mammalia: Chiroptera) in the Brazilian Pantanal. Experimental & Applied Acarology. 2016; 69: 73-85'},{id:"B131",body:'Muñoz-Leal S, Barbier E, Soares FAM, Bernard E, Labruna MB, Dantas-Torres F. New records of ticks infesting bats in Brazil, with observations on the first nymphal stage of Ornithodoros hasei. Experimental & Applied Acarology. 2018; 76: 537-549'},{id:"B132",body:'Luz HR, Muñoz-Leal S, Almeida JC, Faccini LH, Labruna MB. Ticks parasitizing bats (Mammalia: Chiroptera) in the Caatinga Biome, Brazil. Brazilian Journal Veterinary Parasitology. 2018; 35: 484-491'},{id:"B133",body:'Kohls GM, Clifford CM, Jones EK. The systematics of the subfamily Ornithodorinae (Acarina: Argasidae). IV. Eight new species of Ornithodoros from the Western Hemisphere. Annals of the Entomological Society of America. 1969; 62: 1035–1043'},{id:"B134",body:'Guzmán-Cornejo C, Herrera-Mares A, Robbins RG, Rebollo-Hernández A. The soft ticks (Parasitiformes: Ixodida: Argasidae) of Mexico: species, hosts, and geographical distribution. Zootaxa. 2019; 4623: 485-525'},{id:"B135",body:'De La Cruz J. Mint: Bioecologia de las grutas de calor. Mundos Subterraneos, UMAE, Mexico, DF. 1992; 3: 7-21'},{id:"B136",body:'Ribeiro JMC, Labruna MB, Mans BJ, Marumaya SR, Francischetti IMB, Barizon GC, Santos IKFM. The sialotranscriptome of Antricola delacruzi female ticks is compatible with non-hematophagous behavior and an alternative source of food. Insect Biochemistry Molecular Biology. 2012; 42: 332-342'},{id:"B137",body:'Estrada-Peña A, Venzal JM, Barros-Battesti DM, Onofrio VC, Trajano E, Firmino JVL. Three new species of Antricola (Acari: Argasidae) from Brazil, with a key to the known species in the genus. Journal of Parasitology. 2004; 90: 490-498'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Hermes R. Luz",address:"hermesluz@globomail.com",affiliation:'
Faculdade Florence, Brazil
Programa de Pós-graduação em Biotecnologia (RENORBIO), Universidade Federal do Maranhão – UFMA, Brazil
'},{corresp:null,contributorFullName:"Thiago F. Martins",address:null,affiliation:'
Departamento Medicina Veterinária Preventiva e Saúde Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, Brazil
Departamento de Laboratórios Especializados, Superintendência de Controle de Endemias, Secretaria de Estado da Saúde de São Paulo, Brazil
Departamento de Patología y Medicina Preventiva, Facultad de Ciencias Veterinarias, Universidad de Concepción, Chile
'},{corresp:null,contributorFullName:"Francisco B. Costa",address:null,affiliation:'
Departamento de Patologia, Curso de Medicina Veterinária, Universidade Estadual do Maranhão, Brazil
'},{corresp:null,contributorFullName:"Sérgio L. Gianizella",address:null,affiliation:'
Laboratório de Zoologia, Departamento de Biologia, Instituto de Ciências Biológicas, Universidade Federal do Amazonas, Brazil
'},{corresp:null,contributorFullName:"João Luiz H. Faccini",address:null,affiliation:'
Departamento de Parasitologia Animal, Universidade Federal Rural do Rio de Janeiro, Brazil
'},{corresp:null,contributorFullName:"Marcelo B. Labruna",address:null,affiliation:'
Departamento Medicina Veterinária Preventiva e Saúde Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, Brazil
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1. Introduction
Bayesian networks (BNs) allow a tractable graph-based representation for probabilistic reasoning (or inference), under uncertainty, about a given problem or domain. A recurrent problem in robotics is to reason about the class of an object in the environment, given evidence (from sensors, e.g. RGB-D cameras), and probabilistic models (e.g. probability outputs of a classifier) in the domain that represents the problem. For example, a robot would be needed to detect and then recognise a particular type of object (such as a mug) in a given place (e.g. kitchen) [1]. Another example would be an autonomous vehicle that has to detect road users; hence, the object categories of interest would be pedestrian, cyclist, car and van, bus and truck, and motorised two-wheelers.
The topology, or structure, of a BN graph is the first step in solving the problem, and it should provide the relationship (dependencies represented by links) among the nodes (variables in the problem domain). The next step is to define the conditional probabilities for the nodes and, then, the joint probability of the BN has to be considered in order to allow computing the posterior probability of the form PClassEvidences, i.e. a posteriori of the class, or category, given the evidences from a set of sensor-based models [1].
In this chapter, we will address BN with similar topologies to the one illustrated in Figure 1. The structure shown in Figure 1 is a ‘common effect’ chain [2], which means that all parent nodes contribute to the node C designated by the ‘class’. The node C is the label variable and takes values such as: C = {person, non-person}, or C = {1, 0}, or in multiple class case, C = {mug, spoon, knife, fork, plate, can} or C = {concentrated, relaxed, neutral}. The evidence nodes, as illustrated in Figure 1, provide probability values per class of interest; thus, such nodes are modelled by a classifier (e.g. convolutional neural network [CNN], SVM, and Bayes classifier). The node called ‘context’ might represent evidence from the environment, or information shared by the infrastructure (e.g. cameras mounted on the scenario), or any other evidence not directly related to a given learning classifier using data/features from sensors onboard the robot.
Figure 1.
Topology of a BN where all the parent nodes {X1, X2, …, Xn} contribute to a common effect, which is the set of classes (node C) of interest in a given robotic domain.
The remainder of this chapter is organised as follows: Section 2 briefly describes the use of BNs for supervised classification problems. Use cases on object manipulation, pedestrian classification, and EEG-based Mental State Classification are described in Sections 3–5, respectively. Finally, Section 6 presents a summary and remarks.
2. Bayesian networks for supervised classification
In a more general and high-level perspective, a BN is characterised by nodes that represent a finite set of random variables, i.e. a variable/function whose outputs outcome from a random measured process (belonging to the domain of interest) and links (i.e. directed arcs) that represent the direct dependencies between the nodes. Hereafter, the link dependencies will assume the form of conditional probabilities. By examining Figure 1, we can see that each node Xi,i=1,…,n, is conditionally independent of all the nodes, while the node C is conditionally dependent of all its parent nodes X1,X2,…,Xn. This is a simple BN structure where the nodes represent learning model—in the form of supervised classifiers. On the other hand, which is common in some classification problems, the nodes may represent features as extracted from observed data.
Let PXC be the outcome of a learning classifier given the observed/measured sensor data. The variable X can represent a learned model, using a probabilistic classifier, based on supervised and measured data from a camera, a LIDAR, an RGB-D sensor, or a combination of multimodality data. We could represent the conditional probability as PXθC to explicitly show that the output also depends on a learning model (here represented by θ).
In a nutshell and considering the use cases described in the sequel, BNs are used to express the joint probability of events (represented by the nodes) that model a classification system where the relationships between events are expressed by conditional probabilities. Given the observations/measurements (evidence) and prior knowledge, statistical inference is accomplished using the Bayes\' theorem. The goal is to calculate the posterior PCXi of the set of classes given the evidential nodes Xi,i=1,…,n. So, inference in supervised classification applications aims to estimate the probability of the classes given the class-conditional probabilities, priors and observations.
In this work, in one of the approaches presented, we consider BN structures where the sensory data are transformed to a feature space which is then feed into a trained classifier. The classifier is assumed to output a class-conditional probability which is then used to calculate the a posteriori. When multiple sensors are considered, the conditional independency property between sensors will be satisfied, for example: PXsensor1Xsensor2Xsensor3=PXsensor1. The following sections will present three different study cases where BN are employed as a supervised classifier.
3. Use case in object shape representation through in-hand exploration
Accurate modeling of the world (environment and its components) is important in autonomous robotics applications. More precisely, for grasping applications dealing with objects used in everyday tasks, the object information (intrinsic and extrinsic) acquired before the robot executes a task is crucial for grasp strategies. The object geometry (size and shape) plays an important role in such applications, where its representation is also valuable for classification into a class of known objects and also for identification of regions on the object surface proper for a stable grasp. Since the robotic end-effector usually relies on the knowledge of object geometry to plan or to estimate grasp candidates, the more accurate the geometry of the object, the higher is the likelihood of success when estimating the candidate’s grasp for that object. Many techniques can be used to reconstruct and represent an object using different sensors, such as vision-based systems, laser range finders, etc., where the most common is through visual information.
Mapping techniques such as occupancy grid [3, 4] have been used in robotics to describe the environment of mobile robots. Two-dimensional grids have been used for static indoor mapping as shown in [5]. The idea is to estimate the probability of each cell to be occupied or empty after the sensors’ observation. Probabilistic volumetric maps are also useful in robotics by providing means of integrating different occupancy belief maps in order to update a central multimodal map using Bayesian filtering. A grid divides the workspace into equally sized voxels, and the edges are aligned with one of the axes of a reference coordinate frame. The coverage of each voxel given the sequence of batches of measurements is modelled through a probability density function. The probabilistic approach for building volumetric maps of unknown environments can also be based on information theory. Each sensor (e.g. vision, laser, etc.) can adopt an entropy gradient-based exploration strategy to define the occupied regions (most explored) in the map.
Object in-hand exploration is the procedure of exploring the shape of objects using tactile information and fingers motion around the object surface to reconstruct its shape [6]. In order to acquire the probabilistic representation of an object using a volumetric map, it is necessary to have an a priori estimation of the area, where the object is placed for mapping. There are two scenarios in which in-hand exploration can be applied: a static object placed at a specific location or an object being explored in-hand in constant motion (dynamic exploration with moving object). The sensors used for this task is a cyberglove that measures fingers flexure (0–255 range), with six electromagnetic motion sensors (Polhemus sensors), where each sensor provides 6D information (x, y, z, yaw, pitch, and roll), and tactile sensors in each fingertip and palm (Tekscan pressure sensor) that measure the force (0–255 range). Figure 2 depicts the experimental setup and sensors used for object in-hand exploration.
Figure 2.
Experimental setup: (a) workspace for mapping (grid 35 cm × 35 cm × 35 cm equally divided, where each voxel is sized with 0.5 cm); (b) Polhemus Liberty Motion Tracking System: magnetic sensors attached to the cyberglove (fingertips and back of the hand).
When the object exploration is in-hand and the object is moving, then it is needed to perform a registration to map the object displacements into a single frame of reference. We can consider that, for every motion of the object, a local map is built, so that all local maps should be integrated into a global map to have the whole representation of the object shape exploration in the same frame of reference. Knowing the object initial position and the object displacements, we can compute the transformations to have all points in the same frame of reference. Given that the sensor attached to the object has six DoF (x, y, z, yaw, pitch, and roll), we can compute the rotation and translation of the object. We compute the rotation matrix of the object in a specific point in time using α = yaw (rotation in z axis), β = pitch (rotation in y), and φ = roll (rotation in x).
To map the point cloud in the same frame of reference, for all points, we find the translation of the fingertip sensor to the object sensor and then we apply the rotation to that point, p′ = Rot, where p′ is the new position of the 3D point that we are mapping to the same frame of reference of the object sensor; Ro is the rotation matrix 3 × 3 of the object sensor; and t the translation of the fingertip sensor to the object sensor.
The Bayesian volumetric map [6] is an occupancy grid, i.e. discrete random fields, wherein each cell has an assigned value, which represents the probability of the cell being occupied. The dimensions of the voxels define the spatial resolution of the representation. The edges of the grid are aligned with one of the axes of the world frame of reference W. In this work, the map is a 3D grid comprised of a set of cells c ∈ M, denoted as voxels, wherein each voxel is a cube with edge ε ∈ R. The voxels divide the workspace into equally sized cubes with volume ε3. The occupancy of each individual voxel is assumed to be independent from the other voxels occupancy, and thus, Oc is a set of independent random variables as follows:
c ∈ M: Index a cell on the Map;
Oc ∈ [0, 1]: Probability describing if the cell c is empty or occupied;
Zc: Measurement that influences the cell c. It represents the measurements acquired from five sensors, each one returns the 3D location of each finger movement in the map;
P(Oc): Probability distribution of preliminary knowledge describing the occupancy of the cell c, initially as a uniform distribution (0.5 for each state: empty or occupied); and
P(Zc|Oc): Probability density function corresponding to the set of measurements that influences the cell c taken from the in-hand exploration measurements. This distribution is computed from the in-hand exploration sensor model.
The knowledge about the occupancy of a voxel c in the map M, after Z measurements received at time t from the sensors, is represented by the probability density function P(Oc|Zct). Updating the 3D probabilistic representation of the manipulated object shape upon a new measurement Zt means updating the probability distribution function P([Oc = 1]|Zct) of the voxel c influenced by the measurement Z at time t. Voxels are influenced by a measurement Zt if the location associated with the sample computed from the sensor model P (Zct|[Oc = 1]) is contained in that voxel location c. For each voxel c, the set of measurements Zct contains n measurements Zc influencing a voxel c along the time t. The probability density function of the object shape representation of voxel c given the Zc measurements influencing such voxel is represented by P(Zct |[Oc = 1]). To update the occupancy estimation of a cell in the map, the Bayes rule is applied:
where P([Oc = 0]) = 1 − P([Oc = 1]); P(Zct|[Oc = 1]) is given by the probability density function computed from the sensor model and P(Zct|[Oc = 0]) is a uniform distribution.
Assuming that consecutive measurements Zt are independent given the cell occupancy, the following expression is obtained:
POc=1Zct=β×POc∏t=1TPZctOc=1,E2
where β is a constant representing a normalization, factor ensuring that the left side of the equation sums up to one over all Oc.
The cells occupancy in the map are probabilities that are updated over time as long as the sensors measurements are active. At the end of the in-hand exploration of the object, the cells are allowed to represent only two states: occupied or empty, Oc ∈ [0, 1], so that a threshold is used for each cell to consider one of the two states:
Oc=0PZct<0.51POcZct≥0.5.E3
Figure 3 shows an example of the probabilistic volumetric map and its utility. The map can be used to represent the full model of the object as well as partial volume of the object and contact.
Figure 3.
Examples of the Bayesian volumetric map. Left image: real object; middle image: partial volume of the object obtained during in-hand exploration; right image: map of the full object model and contact points overlaid on the object surface (red voxels representing the contact points and blue voxel representing the centroid of the object to define its frame of reference).
Each magnetic sensor attached to the fingertips returns the 3D coordinates of the finger location based on the sensor frame of reference (source/emitter of the Polhemus Liberty tracking system). The frame rate of each sensor was defined to be up to 15 Hz. During data acquisition, a workspace (35 cm3) is defined in the experimental area for mapping. The grid space is divided into equally sized voxels (also denoted as cells) of 0.5 cm3. Due to the size of each cell, relative to the standard deviation of the magnetic tracking sensors measurements (up to 3 mm), inside each cell a 3D isotropic Gaussian probability distribution is defined, P(Zct|Oc), centred at the cell central point with the standard deviation 0.3 cm and mean value equal to the central point coordinates of the cell. In other words, this means that the model attempts to ensure that, upon receiving a measurement from the sensor attached to the fingertip, the closer the finger position is to the centre of a specific cell of the map, the more probable that cell is occupied. Furthermore, during the object surface exploration, the more often that the finger passes through that cell, the cell probability is updated with higher certainty in which that given point position actually belongs to the object surface. The probability that a measurement belongs to a cell is given by a normal distribution using the known sensor position error as the standard deviation and the sensors positions relative to the centre of each cell in the map as follows:
POc=12Π3/2Σ1/2e−12x−μTΣ−1x−μ,E4
where P(Zct|Oc) represents the probability distribution of the sensor measurement given a specific cell Oc; |Σ| represents the determinant of Σ (sensor noise variation). It can also represent a scalar value. After normalization, it takes the form:
POc=1=exp−x−ux2+x−uy2+x−uz22σ2,E5
where (x, y, z) are the coordinates of the 3D point on the object surface, and u is the central coordinate of the cell (for each axis). The in-hand exploration of objects can be performed by using the thumb and other fingers, i.e. the occupancy grid can be influenced by them over time, thus, expanding on the model for cell update, the contribution of the sensor on each finger through time can be made explicit on the decomposition as follows:
where T represents the current time instant and N = 4, the remaining four fingers of the hand. This process for updating the cell over time recursively (i.e. initially using the cell probability as a uniform distribution: empty or occupied, and later the cell probability—updated with the Bayes rule—is used as prior for the next update), represents a Bayesian network.
The BN representation of the formalism applied to the decomposition of the joint distribution in which the sensor model was used is shown in Figure 4. The plate notation relies on assumptions of duplicated subgraph as many times as the associated repetition number (in this particular case the hand fingers); the variables in the subgraph are indexed according to the repetition number; the links that cross a plate boundary are replicated for each subgraph repetition; the distributions are in the joint distribution as an indexed product of the sequence of variables. Bayesian formalisms for probabilistic model construction and some BN examples of occupancy grid model can also be seen in [6, 7].
Figure 4.
BN for object representation by in-hand exploration using occupancy grid. The left image shows the labels: prior, posterior, and respective distributions, yet not necessary in dynamic BN representations. The variables are defined in terms of their notation and conditional dependence. The instantiation is defined with their parameters and the random variables that support the model are fully described (i.e. their significance and measurable space). The right image shows the plate notation applied to the BN formalism to represent the in-hand exploration of objects, making explicit the contribution of the sensors over time.
Figures 5 and 6 shows different household objects explored in-hand for shape retrieval.
Figure 5.
Object representation using the probabilistic volumetric map: sponge and its computed map.
Figure 6.
Object shape representation by in-hand exploration of a spray bottle. The first image (left to right) is the raw data (point cloud), next three images are different views of the voxels representation of the object shape, and the last image is the occupancy representation of the cells, the darkest ones represent the lower probabilities (less explored regions).
4. Use case in pedestrian classification
A pedestrian detection system is one of the key components in Advanced Driver Assistance Systems (ADAS) and also in autonomous driving vehicles. Recently, pedestrian detection has regained particular attention from academia, automotive industry, and society [8]. In this chapter, pedestrian classification is studied based on a multimodal Bayesian network, where the BN’s structure has a node representing the binary class (pedestrian and nonpedestrian) and the parent nodes are represented by machine learning models in the form of supervised classifiers. In terms of sensory data, we will consider a LIDAR sensor as an intermodality technology, which provides range (distance) and reflectance (intensity return). In order to study multimodality between two sensor technologies, a colour (RGB) camera is also considered in the BN. The classifiers are modelled by a deep convolutional neural network (CNN). Data from a LIDAR enter into the CNN classifier in the form of high-resolution distance/depth (DM) and reflectance maps (RMs). Distance and intensity (reflectance) raw data from the LIDAR are transformed to high-resolution (dense) maps as described in [9, 10].
A multimodal BN is then used to combine the likelihoods from CNN-classifiers learned using data from a LIDAR (based on DM and RM) and from a camera. Pedestrian recognition is evaluated on a ‘binary classification’ dataset created from the KITTI Vision Benchmark Suite, which provides data from a colour camera and from a Velodyne HDL-64E LIDAR. The performance results using the BN are compared with the CNNs having a single modality as input, and against nonlearning rules, namely: minimum, maximum, and average.
We will formulate the classification problem in such a way that the class node (C) of the BN is inferred from the classification nodes (XRGB,XDM,XRM); therefore, the ‘full’ joint distribution is expressed by:
PCXRGBXDMXRM=PCPXRGBCPXDMXRGBCPXRMXDMXRGBC,E7
assuming each classifier node contributes independently to explain C and also assuming the classifiers are independent of each other but not independent of the class so, e.g. PXDM|XRGB,C=P(XDM|C), we can express the class-conditional a posteriori as:
PCXRGBXDMXRM∼PCPXRGBCPXDMCPXRMC.E8
We will consider the class a-priori probability to be uniform and equally distributed; thus, the probability of being pedestrian or nonpedestrian (PC) can be dropped out from the equation above. Therefore, the inference problem resumes to a product of the outputs probabilities from the CNN models.
To evaluate the multimodal BN described here, a pedestrian classification dataset was created based on the 2D object-detection dataset of KITTI. The labelled classes are given in the form of 2D bounding box tracklets: ‘Pedestrian’, ‘Car’, ‘Truck’, ‘Tram’, ‘Van’, ‘Person (sitting)’, ‘Cyclist’ and ‘Misc’. The classes were separated in two categories of interest: pedestrian and nonpedestrian, i.e. a binary problem. The number of positives examples is 4487 cropped images (labelled bounding boxes of type ‘Pedestrian’), while the negative class has 47,378 cropped images (types: ‘Cyclist’. ‘Car’, ‘Person (sitting)’ and so on). It was considered 70% for the training set (10% of that for validation) and the remaining 30% for the testing set. Table 1 gives a summary of the dataset used in this use case.
Summary of dataset for pedestrian classification
Training set
n# positives = 2827 n# negatives = 29,849
Validation set
n# positives = 314 n# negatives = 3316
Testing set
n# positives = 1346 n# negatives = 14,213
Table 1.
Pedestrian dataset.
Among several convolutional neural networks, we opted to use AlexNet CNN architecture with batch normalization in the first two layers and the last layer, the softmax activation function with two classes and dropout of 50%. The network was trained from scratch for the pedestrian and nonpedestrian classes [10]. Through the bounding boxes provided by the KITTI dataset, we cropped the objects contained in the depth and reflectance maps images. All objects were resized to the size of 227 × 227 because this is the network input size. The network was trained with the following parameter settings: 30 epochs, batch size equal 64, stochastic gradient descent optimizer with lr = 0:001 (learning rate), decay = 10 − 6 (learning rate decay over each update), momentum = 0.9, and categorical cross-entropy as loss function.
Denoting PXiC the confidence (i.e. the class-conditional probability) yielded by deep models CNNi (i = 1, …, n), where n is the number of models, CNN1 and CNN2 denote CNN models learned from DM and RM (reflectance), respectively, while CNN3 denotes a model using RGB data. Three nonlearning fusion rules are considered: average (AVE), maximum (MAX), and minimum (MIN). The average rule calculates the simple mean of the CNN-classifiers outputs F-ave =1n∑i=1nPXiC. The maximum rule outputs the maximum value over the classifier responses, F-max = maxPXiC, while the minimum rule is F-min =minPXiC.
The pedestrian classification results are reported using Precision (Pre), Recall (Rec), and F-score (F1) performance measures, allowing a more detailed and accurate analysis of the results. The F-scores values were obtained considering a threshold of 0.5. A number of pedestrian and nonpedestrian examples are unbalanced, as shown in Table 1; thus, F-score is here considered because it is a suitable performance measure for unbalanced cases. The results obtained using the BN and the rules AVE, MAX, and MIN are shown in Figure 7.
Figure 7.
Classification performance, in terms of Pre, Rec, and F-1, considering a multimodal BN in comparison with deterministic rules (Min, Max, Average).
Results show that decision rules like minimum and maximum tend to have poor results, in terms of F-score, compared to the average rule and the multimodal BN. However, the values of Precision and Recall (or True Positive rate) are very high for Min and Max, respectively. The Average and the BN achieved close classification performance in all measures, although the BN’s results were slightly better.
5. Use case in EEG-based mental states classification
AI-enabled wearable technology has the ability to enhance the capabilities of today’s user-centred devices and analytics toward promoting humans’ quality of life and enabling an improved health care by monitoring humans’ complex bio-signals, reducing risks, detecting anomalous situations, thus, optimising standards of care. A good example is the EEG-based brain-controlled devices that can serve as powerful aids for severely disabled people in their daily life, especially to help them to move voluntarily. The EEG-based brain-machine interfaces are one of the many alternatives that can be used to interact with devices using the superficial brain activity signals. These signals, called electroencephalograms or EEG for short, convey information regarding the voltage measured by electrodes (dry or wet) placed around the scalp of an individual. Recently, new applications for restoring function to those with motor impairments using EEG-based brain machine interfaces for conveying messages and commands to devices such as robot arm, wheelchair, and any other devices using bio-signals have been developed. A good example where EEG is employed is to detect mental states. The ability to autonomously detect mental states, whether cognitive or affective, is useful for multiple purposes in many domains such as robotics, health care, education, neuroscience, etc. The importance of efficient human-machine interaction mechanisms increases with the number of real life scenarios where smart devices, including autonomous robots, can be applied. One of the many alternatives that can be used to interact with machines is through superficial brain activity signals. A major challenge in brain-machine interface applications is inferring how momentary mental states are mapped into a particular pattern of brain activity. One of the main issues of classifying EEG signals is the amount of data needed to properly describe the different states, since the signals are complex. The signals are considered stationary only within short intervals, that is, why the best practice is to apply short-time windowing technique in order to detect local discriminative features to meet this requirement.
This section presents how Bayesian inference can be used to classify mental states. The framework consists of (i) statistical and temporal features extraction using time window technique, (ii) attributes selection to keep only the relevant information from the signals, and (iii) Bayesian classification technique to categorise multiple mental states (e.g. relaxed, neutral, and highly concentrated).
5.1. Data acquisition
The sensor Muse Headband was used for data collection. The Muse is a commercial EEG sensing device with five dry-application sensors, one used as a reference point (NZ, at the centre of the forehead) and four (at points TP9, AF7, AF8, TP10, i.e. around the forehead Figure 8) to record brain wave activity. To prevent the interference of electromyographic signals, nonverbal tasks that required little to no movement were set. Blinking, though providing interference to the AF7 and AF8 sensors, was neither encouraged nor discouraged to retain a natural state. This was due to the dynamicity of blink rate being linked to tasks requiring differing levels of concentration, and as such, the classification algorithms would take these patterns of signal spikes into account. In addition, subjects were asked not to close their eyes during any of the tasks. Three stimuli were devised to cover the three mental states available from the Muse Headband—relaxed, neutral, and concentrating. A dataset was created after five participants performing the three mental states, where each session lasted 1 minute. The relaxed task had the subjects listening to low-tempo music and sound effects designed to aid in meditation while being instructed on relaxing their muscles and resting. For a neutral mental, a similar test was carried out, but with no stimulus at all, this test was carried out prior to any others to prevent lasting effects of a relaxed or concentrative mental state. Finally, for concentration, the subjects were instructed to follow the ‘shell game’ in which a ball was hidden under one of the three cups, which were then switched, the task was to try and follow which cup hid the ball. After a short amount of time into the stimulus starting, as to not gather data with an inaccurate class, the EEG data from the Muse Headband were automatically recorded for 60 seconds. The data were observed to be streaming at a variable frequency within the range of 150–270 Hz.
Figure 8.
The International 10-20 EEG electrode placement standard [11]. The sensors of the Muse Headband are denoted in yellow. The NZ placement (green) is used as a reference for calibration.
5.2. Feature extraction
Feature extraction and classification of EEG signals are primary goals in brain–computer interface (BCI) applications. One challenging problem when it comes to EEG feature extraction is the complexity of the signal. Nonstationary signals can be observed during the change in alertness and wakefulness, during eye blinking, and also during transitions of mental states. Discriminative features rely on statistical techniques such as mean, standard deviation, autocorrelation, statistical moments of third and fourth order (skewness and kurtosis to measure the asymmetry of the data and also the peakedness of the probability distribution of the data), time-frequency based on fast Fourier transform (FFT), Shannon entropy, max-min features in temporal sequences, log-covariance given a set of statistical data, and derivatives of the features from different time instants. These features are computed in terms of the temporal distribution of the signal in a time window of 1 second, with overlap of half second between the sliding windows. Details about the modeling and implementation of the features can be found in [12]. Another important point to compute the features is the signals from the EEG Muse headband. Since it returns five types of signal frequencies (alpha, beta, theta, delta, and gamma), then, we compute all set of features for each signal. The aforementioned set of features for all signals are around 2100 feature values. In order to reduce and optimise the classification performance, feature selection is needed.
5.3. Feature selection
There are various well-known algorithms for features selection in the state of the art. These types of algorithms aim at reducing the number of attributes present in a dataset while retaining a model’s predictive accuracy. The following algorithms were used to compare the accuracy performance when used with a Naïve Bayes classifier (NB) and a Bayesian Network (BN): (i) OneR calculates error rate of each prediction based on one rule and selects the lowest risk classification [13]; (ii) Information Gain assigns a worth to each individual attribute by measuring the information gain with respect to the class (difference of entropy) [14]; and (iii) Evolutionary Algorithm creates a population of attribute subsets and ranks their effectiveness with a fitness function to measure their predictive ability of the class [15]. At each generation, solutions are bred to create offspring, and weakest solutions are killed off in a tournament of fitness.
5.4. Classification
Two models were trained on Bayes\' theorem, a formula of conditional probability based on hypothesis H and evidence E. The theorem states that the probability of the hypothesis being true before evidence P(H) is related to the probability of the hypothesis after reading the evidence P(H|E) and is given as follows: PH|E=PE|HPH∑jPE|HPH . A simplistic Naive Bayes model has been used, which has a non-cosideration of the relationships between the features models. It uses the maximum a posteriori decision rule ŷ=argmaxk∈1,…,KPCk∏i=1nPxi|Ck. A BN (Bayes Net) model was also trained. This method generates a probabilistic graphical model via representing probabilities of variables to classes on a directed acyclic graph (DAG) as follows: PCt−1:t−T|Xt:t−T=1β∏k=tT−tPXk|CkPCk. The goal is to infer the current time value of Ct given the data Xt:t–T = {Xt, Xt−1, …, Xt–T} and the prior knowledge of the class, which is attained by the a-posteriori probability P(Ct|Ct−1:t–T, Xt:t–T). The superscript notation denotes the set of values over a time interval.
5.5. Experimental results
The five generated sets from the original dataset classified by NB and BN are shown in Table 1. The most effective model for this EEG dataset using Bayesian inference was the BN along with the OneR Attribute Selector, which had a high accuracy of 73.67% using around 2% of the total of features extracted when classifying the data into one of the three mental states. For each test, 10-fold cross-validation was used to train the model. The lowest performance is 54.2% (Information Gain dataset with a NB classifier). It is reasonable to assume that the naivety in not considering attribute relationships has led to poorer results. These preliminary results show that a BN can be considered for EEG data classification. However, other methods of classification can achieve better performance with the same set of features. In order to improve the performance, we can adopt the strategy of fusion of multiple classifiers using the Bayes\' theorem for fusion as shown in [1, 16] Table 2 presents the result of Bayesian inference combined with feature selection algorithms. Better results are attained when using OneR algorithm for features selection followed by classification via Bayesian networks.
Dataset
Accuracy %
Naive Bayes
Bayesian network
Number of selected features (%)
OneR
56.30
73.67
44 (2.05)
Information gain
54.20
71.64
31 (1.44)
Evolutionary algorithm
55.04
70.31
99 (4.61)
Table 2.
Accuracy of trained models.
6. Summary
Approaches based on Bayesian network (BN) have been described considering three case studies: Bayesian volumetric map for object perception, pedestrian classification for autonomous-vehicles perception and for EEG-based mental states classification. BNs were formulated and applied in supervised pattern classification problems. In all cases, the BNs assumed conditional independence between sensors’ modalities or feature models.
In summary, this chapter has addressed BN with examples, where other machine learning techniques were employed and combined with BN to sensory perception in applications related to robotics (multimodal sensor fusion for object detection), advanced driver assistance systems for autonomous driving systems, and EEG-based mental states classification, which can be used to control devices (e.g. robots) or in health-related areas for mental health monitoring.
Acknowledgments
This work has been partially supported by the MICINN Project TIN2015-65686-C5-5-R, by the Extremaduran Government project GR15120, by the FEDER project 0043-EUROAGE-4-E (Interreg V-A Portugal-Spain - POCTEP), and by Fundação Araucária (CONFAP Brazil) with a mobility grant to Dr Diego R. Faria and Professor Eduardo P. Ribeiro to coordinate the project “Stepping-stones to transhumanism: merging EEG-EMG data to control a low-cost prosthetic hand”.
\n',keywords:"Bayesian networks, machine learning, multimodal robotic perception",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/64183.pdf",chapterXML:"https://mts.intechopen.com/source/xml/64183.xml",downloadPdfUrl:"/chapter/pdf-download/64183",previewPdfUrl:"/chapter/pdf-preview/64183",totalDownloads:1624,totalViews:0,totalCrossrefCites:0,dateSubmitted:"May 3rd 2018",dateReviewed:"August 23rd 2018",datePrePublished:"November 5th 2018",datePublished:"November 6th 2019",dateFinished:"October 26th 2018",readingETA:"0",abstract:"In order to make machines perceive their external environment coherently, multiple sources of sensory information derived from several different modalities can be used (e.g. cameras, LIDAR, stereo, RGB-D, and radars). All these different sources of information can be efficiently merged to form a robust perception of the environment. Some of the mechanisms that underlie this merging of the sensor information are highlighted in this chapter, showing that depending on the type of information, different combination and integration strategies can be used and that prior knowledge are often required for interpreting the sensory signals efficiently. The notion that perception involves Bayesian inference is an increasingly popular position taken by a considerable number of researchers. Bayesian models have provided insights into many perceptual phenomena, showing that they are a valid approach to deal with real-world uncertainties and for robust classification, including classification in time-dependent problems. This chapter addresses the use of Bayesian networks applied to sensory perception in the following areas: mobile robotics, autonomous driving systems, advanced driver assistance systems, sensor fusion for object detection, and EEG-based mental states classification.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/64183",risUrl:"/chapter/ris/64183",signatures:"Diego R. Faria, Cristiano Premebida, Luis J. Manso, Eduardo P. Ribeiro and Pedro Núñez",book:{id:"7372",type:"book",title:"Bayesian Networks",subtitle:"Advances and Novel Applications",fullTitle:"Bayesian Networks - Advances and Novel Applications",slug:"bayesian-networks-advances-and-novel-applications",publishedDate:"November 6th 2019",bookSignature:"Douglas McNair",coverURL:"https://cdn.intechopen.com/books/images_new/7372.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83962-323-3",printIsbn:"978-1-83962-322-6",pdfIsbn:"978-1-83962-324-0",isAvailableForWebshopOrdering:!0,editors:[{id:"219757",title:"Dr.",name:"Douglas",middleName:null,surname:"McNair",slug:"douglas-mcnair",fullName:"Douglas McNair"}],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. Bayesian networks for supervised classification",level:"1"},{id:"sec_3",title:"3. Use case in object shape representation through in-hand exploration",level:"1"},{id:"sec_4",title:"4. Use case in pedestrian classification",level:"1"},{id:"sec_5",title:"5. Use case in EEG-based mental states classification",level:"1"},{id:"sec_5_2",title:"5.1. Data acquisition",level:"2"},{id:"sec_6_2",title:"5.2. Feature extraction",level:"2"},{id:"sec_7_2",title:"5.3. Feature selection",level:"2"},{id:"sec_8_2",title:"5.4. Classification",level:"2"},{id:"sec_9_2",title:"5.5. Experimental results",level:"2"},{id:"sec_11",title:"6. Summary",level:"1"},{id:"sec_12",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Premebida C, Faria DR, Nunes UJ. Dynamic Bayesian network for semantic place classification in mobile robotics. In: Autonomous Robots (AURO). Springer; 2017;41(5):1161-1172'},{id:"B2",body:'Korb KB, Nicholson AE. Bayesian Artificial Intelligence. 2nd ed. Boca Raton, FL, USA: CRC Press, Inc.; 2010'},{id:"B3",body:'Moravec HP. Sensor fusion in certainty grids for mobile robots. AI Magazine. 1988;9(2):61-74'},{id:"B4",body:'Elfes A. Using occupancy grids for mobile robot perception and navigation. IEEE Computer. 1989;22:46-57'},{id:"B5",body:'Thrun S, Burgard W, Fox D. Probabilistic robotics. In: Arkin RC, editor. MIT press; 2005. ISBN 9780262332750'},{id:"B6",body:'Faria DR. Probabilistic learning of human manipulation of objects towards autonomous robotic grasping [PhD thesis]. Portugal: Department of Electrical and Computer Engineering, University of Coimbra; 2014'},{id:"B7",body:'Faria DR, Martins R, Lobo J, Dias J. Probabilistic representation of 3D object shape by in-hand exploration. IEEE/RSJ International Conference on Intelligent Robots and Systems; 2010'},{id:"B8",body:'Ross PE. Uber robocar kills pedestrian, despite presence of safety driver. In: IEEE Spectrum. Available from: https://spectrum.ieee.org [Accessed: June 2018]'},{id:"B9",body:'Premebida C, Garrote L, Asvadi A, Pedro Ribeiro A, Nunes U. High-resolution LIDAR-based depth mapping using bilateral filter. IEEE International Conference on Intelligent Transportation Systems ITSC; 2016'},{id:"B10",body:'Melotti G, Premebida C, Goncalves N, Nunes U, Faria DR. Multimodal CNN pedestrian classification: A study on combining Lidar and camera data. 21th IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018'},{id:"B11",body:'Klem GH, Lüders HO, Jasper HH, Elger C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology. Supplement. 1999;52:3-6'},{id:"B12",body:'Bird JJ, Manso LJ, Ribeiro EP, Ekart A, Faria DR. A study on mental state classification using EEG-based brain-machine interface. In: 9th IEEE International Conference on Intelligent Systems; 2018'},{id:"B13",body:'University of Waikato. OneR [online] Weka.sourceforge.net. Available from: http://weka.sourceforge.net/doc.dev/weka/classifiers/rules/OneR.html [Accessed: August 2018]'},{id:"B14",body:'University of Waikato. InfoGainAttributeEval [online] Weka.sourceforge.net. Available from: http://weka.sourceforge.net/doc.dev/weka/attributeSelection/InfoGainAttributeEval.html [Accessed August 9, 2018]'},{id:"B15",body:'Back T. Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press; 1996'},{id:"B16",body:'Premebida C, Faria DR, de Souza FA, Nunes UJ. Applying probabilistic mixture models to semantic place classification in mobile robotics. In: IEEE International Conference on Intelligent Robots and Systems; 2015. pp. 4265-4270'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Diego R. 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School of Technology, University of Extremadura, Spain
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',metaTitle:"Authorship Policy",metaDescription:"IN TECH's Authorship Policy is based on ICMJE criteria for authorship. In order to be identified as an Author, one must:",metaKeywords:null,canonicalURL:"/page/authorship-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"
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Substantially contribute to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work
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Participate in drafting or revising the work
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Approve the final version of the work to be published.
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All contributors who meet these criteria are listed as Authors. Their exact contributions should be described in the manuscript at the time of submission.
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Conversely, all contributors who do not meet these criteria should be listed in the Acknowledgments section of the manuscript, along with a short description of their specific contributions.
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CHANGES IN AUTHORSHIP
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If it is felt necessary to make changes to the list of Authors after a manuscript has been submitted or published, it is the responsibility of the Author concerned to provide a valid reason to amend the published list. Additionally, all listed Authors must verify and approve the proposed changes in order for any amendments to be made.
\\n\\n
AFFILIATION
\\n\\n
Authors are responsible for ensuring all addresses and emails provided are correct. Under affiliation(s) all Authors should indicate where the research was conducted. Please note that no changes to the affiliation(s) can be made after the chapter has been published.
Substantially contribute to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work
\n\t
Participate in drafting or revising the work
\n\t
Approve the final version of the work to be published.
\n
\n\n
All contributors who meet these criteria are listed as Authors. Their exact contributions should be described in the manuscript at the time of submission.
\n\n
Conversely, all contributors who do not meet these criteria should be listed in the Acknowledgments section of the manuscript, along with a short description of their specific contributions.
\n\n
CHANGES IN AUTHORSHIP
\n\n
If it is felt necessary to make changes to the list of Authors after a manuscript has been submitted or published, it is the responsibility of the Author concerned to provide a valid reason to amend the published list. Additionally, all listed Authors must verify and approve the proposed changes in order for any amendments to be made.
\n\n
AFFILIATION
\n\n
Authors are responsible for ensuring all addresses and emails provided are correct. Under affiliation(s) all Authors should indicate where the research was conducted. Please note that no changes to the affiliation(s) can be made after the chapter has been published.
\n\n
Policy last updated: 2017-05-29
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This is also a reason for a continuous research activity to optimize the effect of the different welding parameters and tool-metal setups. In this contribution, two innovative welding methodologies are presented and discussed. A first new FSW configuration was defined as double-side friction stir welding (DS-FSW). In the DS-FSW, the welding is performed on both sheet surfaces, that is, the first welding is followed by a second one performed on the opposite sheet surface. In this chapter, the effect of the welding parameters, tool configuration and sheet positioning on the yield, ultimate strength, and ductility of an aluminum plate, its microstructure and its post-welding formability are discussed. A second new FSW configuration consists of a pin rotation around its centerline welding direction by 0.5 and 1.0 mm. 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His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"94311",title:"Prof.",name:"Martins",middleName:"Ochubiojo",surname:"Ochubiojo Emeje",slug:"martins-ochubiojo-emeje",fullName:"Martins Ochubiojo Emeje",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94311/images/system/94311.jpeg",biography:"Martins Emeje obtained a BPharm with distinction from Ahmadu Bello University, Nigeria, and an MPharm and Ph.D. from the University of Nigeria (UNN), where he received the best Ph.D. award and was enlisted as UNN’s “Face of Research.” He established the first nanomedicine center in Nigeria and was the pioneer head of the intellectual property and technology transfer as well as the technology innovation and support center. Prof. Emeje’s several international fellowships include the prestigious Raman fellowship. He has published more than 150 articles and patents. He is also the head of R&D at NIPRD and holds a visiting professor position at Nnamdi Azikiwe University, Nigeria. He has a postgraduate certificate in Project Management from Walden University, Minnesota, as well as a professional teaching certificate and a World Bank certification in Public Procurement. Prof. Emeje was a national chairman of academic pharmacists in Nigeria and the 2021 winner of the May & Baker Nigeria Plc–sponsored prize for professional service in research and innovation.",institutionString:"National Institute for Pharmaceutical Research and Development",institution:{name:"National Institute for Pharmaceutical Research and Development",country:{name:"Nigeria"}}},{id:"436430",title:"Associate Prof.",name:"Mesut",middleName:null,surname:"Işık",slug:"mesut-isik",fullName:"Mesut Işık",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/436430/images/19686_n.jpg",biography:null,institutionString:null,institution:{name:"Bilecik University",country:{name:"Turkey"}}},{id:"268659",title:"Ms.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/268659/images/8143_n.jpg",biography:"Dr. Zhan received his undergraduate and graduate training in the fields of preventive medicine and epidemiology and statistics at the West China University of Medical Sciences in China during 1989 to 1999. He received his post-doctoral training in oncology and cancer proteomics for two years at the Cancer Research Institute of Human Medical University in China. In 2001, he went to the University of Tennessee Health Science Center (UTHSC) in USA, where he was a post-doctoral researcher and focused on mass spectrometry and cancer proteomics. Then, he was appointed as an Assistant Professor of Neurology, UTHSC in 2005. He moved to the Cleveland Clinic in USA as a Project Scientist/Staff in 2006 where he focused on the studies of eye disease proteomics and biomarkers. He returned to UTHSC as an Assistant Professor of Neurology in the end of 2007, engaging in proteomics and biomarker studies of lung diseases and brain tumors, and initiating the studies of predictive, preventive, and personalized medicine (PPPM) in cancer. In 2010, he was promoted to Associate Professor of Neurology, UTHSC. Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. His current main research interest focuses on the studies of cancer proteomics and biomarkers, and the use of modern omics techniques and systems biology for PPPM in cancer, and on the development and use of 2DE-LC/MS for the large-scale study of human proteoforms.",institutionString:null,institution:{name:"Xiangya Hospital Central South University",country:{name:"China"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"354817",title:"Dr.",name:"Anubhab",middleName:null,surname:"Mukherjee",slug:"anubhab-mukherjee",fullName:"Anubhab Mukherjee",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y0000365PbRQAU/ProfilePicture%202022-04-15%2005%3A11%3A18.480",biography:"A former member of Laboratory of Nanomedicine, Brigham and Women’s Hospital, Harvard University, Boston, USA, Dr. Anubhab Mukherjee is an ardent votary of science who strives to make an impact in the lives of those afflicted with cancer and other chronic/acute ailments. He completed his Ph.D. from CSIR-Indian Institute of Chemical Technology, Hyderabad, India, having been skilled with RNAi, liposomal drug delivery, preclinical cell and animal studies. He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. Ltd. and heads the Hyderabad R&D center of the organization.",institutionString:"Esperer Onco Nutrition Pvt Ltd.",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a scientist and Principal Investigator at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering the lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via artificial intelligence-based analyses of exosomal Raman signatures. Dr. Paul also works on spatial multiplex immunofluorescence-based tissue mapping to understand the immune repertoire in lung cancer. Dr. Paul has published in more than sixty-five peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award and the 2022 AAISCR-R Vijayalaxmi Award for Innovative Cancer Research. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals. He is currently working on the protective activity of phenolic compounds in disorders associated with oxidative stress and inflammation.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Dr.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329248",title:"Dr.",name:"Md. Faheem",middleName:null,surname:"Haider",slug:"md.-faheem-haider",fullName:"Md. Faheem Haider",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329248/images/system/329248.jpg",biography:"Dr. Md. Faheem Haider completed his BPharm in 2012 at Integral University, Lucknow, India. In 2014, he completed his MPharm with specialization in Pharmaceutics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. He received his Ph.D. degree from Jamia Hamdard University, New Delhi, India, in 2018. He was selected for the GPAT six times and his best All India Rank was 34. Currently, he is an assistant professor at Integral University. Previously he was an assistant professor at IIMT University, Meerut, India. He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/system/329795.png",biography:"Dr. Mohd Aftab Siddiqui is an assistant professor in the Faculty of Pharmacy, Integral University, Lucknow, India, where he obtained a Ph.D. in Pharmacology in 2020. He also obtained a BPharm and MPharm from the same university in 2013 and 2015, respectively. His area of research is the pharmacological screening of herbal drugs/natural products in liver cancer and cardiac diseases. He is a member of many professional bodies and has guided many MPharm and PharmD research projects. Dr. Siddiqui has many national and international publications and one German patent to his credit.",institutionString:"Integral University",institution:null}]}},subseries:{item:{id:"5",type:"subseries",title:"Parasitic Infectious Diseases",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11401,editor:{id:"67907",title:"Dr.",name:"Amidou",middleName:null,surname:"Samie",slug:"amidou-samie",fullName:"Amidou Samie",profilePictureURL:"https://mts.intechopen.com/storage/users/67907/images/system/67907.jpg",biography:"Dr. Amidou Samie is an Associate Professor of Microbiology at the University of Venda, in South Africa, where he graduated for his PhD in May 2008. He joined the Department of Microbiology the same year and has been giving lectures on topics covering parasitology, immunology, molecular biology and industrial microbiology. 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\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
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The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment"},{id:"5",title:"Parasitic Infectious Diseases",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. 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He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
",annualVolume:11399,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/3.jpg",editor:{id:"205604",title:"Dr.",name:"Tomas",middleName:null,surname:"Jarzembowski",fullName:"Tomas Jarzembowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKriQAG/Profile_Picture_2022-06-16T11:01:31.jpg",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorTwo:{id:"484980",title:"Dr.",name:"Katarzyna",middleName:null,surname:"Garbacz",fullName:"Katarzyna Garbacz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003St8TAQAZ/Profile_Picture_2022-07-07T09:45:16.jpg",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorThree:null,editorialBoard:[{id:"190041",title:"Dr.",name:"Jose",middleName:null,surname:"Gutierrez Fernandez",fullName:"Jose Gutierrez Fernandez",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"University of Granada",institutionURL:null,country:{name:"Spain"}}},{id:"156556",title:"Prof.",name:"Maria Teresa",middleName:null,surname:"Mascellino",fullName:"Maria Teresa Mascellino",profilePictureURL:"https://mts.intechopen.com/storage/users/156556/images/system/156556.jpg",institutionString:"Sapienza University",institution:{name:"Sapienza University of Rome",institutionURL:null,country:{name:"Italy"}}},{id:"164933",title:"Prof.",name:"Mónica Alexandra",middleName:null,surname:"Sousa Oleastro",fullName:"Mónica Alexandra Sousa Oleastro",profilePictureURL:"https://mts.intechopen.com/storage/users/164933/images/system/164933.jpeg",institutionString:"National Institute of Health Dr Ricardo Jorge",institution:{name:"National Institute of Health Dr. Ricardo Jorge",institutionURL:null,country:{name:"Portugal"}}}]},{id:"4",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",annualVolume:11400,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",institutionString:null,institution:{name:"Sichuan University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"302145",title:"Dr.",name:"Felix",middleName:null,surname:"Bongomin",fullName:"Felix Bongomin",profilePictureURL:"https://mts.intechopen.com/storage/users/302145/images/system/302145.jpg",institutionString:null,institution:{name:"Gulu University",institutionURL:null,country:{name:"Uganda"}}},{id:"45803",title:"Ph.D.",name:"Payam",middleName:null,surname:"Behzadi",fullName:"Payam Behzadi",profilePictureURL:"https://mts.intechopen.com/storage/users/45803/images/system/45803.jpg",institutionString:"Islamic Azad University, Tehran",institution:{name:"Islamic Azad University, Tehran",institutionURL:null,country:{name:"Iran"}}}]},{id:"5",title:"Parasitic Infectious Diseases",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",annualVolume:11401,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",editor:{id:"67907",title:"Dr.",name:"Amidou",middleName:null,surname:"Samie",fullName:"Amidou Samie",profilePictureURL:"https://mts.intechopen.com/storage/users/67907/images/system/67907.jpg",institutionString:null,institution:{name:"University of Venda",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"188881",title:"Dr.",name:"Fernando José",middleName:null,surname:"Andrade-Narváez",fullName:"Fernando José Andrade-Narváez",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRIV7QAO/Profile_Picture_1628834308121",institutionString:null,institution:{name:"Autonomous University of Yucatán",institutionURL:null,country:{name:"Mexico"}}},{id:"269120",title:"Dr.",name:"Rajeev",middleName:"K.",surname:"Tyagi",fullName:"Rajeev Tyagi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRaBqQAK/Profile_Picture_1644331884726",institutionString:"CSIR - Institute of Microbial Technology, India",institution:null},{id:"336849",title:"Prof.",name:"Ricardo",middleName:null,surname:"Izurieta",fullName:"Ricardo Izurieta",profilePictureURL:"https://mts.intechopen.com/storage/users/293169/images/system/293169.png",institutionString:null,institution:{name:"University of South Florida",institutionURL:null,country:{name:"United States of America"}}}]},{id:"6",title:"Viral Infectious Diseases",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",annualVolume:11402,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",editor:{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",fullName:"Emmanuel Drouet",profilePictureURL:"https://mts.intechopen.com/storage/users/188773/images/system/188773.png",institutionString:null,institution:{name:"Grenoble Alpes University",institutionURL:null,country:{name:"France"}}},{id:"188219",title:"Prof.",name:"Imran",middleName:null,surname:"Shahid",fullName:"Imran Shahid",profilePictureURL:"https://mts.intechopen.com/storage/users/188219/images/system/188219.jpeg",institutionString:null,institution:{name:"Umm al-Qura University",institutionURL:null,country:{name:"Saudi Arabia"}}},{id:"214235",title:"Dr.",name:"Lynn",middleName:"S.",surname:"Zijenah",fullName:"Lynn Zijenah",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSEJGQA4/Profile_Picture_1636699126852",institutionString:null,institution:{name:"University of Zimbabwe",institutionURL:null,country:{name:"Zimbabwe"}}},{id:"178641",title:"Dr.",name:"Samuel Ikwaras",middleName:null,surname:"Okware",fullName:"Samuel Ikwaras Okware",profilePictureURL:"https://mts.intechopen.com/storage/users/178641/images/system/178641.jpg",institutionString:null,institution:{name:"Uganda Christian University",institutionURL:null,country:{name:"Uganda"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/254446",hash:"",query:{},params:{id:"254446"},fullPath:"/profiles/254446",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()