Composition of most commonly used feeds, fodders and its nutrient composition (DM, CP, TDN) was used as per ICAR (2013) and present cost of the ingredients*.
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"7472",leadTitle:null,fullTitle:"Gut Microbiota - Brain Axis",title:"Gut Microbiota",subtitle:"Brain Axis",reviewType:"peer-reviewed",abstract:"The gut-brain axis has gained considerable attention from different branches of the scientific community in recent years. In this book, scientists from different disciplines present current scientific knowledge on the topic. The interaction between the prokaryote and eukaryote cells stimulates the evolutionary processes, and results in various systemic illnesses such as neuropsychiatric disorders and may help the continuity of health. Nature has provided us with healthy food that builds our pharmacy. This natural pharmacy store may help the body's healing processes through its effects on gut microbiota and the immune system. This book aims to provide the reader with detailed analyses of the current scientific knowledge on the gut-brain axis and its relation with health and disease. We hope that the reader benefits from the presented material.",isbn:"978-1-78984-815-1",printIsbn:"978-1-78984-814-4",pdfIsbn:"978-1-83881-828-9",doi:"10.5772/intechopen.75784",price:119,priceEur:129,priceUsd:155,slug:"gut-microbiota-brain-axis",numberOfPages:114,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"4aaffb64056f2ff00c7ddf1b0d235174",bookSignature:"Alper Evrensel and Barış Önen Ünsalver",publishedDate:"December 12th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/7472.jpg",numberOfDownloads:7829,numberOfWosCitations:12,numberOfCrossrefCitations:10,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:22,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:44,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 27th 2018",dateEndSecondStepPublish:"April 17th 2018",dateEndThirdStepPublish:"June 16th 2018",dateEndFourthStepPublish:"September 4th 2018",dateEndFifthStepPublish:"November 3rd 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"197156",title:"Dr.",name:"Alper",middleName:null,surname:"Evrensel",slug:"alper-evrensel",fullName:"Alper Evrensel",profilePictureURL:"https://mts.intechopen.com/storage/users/197156/images/system/197156.jpeg",biography:"Dr. Alper Evrensel is currently an Assistant Professor of Psychiatry at the Uskudar University, Istanbul, Turkey. He has been working at the NP Istanbul Brain Hospital for 10 years. He has been working in the area of neuropsychiatry, neuropsychophilosophy, and published over 50 papers in peer-reviewed journals, as well as 3 invited chapters in books. His research and clinical interests focus on gut-brain axis and fecal microbiota transplantation in neuropsychiatric disorders.",institutionString:"Üsküdar University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Üsküdar University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"247088",title:"Dr.",name:"Barış Önen",middleName:null,surname:"Ünsalver",slug:"baris-onen-unsalver",fullName:"Barış Önen Ünsalver",profilePictureURL:"https://mts.intechopen.com/storage/users/247088/images/system/247088.jpeg",biography:"Dr. Barış Önen Ünsalver is currently an Assistant Professor of Psychiatry at the Uskudar University, Istanbul, Turkey. She has been working at the NP Istanbul Brain Hospital for 8 years. She has been working in the area of neuropsychiatry, neuropsychophilosophy, psychosomatic medicine and published over 30 papers in peer-reviewed journals, as well as 5 invited chapters in books.",institutionString:"Üsküdar University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1059",title:"Neuroscience",slug:"mental-and-behavioural-disorders-and-diseases-of-the-nervous-system-neuroscience"}],chapters:[{id:"62182",title:"Prokaryotes Rule the World",doi:"10.5772/intechopen.77953",slug:"prokaryotes-rule-the-world",totalDownloads:1097,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"For millions of years, prokaryotic organisms have functioned as a vital selective force shaping eukaryotic evolution. It is now widely accepted that gut bacteria play a vital role in various physiological and metabolic activities of hosts, and thus, it is essential to maintain their homeostasis. Previous studies have shown an association of gut bacterial imbalance (dysbiosis) associated with several pathologies. However, very little is known about possible mechanisms involved between bacteria and hosts to maintain their homeostasis in the gut. Bacterial activities, such as cooperation (biofilm formation, horizontal gene transfer, quorum sensing, etc.), antagonism, and combination, and host responses of their immune system, gut barrier functions, and different dietary components have been identified as crucial factors for maintaining bacterial homeostasis in the gut. Our understanding of several possible mechanisms involved in gut bacterial homeostasis should be widened to modulate their composition or treat diseases. The objective of this chapter is to provide an overview of different factors involved in gut bacterial homeostasis with an emphasis on host intestinal barrier and immune system, dietary components, and quorum sensing. Also, brief information regarding roles of microbiota on gut-brain axis has also been included.",signatures:"Bishnu Adhikari, Young Min Kwon, Billy M. Hargis and Guillermo Tellez-Isaias",downloadPdfUrl:"/chapter/pdf-download/62182",previewPdfUrl:"/chapter/pdf-preview/62182",authors:[{id:"73465",title:"Dr.",name:"Guillermo",surname:"Téllez",slug:"guillermo-tellez",fullName:"Guillermo Téllez"},{id:"76651",title:"Dr.",name:"Billy",surname:"Hargis",slug:"billy-hargis",fullName:"Billy Hargis"},{id:"248637",title:"Mr.",name:"Bishnu",surname:"Adhikari",slug:"bishnu-adhikari",fullName:"Bishnu Adhikari"},{id:"248639",title:"Dr.",name:"Young Min",surname:"Kwon",slug:"young-min-kwon",fullName:"Young Min Kwon"}],corrections:null},{id:"62506",title:"Influence of Probiotic Supplementation on Brain Function: Involvement of Gut Microbiome, Inflammation, and Stress Pathway",doi:"10.5772/intechopen.79511",slug:"influence-of-probiotic-supplementation-on-brain-function-involvement-of-gut-microbiome-inflammation-",totalDownloads:1304,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Probiotics were reported for several physical and psychological health benefits. Probiotics can positively alter the gut microbiome and nourish the commensal microbial load. Recent studies revealed that the cognitive functions (anxiety and depression) of human beings are meticulously associated with their genetic makeup, food habits, and gut microbiome. The gut microbiome may communicate with the brain through neural and humoral pathways, while involving several neurotransmitters and signaling molecules. The immune response, especially inflammatory system, plays a critical role in the microbiome and in mental health. Thus, many studies were conducted to explore the beneficial effect of probiotic, single and multistrain, formulations. Fruitful results were observed, but the underlying mechanism of probiotic-mediated improvement of mental health is not fully illustrated, even though some studies explained that the production of neurotransmitter-like metabolites by the probiotic strain could be the possible mediator of gut-brain axis. The present chapter summarizes the outcome of probiotic-based treatment for the improvement of stress and depression with respect to microbiome change, inflammation, and stress pathway.",signatures:"Chaiyavat Chaiyasut and Bhagavathi Sundaram Sivamaruthi",downloadPdfUrl:"/chapter/pdf-download/62506",previewPdfUrl:"/chapter/pdf-preview/62506",authors:[{id:"254957",title:"Ph.D.",name:"Chaiyavat",surname:"Chaiyasut",slug:"chaiyavat-chaiyasut",fullName:"Chaiyavat Chaiyasut"},{id:"255003",title:"Dr.",name:"Sivamaruthi",surname:"Bhagavathi Sundaram",slug:"sivamaruthi-bhagavathi-sundaram",fullName:"Sivamaruthi Bhagavathi Sundaram"}],corrections:null},{id:"63475",title:"Philosophy of Nutrition: Past-Future Nutrition",doi:"10.5772/intechopen.80726",slug:"philosophy-of-nutrition-past-future-nutrition",totalDownloads:1241,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"“Back to the roots” is what we may call our experience in our researches concerning gut-brain axis. What Hippocrates, Plato, Ibn-Khaldun, Galen, and many other philosophers from antique ages suggested can be proven today with all our technological aids. The observation in the old of the link ages between nutrition and the well being of our souls, mind, and bodies was found to be true. In fact, what the ancient philosophers said about nutrition in connection with a healthy life is quite similar to what we hear in the recent years. This is a demonstration of how important it is to observe ourselves as humans. In the last researches, the connection between gut and brain and their formation of the personal mood showed the same results. Together with the mood, the spirit has also proven to be influenced by nutrition. Our industrial era put the focus right from the beginning more on feeding masses than on nurturing human kind. Leaving that aside, the doctors today concentrate more on diagnosis and their foreseen treatment than on observing and preventing dıseases. A healthy and conscious nutrition is the start of a healthy worth living lıfe. What philosophers and doctors found out hundreds of years ago should be applicable and excisable today.",signatures:"Gulsen Meral",downloadPdfUrl:"/chapter/pdf-download/63475",previewPdfUrl:"/chapter/pdf-preview/63475",authors:[{id:"259964",title:"Dr.",name:"Gulsen",surname:"Meral",slug:"gulsen-meral",fullName:"Gulsen Meral"}],corrections:null},{id:"62899",title:"Autism in Children Connected with Gastrointestinal Symptoms",doi:"10.5772/intechopen.79863",slug:"autism-in-children-connected-with-gastrointestinal-symptoms",totalDownloads:1203,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Autism in children has increased significantly over the last few years. Eating disorders and ailments of the gastrointestinal system are a common affliction among these children. The hypothesis linking the autism spectrum disorder (ASD) and the digestive system with its bacterial microflora based on the concept of the gut-brain axis become very interesting and credible. This axis is a two-way communication between the central nervous system (CNS) and gut innervation. Mechanisms of this dependency include effects of neurological, immunological, and hormonal mediators. Among patients with ASD, mucosal permeability is frequently diagnosed, which may be caused by chronic inflammation. Such inflammation can damage cells of the intestinal membrane. Children with ASD also have a different composition of intestinal and gastric flora compared to healthy ones. Different types of environmental and situational stressors may contribute to the occurrence of gastrointestinal disorders such as irritable bowel syndrome, enteritis, as well as increase intestinal permeability and change their bacterial flora. The chapter presents eating disorders and nutritional deficiencies in children with ASD and shows how nutrition during pregnancy can affect ASD symptoms and how to reduce the severity of ASD symptoms through carefully selected nutritional interventions and supplementation.",signatures:"Piotr Walecki, Aleksandra Kawala-Janik and Justyna Siwek",downloadPdfUrl:"/chapter/pdf-download/62899",previewPdfUrl:"/chapter/pdf-preview/62899",authors:[{id:"248909",title:"Dr.",name:"Piotr",surname:"Walecki",slug:"piotr-walecki",fullName:"Piotr Walecki"},{id:"264149",title:"Dr.",name:"Aleksandra",surname:"Kawala-Janik",slug:"aleksandra-kawala-janik",fullName:"Aleksandra Kawala-Janik"},{id:"264150",title:"MSc.",name:"Justyna",surname:"Siwek",slug:"justyna-siwek",fullName:"Justyna Siwek"}],corrections:null},{id:"62085",title:"Fecal Microbiota Transplants as a Treatment Option for Parkinson’s Disease",doi:"10.5772/intechopen.78666",slug:"fecal-microbiota-transplants-as-a-treatment-option-for-parkinson-s-disease",totalDownloads:1352,totalCrossrefCites:3,totalDimensionsCites:3,hasAltmetrics:1,abstract:"Parkinson’s disease (PD) is a progressive neurodegenerative disease with an unknown cause, high prevalence, and no effective therapy. Alterations in gut microbiota composition and function have been found in PD, which could influence the gut-brain axis. Several mechanisms have been proposed and are investigated to explain the link between gut microbiota and PD. In model systems and in individual case reports, modulation of gut microbiota has been associated with improvement of PD. A safe and effective way of gut microbiota manipulation is fecal microbiota transplant (FMT). FMT is used successfully for treatment of recurrent gastrointestinal infections as well as other indications. We advocate randomized clinical trials with FMT as a treatment option for PD.",signatures:"Inez A. Flameling and Ger T. Rijkers",downloadPdfUrl:"/chapter/pdf-download/62085",previewPdfUrl:"/chapter/pdf-preview/62085",authors:[{id:"248880",title:"Prof.",name:"Ger",surname:"Rijkers",slug:"ger-rijkers",fullName:"Ger Rijkers"},{id:"249674",title:"Dr.",name:"Inez",surname:"Flameling",slug:"inez-flameling",fullName:"Inez Flameling"}],corrections:null},{id:"62125",title:"Probiotics for Preventing Cognitive Impairment in Alzheimer’s Disease",doi:"10.5772/intechopen.79088",slug:"probiotics-for-preventing-cognitive-impairment-in-alzheimer-s-disease",totalDownloads:1633,totalCrossrefCites:5,totalDimensionsCites:12,hasAltmetrics:1,abstract:"Alzheimer’s disease (AD) is a progressive and irreversible neurodegenerative disease that results in gradual cognitive impairment and eventually leads to dementia. However, despite AD being one of the most prevalent neurodegenerative diseases in aging societies, no clinically successful therapeutic strategies for its treatment or prevention have been reported to date. Studies have indicated that gut microbial alterations are linked to AD. Probiotics are living microorganisms that are known to confer health benefits to the host when ingested in adequate amounts. Certain strains of probiotics appear to influence the central nervous system (CNS) and behavior via the microbiota-gut-brain axis. Increasing evidence from preclinical and clinical studies has demonstrated that probiotics possess preventive as well as therapeutic potential for AD. It is speculated that probiotics could ameliorate the progression of AD by modulating the inflammatory process, counteracting oxidative stress, and other possible mechanisms, although further studies are needed to understand the details. In this chapter, we will highlight the current understandings of the effects as well as the possible mechanisms of action of probiotics for preventing cognitive impairment in AD.",signatures:"Chyn Boon Wong, Yodai Kobayashi and Jin-zhong Xiao",downloadPdfUrl:"/chapter/pdf-download/62125",previewPdfUrl:"/chapter/pdf-preview/62125",authors:[{id:"249102",title:"Dr.",name:"Jinzhong",surname:"Xiao",slug:"jinzhong-xiao",fullName:"Jinzhong Xiao"},{id:"259257",title:"Dr.",name:"Chyn Boon",surname:"Wong",slug:"chyn-boon-wong",fullName:"Chyn Boon Wong"},{id:"259258",title:"Mr.",name:"Yodai",surname:"Kobayashi",slug:"yodai-kobayashi",fullName:"Yodai Kobayashi"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"4461",title:"Advanced Brain Neuroimaging Topics in Health and Disease",subtitle:"Methods and Applications",isOpenForSubmission:!1,hash:"30152982950eed84faf2ad2a75f78f4e",slug:"advanced-brain-neuroimaging-topics-in-health-and-disease-methods-and-applications",bookSignature:"T. 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\r\n\tThis book is intended for professionals dealing with diagnostics and treatment of infertility and aims to provide comprehensive information on the current state of assisted reproductive technologies and their directions of development.
\r\n\tAssisted Reproductive Technologies (ART) is a key technology for treating infertility, which occurs in 10-15% of the general population in reproductive age. This has been one of the most tumultuously developing interdisciplinary technologies in medicine in recent decades. Thanks to in vitro methods, more than 5 million children were born in the whole world. For 40 years, the success rates of this treatment have increased many times, respectively in the first years from less than 10% to more than 50% in present days (in some groups of patients). The reason for this rapid increase is the introduction of new drugs and stimulation protocols, improvement of embryo culture media, and the use of new types of laboratory equipment that improve the conditions for embryo development. Last but not least, the introduction of modern genetic methods, as well as new gamete and tissue freezing techniques, has improved the methods' diagnostic and therapeutic capabilities.
Applications of, e.g., clinical diagnosis, drug development, environmental research, security and defense, require self-contained rapid analytical platforms to get rid of tedious operation processes and long turn-around times. In 1960s, applications of enzymes explored a new way in analytical chemistry to obtain specific, sensitive and ease-of-use assays. At the same time, ion selective electrodes have been developed for rapid non-reagental analysis of inorganic ions. In 1962, the concept of enzyme transducer was proposed and sooner the device was developed [1]. Following this idea of enzyme electrode, the first enzyme electrode-based glucose meter was commercialized in 1975. After that, self-contained analytical platforms based on different principles were developed including thermistor, [2] optical fiber, [3] piezoelectric crystal detector, [4] surface plasmon resonance, [5] etc. Today, such analytical platforms are regarded as biosensors. A biosensor is a self-contained integrated device that is capable of providing specific quantitative or semi-quantitative analytical information using a biological recognition element (biochemical receptor) which is in direct spatial contact with a transducer element [6]. Today, biosensors have been applied to a wide variety of analytical problems, e.g., medicine, environmental research, food control, and process industry [7].
Biosensors can be divided into two groups based on involving a labeling process during the detection or not. A label is a foreign molecule that is chemically or temporarily attached to the target (i.e., the molecule of interest) through a labeling process to detect molecular presence or activity. In the above-mentioned early period of the biosensor history, typical biosensing processes were usually realized by measuring the transduced mechanical, electrical, or optical signals without any labels, as illustrated in Figure 1a. Such label-free biosensors can provide direct information without complicated sample preparation steps. In contrast, label-based biosensors utilizing additional operation processes for higher signal-to-noise ratios and for a broader range of sensing/transducer systems. Conventional biosensing labels are optical molecules or radioactive elements borrowed from bio-analytical systems such as gel electrophoresis and enzyme linked immunosorbent assays. A typical strategy of sandwich assay for antibody-based detection is shown in Figure 1b.
Scheme of typical (a) label-free and (b) label-based biosensors.
Due to the fast development of nanotechnology and material science, nanomaterials are widely adopted as biosensing labels, many of which are dyes in senses of optics or electrochemistry. The special size of these nanomaterial dyes provides unique properties that greatly improve the performances of relevant biosensors. In this chapter, we focus on dyes used as biosensing labels and discuss their properties, applications and how they improve the biosensing properties.
Colorimetry technique is a practical and direct analytical method to determine the concentration of colored analyte depending on the color change in solution. The colorimetric biosensing strategy based on this principle has become one of the most popular and important strategies due to its simplicity, visualization, low cost and non-destruction. Based on the strategies of signal generation, colorimetric assays can mainly be divided into two groups, i.e., assays based on enzymes for chromogenic reactions, and assays based on colored labels. Herein, we focus on the later group in which dyes play a crucial role.
As a successful example to employ nanomaterial and nanotechnology to solve the biological problems, colloidal gold has been introduced in the biosensing fields more than 20 years with lots of amazing works being reported. Colorimetric biosensors based on gold nanoparticles (GNPs) have greatly developed in both scientific study and commercial applications.
(a) Localized SPR band formation. Red and gray circles represent negative and positive electron clouds, respectively. (b) GNP agglomeration leads to the shift of SPR absorption band.
Schematic of a typical lateral-flow immunological detection system.
Three principle methods for modifying GNPs are briefly illustrated in Figure 4: (1) A simple and common way to immobilize the biomolecules on the GNPs is labeling through the sulfur-gold interactions; [20] (2) Ligands can be capped on the GNPs in the process of particle growth or though ligands replace after the synthesis; (3) Ligands can be absorbed on the GNPs surface directly via non-covalent interactions.
Illustration of different GNP conjugation methods.
In 1997, the first GNP-based colorimetric biosensor was reported [21]. In this work, the hybridization of DNA probes capped on GNP surface and target DNA resulted in the formation of GNP agglomeration, accompanying a visually red-to-purple color change. This is the most typical biosensor that uses biochemical reactions to induce the cross-linked aggregation of GNPs. Since then, a new generation of medical diagnostic technology based on the nanomaterials has begun. Oligonucleotides, peptides, antibodies and aptamers have been labeled with GNPs for the colorimetric detection of different targets based on the similar principle. Such strategy designs usually achieve naomolar detection limits, which is limited by the signal-to-noise ratio related to the intrinsic properties of labels and sensors [22]. To amplify the signals and optimize the performance of biosensor, the biochemical and molecular amplification methods are introduced in the biosensing process. Via duplex-specific nuclease-assisted amplification method, a colorimetric method was developed for microRNA dection based on GNPs aggregation [23]. DNAzyme-assisted target recycling was utilized, combined with surface plasmons of GNPs coupling in the colorimetric biosensor, obtaining a fast and simple detection of genetic targets with 50 pM sensitivity [24]. Using imaging-based analysis instead of spectrographic analysis has higher signal-to-noise ratio and thus potentially lower detection limit. A dark-field microscope based methodology was applied for the sensing of GNP aggregation, obtaining a detection limit of 43 aM of DNA, which was 5–9 orders of magnitude lower than conventional colorimetric sensor based strategies [25].
Carbon nanoparticles, also named colloidal carbon, can be visually detected in a qualitative or semi-quantitative manner and thus being used as colored labels. Compared to GNPs, carbon nanoparticles have several excellent properties, e.g., high stability, nontoxicity, ease-of-preparation, and ease-of-modification [26]. The dark black color of carbon dots endows a high signal-to-noise ratio, allowing sensitivities below the low picomolar range even by visual inspection [27].
Colored latex particles are also often used as labels in the colorimetric biosensor. Latex particles are natural or synthetic polymer nano- and micro-particles that suspend stably in water, and the polystyrene particles are used mostly.
There are three ways to prepare colored latex particles by dying latex particles with different types of dyes molecules: (1) co-polymerization of polymer monomer with dyes; (2) cross-linking the dyes on particles surface by covalent bonds; (3) physical embedding or absorption dyes in particles. After the dying, usually dyes on the surface are removed in order to functionalize the active groups (sulfhydryl groups, amino groups and carboxyl groups) on the latex particles for further labeling the biomolecules [28].
Benefit its wide variety of sources, low cost and easy to be functionalized, the latex particles are applied as probes in immunochromatographic analysis quite early [29]. The good properties enable them are still used now. A lateral flow immunoassay was developed by covalent functionalizing the antigens on colored latex particles for the visual diagnosis of canine visceral leishmaniasis [30]. A latex particles-GNPs composites labeled with antibodies were synthesized as probed for the immunochromatographic test. The nanocomposites amplified the binding capacity of GNPs with target antigens and improved the sensitivity 2 orders of magnitude compared with GNPs-antibodies probes [31].
In the field of biotechnology, diagnosis and drug discovery, fluorescent assay is by far the most popular methodology because of not only its sensitivity and versatility but also the high commercialization of fluorescent labels [32]. In addition to the new fluorescent nanomaterials (e.g., upconversion fluorescent materials and aggregation-induced emission (AIE) materials that are described further below), new spectroscopic sensors have also been developed based on rising technologies such as fiber optics, LEDs and fast imaging devices, all of which contributed to the fast development as well as high interdisciplinarity of fluorescent biosensors.
Organic fluorescent dyes are a class of organic molecules that contain a fluorescent core skeleton with a large conjugate system and some auxochrome or active group (such as carboxyl, amino, amide, etc). The fluorescent core skeleton enables them absorb a certain excitation light and emitting it as fluorescence. The auxochrome or active group is capable of altering wavelengths and enhance fluorescence or labeling them to bio-receptors for recognizing various biomolecules in biosensing [33]. Briefly, the fluorescent dyes labeled bio-receptors, also called fluorescent probes, can recognize various biomolecules and then convert the recognition events into fluorescent signal output to achieve biosensing or imaging.
Currently, there are many kinds of organic fluorescent dyes, most of which can be used to label bio-receptors for biosensing and imaging. Here, some major organic fluorescent dyes labels are introduced, including fluorescein derivatives, rhodamine derivatives, cyanine derivatives and other commonly used organic fluorescent dyes.
The signal conversion mechanism in sensing process are various, such as electron transfer quenching or fluorescence recovery, fluorescence resonance energy transfer (FRET), or monomer-excimer emission conversion with pyrene fluorophores. The following will introduce the major signal conversion mechanism involved in the fluorescence biosensing process.
EB staining for nucleic acids detection.
An emerging biosensing strategy is designed based on the G-quadruplex (G4) DNA structure and corresponding intercalating dyes such as ThT, NMM, etc. (Figure 6) [38]. G4 DNA structure is formed from DNA guanine-rich sequences, which has been confirmed to be stably present in human live cell [39]. Therefore, endogenous G4 DNA can be easily detected by using intercalating dyes targeting G4 DNA. Additionally, G4 DNA structures can be formed by the amplicons of any kinds of DNA amplification methods that produce single-stranded DNA, making G4 structure a convenient cascade amplification tool (a molecular amplification followed by a signal amplification) that can be applied in homogeneous and isothermal bioanalytical assays. Moreover, the formation or consume of the G4 structure after binding to the target molecules will change the interaction between G4 and intercalating dyes, resulting in increased or decreased fluorescence intensity for detection.
Fluorescence enhancement based on the intercalating dyes and G4 structure.
A FRET technique includes an energy transfer between two fluorophores, i.e., from high energy donor to a lower energy acceptor (Figure 7). The FRET occurs when the donor and acceptor are close to each other, approximately between 1–10 nm, and this distance meets the dimensions of biological molecules. Since the FRET is sensitive to the relative distance between donors and acceptors, when biological acceptor labeled with donors (or acceptors) comes close to the biological target labeled with acceptors (or donors), FRET signals can be detected.
Schematic illustration of fluorescence resonance energy transfer.
Rather than labels the donor and the acceptor on different biomolecules, a molecular beacon (MB) utilized a donor linked with an acceptor through a bioresponsive probe, further simply the design of FRET biosensors [40]. Typically, a MB is a single-stranded oligonucleotide probe labeled with a fluorophore at its one end and a quencher at the other. Due to the length and/or the secondary structure of the oligonucleotide, the probe holds the fluorophore and quencher close to each other, thus inducing a quenching. Upon the hybridization between the probe and the target, the distance between the fluorophore and the quencher changes, restoring the fluorescence [41] (Figure 8).
Illustration of a molecular beacon and examples of its applications.
The labeling type between organic fluorescent dyes and bio-receptors can generally be divided into two types: covalent and non-covalent (such as intercalation, groove binding or electrostatic interaction). Different labeling method has different fluorescent sensing mechanisms.
Covalently binding labeled fluorescent probes including single-labeled fluorescent probe and dual-labeled fluorescent probe. Single-labeled fluorescent probes are obtained by covalently binding single fluorescent dye molecules to bio-receptors. The single-labeled probe sensing mechanism may be summarized as follows: when the bio-receptor of the fluorescent probe recognizes the target molecules, the fluorescence properties of dyes would be changed, such as changes in fluorescence intensity and fluorescence anisotropy, thus converting the recognition process into a measurable fluorescence signal [44, 45, 46]. Dual-labeled fluorescent probes are obtained by covalently binding dual fluorescent dye molecules (or a dye and a quencher) to bio-receptors. The dual-labeled probes are all distance dependent, the rearrangement of the probe structure after binding to the target molecules will change the distance between the two labels, resulting in changes in the fluorescence properties of the system.
Non-covalently binding fluorescent probes mainly refer to nucleic acid fluorescent probes that obtained by the binding of intercalating dyes and DNA. As mentioned above, when the nucleic acid intercalating dye binds to a specific DNA structure, the fluorescent signal changes. Based on this principle, a series of biosensors have been developed. Compared with covalently binding fluorescent probes, the non-covalently binding fluorescent probes will not affect the binding affinity of the probe to the target, and also have the advantages of easy operation and low cost [47].
Fluorescein and its derivatives are one class of xanthene dyes. Fluorescein was first produced by Von Bayer in 1871, which has a good rigid coplanar structure and can produce strong green fluorescence under the action of laser. Due to its easy synthesis, low cost, low biological and cytotoxicity, high molar absorption coefficient, and high fluorescence quantum yield, fluorescein can be widely used in biological imaging and analysis [48]. However, fluorescein also has some defects, such as high pH sensitivity [49], small stokes [50] and poor light stability [51]. In order to improve the fluorescence performance of fluorescein, many important fluorescein derivatives have been developed by introducing functional group modification to fluorescein [52]. Additionally, fluorescein derivatives contain some active groups, which can bind with bio-receptors to obtain fluorescent dyes labeled probes with high selectivity, good stability and high sensitivity for biosensing [53]. Currently, commercially available fluorescein derivatives dye mainly includes 6-carboxy-fluorescein (FAM), 5-tetrachloro-fluorescein (TET), 5-hexachloro- fluorescein (HEX).
It was discovered in the late 1980s that rhodamine and its derivatives are important fluorescent dyes and also belong to xanthene dyes. The molecular structure of rhodamine dyes is very stable, coplanar, and can produce strong red fluorescence under the excitation. They also can bind with bio-receptors to obtain fluorescent dyes labeled probes with high selectivity, good stability and high sensitivity for biosensing. Compared with fluorescein derivatives, rhodamine derivatives have stronger photostability, higher fluorescence quantum yield and lower pH sensitivity. Commercially available rhodamine derivatives dyes for labels in biosensing mainly include 6-carboxyl-x-rhodamine (ROX), tetramethyl-6-carboxyrhodamine (TAMRA) and Texas red.
It was discovered in the late 1880s that rhodamine and its derivatives are important fluorescent dyes and also belong to xanthene dyes [54]. The molecular structure of rhodamine dyes is very stable, coplanar, and can produce strong red fluorescence under the excitation [55]. They also can bind with bio-receptors to obtain fluorescent dyes labeled probes with high selectivity, good stability and high sensitivity for biosensing. Compared with fluorescein derivatives, rhodamine derivatives have stronger photostability, higher fluorescence quantum yield and lower pH sensitivity [56]. Commercially available rhodamine derivatives dyes for labels in biosensing mainly includes 6-carboxyl-x-rhodamine (ROX), tetramethyl-6-carboxyrhodamine (TAMRA) and Texas red.
Cyanine dyes was first discovered by Williams in 1856, subsequently, Vogel discovered that these dyes have very good photosensitivity, which promote the development of cyanine dyes [57]. Cyanine dyes and derivatives have excellent spectral characteristics, such as high molar extinction coefficient, high fluorescence quantum yield, and long fluorescence emission wavelength. More importantly, the maximum emission and absorption of these dyes are located in the near-infrared region. In this region, the self-absorption and background fluorescence of biomolecules are relatively small [58]. Thus, cyanine dye derivatives have become the most commonly used fluorescent signal groups in protein, nucleic acid and other biological analysis [59]. Commercially available cyanine derivatives dyes for labels in biosensing mainly refers to N-carboxypentyl-5-sulfonate-3H-indocyanine dyes, including Cy3, Cy5, Cy5.5 and Cy7.
Quantum dots (QDs) are spherical or quasiballistic semiconductor nanoparticles that bind excitons in the three dimensions, with a diameter no larger than twice the Bohr radius of the excitons of their corresponding semiconductor material, thus confining the motion of electrons, holes, or excitons in three dimensions. Due to the quantum confinement effects, the quantum dots display unique optical and electronic properties compared to the bulk materials.
QDs were firstly synthesized in glass matrix in 1970s and with their fluorescent properties reported [60]. Later some groups studied the novel properties of quantum dots and tried to investigate influences of quantum effects on the optical properties of QDs [61]. In 1980s, CdS nanospheres were synthesized in colloidal solution and the basic theory of QDs were studied [62]. In 1993, the high quality colloidal QDs were prepared first time with uniform size in the solution [63], which provided favorable materials for both theoretical study and practical applications. Since then, various types of QDs with different compositions and properties have been synthesized by the solution growth method.
According to the chemical compositions, QDs can be mainly divided to two groups. Single component QDs, such as metal chalcogenides, [64] attracted much attentions at the early stage of the QDs development. Due to the uniformity, optical and electronic properties of such QDs can be tuned by simply controlling their sizes. Multiple component QDs are either core-shell structural or alloyed. Core-shell structural QDs have a core with one component embedded in another material as a shell, such as CdSe/ZnS [65]. Usually, to reduce the nonradioactive recombination of electron–hole pairs, the material used as the shell has a larger band gap than that in the core, thus improving the fluorescence quantum yield. Coating the same core with different shells adjust the properties of the QDs. Alloyed QDs that have homogeneous or heterogeneous alloyed internal composition, for example, CdSxSe1-x/ZnS [66]. This type of QDs allows tuning the properties by changing the proportion of the component without changing the size. Interestingly, alloyed QDs not only exhibit the original properties of each component, but also display newly additional and adjustable properties because of the merge of the different composites. Now despite classical nanocrystals, there are various new species of QDs that have been prepared, such as perovskite QDs [67] and graphene QDs [68].
Generally, the size of QDs, i.e., in the range of 2–10 nm, endows these nanoparticles high surface-to-volume ratios. The large surface provides rich sites for further functionalization and immobilization of molecules, including nucleic acids and proteins. [69] Importantly, after functionalized with hydrophilic ligands, QDs are soluble and stable in aqueous solution, which is the common environment for biological reactions.
The most obvious and widely utilized properties of QDs are the optical properties. Compared with organic dyes, QDs display higher fluorescence quantum yield and extinction coefficient, broader excitation spectra, longer lifetimes and tunable fluorescent emissions [70]. As the size of QDs decreases, the band gap between valence band (VB) and conduction band (CB) increases, which means more energy needed for electrons excitations (from ground state in VB to CB) as well as more energy released from the electrons de-excitation (from CB to ground state inVB), leading to the fluorescent emission shift to the high frequency range. In addition, the fluorescence wavelength can also be tuned flexibly by adjusting the structure and chemical compositions of QDs as mentioned above. These stand out properties make QDs appealing for bio-medical applications including imaging and biosensing [71]. In biosensing systems, QDs, used with or without nano-sized quenchers, are transducers and functionalized with bio-recognition molecules (bio-receptors). Because of the tunable size and broad spectral width, QDs can play as either energy donors or acceptors in the FRET biosensor [72]. Furthermore, due to their high fluorescence intensity, photostability and long lifetimes than conventional organic fluorophores, QDs were also involved in the design of molecular beacons.
QDs can be simply used as fluorescent labels in immunosensors to quantify the biological targets through directly measuring the presence and/or the intensity of the fluorescence. CdTe/SiO2 core-shell structured nanoparticles were labeled with prostate-specific antigen (PSA) detection antibodies for PSA detection. And the fluorescent signals were measured after the specific recognition between PSA and the QD labeled antibodies followed by a magnetic separation to remove unbound QDs. This system represents a typical fluorescent biosensor detecting the presence of QD labels [74]. This strategy design shows great flexibility for employing a variety of fluorescence detectors, e.g., fluorescence spectrometry and handheld UV lamp tests. Furthermore, such design enables not only target quantification but also imaging multiple targets with different QD labels [75].
One of essential challenges to apply QDs in biosensors is immobilization of target recognition biomolecules onto the surface of QDs via stable bonding. In this part, methods for preparing QD-biomolecule conjugates will be presented and modified QDs applied as labels in biosensors are also summarized. Roughly, there are 4 strategies to prepare the QD-based bioconjugates:
Direct binding: proteins and nucleic acids can be immobilized on the QDs surface directly through interactions between the thiol-groups or imidazole- groups with the metal component of QDs, e.g., alkylthiol terminated DNAs are linked with QDs surface directly via dative thiol bond [79].
Conjugation via ligands: QDs can be functionalized firstly by ligands, such as carboxyl groups, hydroxyl groups and amino-groups, then covalently bond to biomolecules [80].
Conjugation via functional shell: QDs are capped with silane shell [81] or copolymers [82], then bond to biomolecules by the functional groups on the outer shell.
Conjugation via specific biological affinity: some types of biological affinity can be used to bond the QDs with biomolecules strongly and specifically, such as biotin-streptavidin interaction [83].
Upconversion fluorescent materials are emerging fluorescent nanoparticles that can convert low frequent exciting light into high frequent emitting light by absorbing two-photons or multi-photons. The luminous mechanism of upconversion nanoparticles (UCNPs) is anti-stokes, which is opposite with the most fluorescent materials, including organic fluorescent dyes, quantum dots, fluorescent proteins, metal complexes, etc [84]. Because of the distinctive luminescence mechanism, UCNPs have some unique advantages, which make up the disadvantage of above other dyes. Firstly, UCNPs have improved biological tissue penetration. Secondly, UCNPs can reduce light damage on biological samples. Thirdly, UCNPs can effectively avoid the disturbance of autofluorescence from biological samples. Therefore, UCNPs have wide applications in biosensing and imaging [85]. The sensing principle of UCNPs-based probe is widely based on fluorescence resonance energy transfer (FRET) between UCNPs (donor) and other down-conversion fluorophores (acceptor). The reaction between UCNPs-based probe and the target biomolecules will trigger or hinder the FRET process, causing the quenching and enhancement of fluorescence for detection.
Electrochemical biosensor is capable of providing specific quantitative or semi-quantitative analytical information using electrochemical transduction elements, e.g., charge-transfer complexes. Low-cost, energy efficient, portable, easy fabrication, and real-time sensing are major advantages of electrochemical biosensing platforms. Among the electrical signal molecules, there are several types of dyes with electrochemical activity, and they will be introduced in this part. In addition, the electrochemical signals generation mechanisms are explained and applications of these dyes as labels in the biosensors are also displayed.
Methylene blue (MB) is a kind of derivative of phenothiazine and widely used a redox indicator and electron transfer medium in electrochemical analysis. For a typical DNA detection using MB labels, the distance between the MB and the electrode surface is adjusted by the change of conformation of the DNA probes labeled with MB, so that the peak current or the change in impedance can indicate the presence of the target DNA and quantitative concentration. This method is simple and versatile, however easy to be influenced by the solution environment. Despite MB, other organic dyes, such as gentian violet, ethyl green, Hoechst 33258 are also utilized in the electrochemical works. They are not as popular as MB, but show good performance in some biosensors.
Organometallic complexes consist of centrally located metal atoms or ions and completely or partly coordinated organic ligands. The organometallic complexes with transition metals have the advantages of strong redox signal, good chemical stability, low toxicity, and high structural flexibility. They interact with biomolecules via the Intermolecular interaction force and electrostatic interaction.
Ferrocene (Fc), is a yellow organometallic complexes with transition metal (Fe) and aromatic ligands (cyclopentadiene rings). Because Fc has two freely rotating cyclopentadiene rings, it can be labeled with the biomolecules, such as DNA via hydrophobic interactions. As an electrical signal molecule, in the combination of bio-receptors and target molecules, Fc generates electrical signals mainly by adjusting the distance between the Fc and the electrode surface to realize the change of electrical signal and achieve the purpose of detection.
K3[Fe(CN)6]/K4[Fe(CN)6], is a pair of dyes with bright red and yellow color, respectively. Mainly, they are used as electron transfer agents in amperometric biosensors, to replac the natural electron transfer agents of the enzymes. In the commercial blood glucose meters, the glucose in the blood reacts with glucose oxidase and K3[Fe(CN)6] fixed on the surface of the test strip to produce gluconic acid and K4[Fe(CN)6]. Applying a constant working voltage to the test strip, K4[Fe(CN)6] is oxidized to K3[Fe(CN)6], generating an oxidation current that is proportional to the glucose concentration.
One of the most commonly used electrochemical biosensor is cadmium selenide (CdSe) QDs, which employ as electrical signal molecules for the labeling of nucleic acid strands [86]. The Pb2+ cleavage ribozyme sequence was modified on the surface of the magnetic beads, and designed an electrochemical biosensor for detecting Pb2+ by using rolling circle amplification reaction and a signal probe labeled with CdS QDs [87]. Based on Ni2+ cleavage ribozyme and CdSe QDs, The Ni2+ was detected and the detection limit was 6.67 nmol/L [88]. As electrical signal molecules, QDs have versatility and low background signal, which has great application prospects.
Graphene quantum dots (GQDs) are actually sheets of graphene with dimensions less than 100 nm with sp2 hybridized honeycomb structures, and their shapes are mostly circular and elliptical, but square and hexagonal QDs are also available. Basically, GQDs are characterized as graphene-like, consisting of C, O, and H as well as carbonyl, carboxyl, hydroxyl, and epoxy groups. GQDs can bind to ssDNA through π-π interactions, but it has no such effect on double-stranded DNA. Park et al. used GQDs as electrical signal substances to detect the Hg2+ concentration by measuring the current generated during the electrochemical reduction of GQDs [89].
Metal–organic frameworks (MOFs) are crystalline materials with an infinitely regular and infinitely expanding periodic network structure formed by the self-assembly of metal ions and organic ligands through coordination bonds, covalent bonds, and weak intermolecular bonds (π-π stacking, van der Waals forces, hydrogen bonding, and other electrostatic interactions, etc.) [90]. MOFs are nanomaterials with good stability, large porosity, and specific surface area that are of great interest in gas storage, drug delivery, and sensors. Due to the intrinsic peroxidase catalytic activity, MOFs can also be used in electrochemical biosensors. Xu et al. constructed a Pb2+ electrochemical biosensor based on the MOFs prepared based on Fe [91], and AgPt nanoparticles are employed to increase its electrical conductivity and electrocatalytic activity, and the obtained sensitivity approaches 0.032 pmol/L. However, even though MOFs have enzymatic activity to improve sensitivity, their synthesis process is very complicated, and the characterization of the modification process is also very critical, so it is not suitable for routine use.
Investigation and evaluation of dyes play a vital role in the process of introduction novel labels and their corresponding sensing methods, which signify opportunities for the development of biosensors. This chapter highlights the utilization of dyes as biosensing labels and some most important sensing mechanisms for biological, biotechnological, and biomedical applications. These designs and applications have been much attracted for in vivo and in vitro analysis due to their high sensitivity and selectivity, fast response, biocompatibility, etc. Further developments in novel synthetic approaches of functional nanomaterials and sensing strategies will accelerate the discovery of unique properties of dyes, which will further improve their applications towards future biosensing platforms.
The authors are grateful to ÅForsk Foundation (grant number, 20-280), Formas (grant number, 2019-01583), STINT (grant number, IB2020-8594) and I Bergh scholarship. Qilu young scholar program of Shandong University (grant number, 11500082063141) is also acknowledged for the financial support.
The authors declare no conflict of interest.
The primary goal of ration formulation in animal production is to offer a balanced diet that supports physiological functions such as growth, maintenance, reproduction, and lactation while also providing energy for physical and metabolic activity [1]. A standard and efficient feed formulation must include all the classes of feedstuffs (Animal Nutrition Group, India) [2] as provided in Figure 1.
Different classes of standard feedstuff must be included in the feed formulation according to animal nutrition group, India.
A concentrate is a feed or feed mixture that provides increased levels of primary nutrients (protein, carbohydrates, and fat) while containing less than 18 percent crude fiber (CF) and low moisture. These are high in nitrogen-free extract (NFE) and Total Digestible Nutrients (TDN) and low in crude fiber [3]. There are classified into two categories: energy-rich concentrates and protein-rich concentrates, based on the content of crude protein (CP). When the crude protein content of dry concentrates is less than 18 percent, they are categorized as energy-rich concentrates, and when the CP value is greater than 18 percent, they are defined as protein-rich concentrates [4, 5].
Roughages are heavy foods that contain substantially less digestible material, such as crude fiber greater than 18% and a low TDN content (about 60%) on a dry basis. Roughages differ in the level of protein, mineral, and vitamin composition. Some roughages, particularly legumes, are good suppliers of calcium and magnesium [6]. The phosphorus concentration is likely to be moderate to low, whereas the potassium content is likely to be high, these concentrations are affected by the plant species, soil, and fertilization strategies all have an impact on trace minerals. Roughages are categorized into two classes based on moisture content: dry and green or succulent roughages [7]. Green roughages often have 60–90 percent moisture, while dry roughages have just 10–15 percent moisture. Green roughages are divided into several types for ease of use, including pasture, produced fodder crops, tree leaves, and roots. Based on the nutritional content and preparation methods, dry roughages have been further categorized as hay and straw [8].
Minerals available in the feeds are of different types i.e., Micro minerals, macro minerals and chelated minerals. Microminerals, also known as trace minerals, are needed in milligrams (mg) or microgram (g) quantities [9]. They’re found in trace amounts in animal tissues and feeds. They’re frequently found in enzyme cofactors and hormones. Cobalt, iodine, zinc, copper, manganese, and selenium are examples of micro or trace minerals. Macro-minerals play a specific role in the formation and function of the animal’s body. Animals require the following seven macro-minerals: calcium (Ca), phosphorus (P), sodium (Na), magnesium (Mg), potassium (K), sulfur (S), chlorine (Cl) [10]. Chelated minerals are a class of organic minerals that are divided into proteinates, chelates, and other complexes based on their molecular structure [11]. A chelated mineral is one that has two or more chemical interactions with peptides or amino acids, such as copper or zinc. Each one has a different level of absorption and effectiveness.
The National Research Council has studied nutrient requirements based on several criteria such as dry matter intake (DMI), total digestible nutrients (TDN), crude protein (CP), metabolic energy (ME), calcium (Ca), phosphorus (P), and other elements that affect intake and techniques of prediction [12]. The entire weight of feed minus the weight of water in the feed is expressed as a percentage and is known as dry matter. In feeding studies, dry matter intake is determined by weighing the whole ration supplied and the amount of feed left by the animal [13]. The term “total digestible nutrients” stems from an old system of calculating available energy in feeds and animal energy requirements using a complex calculation of measured nutrients. The whole amount of protein present, determined from the total nitrogen available, is referred to as a crude protein. The percent nitrogen is multiplied by 6.25 to get the percent protein. The digestible energy intake minus the energy in the urine minus the energy in the gaseous result of digestion equals the metabolizable energy. Calcium is required for bone formation, neuron function, and the production of milk and eggs in animals. Phosphorus is also included in a wide range of co-enzymes, nucleic acids, proteins and amino acids [14].
It is essential to know the significance of these nutrients in animal feed. Animal disease control, as well as feed and fodder shortages, are the most pressing issues in animal husbandry. Farmers frequently encounter the following issues.
1. Nutrient requirement for the livestock animal,
2. The amount of feed that must be supplied every day to boost productivity,
3. Feed ingredient costs must be kept under control.
Animal nutrition is necessary for livestock production to be effective. Animal feed efficiency and growth rate can both benefit from good nutrition. Diets that meet the demands of animals must be provided.
This work used goats to fully understand nutritional needs and feed composition through the use of a visual basic application. The three phases of the study are explained in this chapter, the first phase is the selection of feeds and understanding their nutrient composition. The second part involves determining which nutrients are important for animals and creating nutrient equations. The third phase entails the establishment of a linear programming model, followed by the design of the interface.
Goats can grow well and produce maximum milk if balanced and nutritious food is fed [15]. A balanced ration should contain digestible nutrients, vitamins, and minerals, including concentrate feeds and green and dry roughages. The feed list was created based on the most commonly used feeds, fodders and its nutrient composition was used as per ICAR (2013) given in Table 1.
sl. No | Name of the ingredients | Cost* | DM % | CP % | TDN % | |
---|---|---|---|---|---|---|
Roughages | 1 | Bajra -Napier Green grass | 0.5 | 20 | 8 | 52 |
2 | Maize Green fodder | 0.5 | 20 | 8 | 60 | |
3 | Multicut sorghum green fodder | 1 | 90 | 7 | 50 | |
4 | Lucerne Green Fodder | 0.7 | 20 | 15.8 | 60 | |
5 | Wheat straw | 1 | 90 | 3.3 | 42 | |
6 | Maize stover | 0.9 | 90 | 3 | 42 | |
7 | Ragi Straw (Dry) | 0.9 | 90 | 6 | 42 | |
8 | Cereal straw | 1 | 90 | 3.5 | 40 | |
Concentrate | 10 | Maize | 1.7 | 90 | 8.1 | 79.2 |
11 | Wheat | 1.8 | 90 | 8 | 75 | |
12 | Wheat Bran | 2.2 | 75 | 12 | 70 | |
13 | Soya DOC | 3 | 90 | 42 | 70 | |
14 | cotton seed | 2.2 | 90 | 16 | 72.2 | |
15 | Cotton DOC | 1 | 90 | 18 | 45 | |
16 | Copra DOC | 3 | 90 | 22 | 70 | |
17 | Concentrate Mix Type I | 3 | 90 | 22 | 75 | |
18 | Concentrate mix Type II | 2.5 | 90 | 16 | 70 | |
Minerals | 19 | Urea | 1 | 95 | 287.5 | 0 |
20 | MM (Mineral Mixture) | 6 | 90 | 0 | 0 | |
21 | DCP | 3.8 | 90 | 0 | 0 | |
22 | Trace Mineral Mixture | 3.5 | 98 | 0 | 0 | |
23 | Salt | 0.5 | 90 | 0 | 0 |
Composition of most commonly used feeds, fodders and its nutrient composition (DM, CP, TDN) was used as per ICAR (2013) and present cost of the ingredients*.
Cost of the ingredients can be changed in the application.
Nutrient requirements are estimated based on the Indian Council of Agricultural Research (ICAR) (2013) and it was programmed in Excel VBA. A balanced ration should meet the nutrient requirement. If the growing goat does not get the nutrients, it will affect milk yield and weight at the time of slaughter [16, 17]. The nutrient requirements for the growing goats are given in Table 2. There are three major factors of balanced ration: DMI, CP and TDN.
Body weight (BW) (kg) | Body weight gain (g/d) | Daily Dry Matter Intake (DMI) | Energy Requirements | Protein Requirements | ||
---|---|---|---|---|---|---|
Kg | % BW | TDN kg/d | ME | CP | ||
Mcal/d | g/d | |||||
5 | 0 | — | — | 0.101 | 0.36 | 19 |
5 | 25 | 0.2 | 4 | 0.141 | 0.51 | 31 |
5 | 50 | 0.21 | 4.2 | 0.181 | 0.66 | 42 |
5 | 75 | — | — | 0.221 | 0.8 | 53 |
5 | 100 | — | — | 0.262 | 0.95 | 65 |
10 | 0 | — | — | 0.169 | 0.61 | 33 |
10 | 25 | 0.36 | 3.6 | 0.21 | 0.76 | 44 |
10 | 50 | 0.37 | 3.7 | 0.25 | 0.9 | 55 |
10 | 75 | 0.35 | 3.5 | 0.29 | 1.05 | 67 |
10 | 100 | — | — | 0.33 | 1.19 | 78 |
10 | 125 | — | — | 0.371 | 1.34 | 89 |
10 | 150 | — | — | 0.411 | 1.48 | 100 |
15 | 0 | — | — | 0.229 | 0.83 | 44 |
15 | 25 | 0.45 | 3 | 0.27 | 0.98 | 56 |
15 | 50 | 0.5 | 3.3 | 0.31 | 1.12 | 67 |
15 | 75 | 0.5 | 3.3 | 0.35 | 1.26 | 78 |
15 | 100 | — | — | 0.39 | 1.41 | 89 |
15 | 125 | — | — | 0.431 | 1.56 | 101 |
15 | 150 | — | — | 0.471 | 1.7 | 112 |
20 | 0 | — | — | 0.285 | 1.03 | 55 |
20 | 25 | 0.58 | 2.9 | 0.325 | 1.17 | 66 |
20 | 50 | 0.6 | 3 | 0.365 | 1.32 | 78 |
20 | 75 | 0.62 | 3.1 | 0.405 | 1.47 | 89 |
20 | 100 | 0.62 | 3.1 | 0.446 | 1.61 | 100 |
20 | 125 | — | — | 0.486 | 1.76 | 111 |
20 | 150 | — | — | 0.526 | 1.9 | 123 |
25 | 0 | — | — | 0.337 | 1.22 | 65 |
25 | 25 | 0.68 | 2.7 | 0.377 | 1.36 | 76 |
25 | 50 | 0.71 | 2.8 | 0.417 | 1.51 | 88 |
25 | 75 | 0.73 | 2.9 | 0.457 | 1.65 | 99 |
25 | 100 | 0.74 | 3 | 0.498 | 1.8 | 110 |
25 | 125 | 0.71 | 2.8 | 0.538 | 1.94 | 121 |
25 | 150 | — | — | 0.578 | 2.09 | 133 |
30 | 0 | — | — | 0.386 | 1.39 | 75 |
30 | 25 | 0.77 | 2.6 | 0.426 | 1.54 | 86 |
30 | 50 | 0.8 | 2.7 | 0.466 | 1.69 | 97 |
30 | 75 | 0.83 | 2.8 | 0.507 | 1.83 | 108 |
30 | 100 | 0.84 | 2.8 | 0.547 | 1.98 | 120 |
30 | 125 | — | — | 0.587 | 2.12 | 131 |
30 | 150 | — | — | 0.627 | 2.27 | 142 |
Dry matter intake, energy and protein requirements of Indian goat based on body weight (kg) and body weight gain (g).
Dry Matter Intake (DMI)(kg/d): Dry matter intake is dependent upon many factors like fodder quality and quantity, climate condition, and nutrient requirement of goat. The DM requirements of goats for different body weights and growth rate functions are different [18]. The dry matter requirement is calculated based on body weight and average daily gain as per the Indian standard [19]. The total DMI intake calculated is in terms of ‘kg’ and the formula used in VBA code is given below:
From the Table 1. Will find CF1 (common factor 1) for 5, 10, 15, 20, 25, 30 kg with respective metabolic body weight (BW^0.75). the formula of CF1 is given below in eq (1)
CF1 values for 5, 10, 15, 20, 25, 30 kg are 30.21, 30.05, 30.04, 30.14, 30.14, 30.11 respectively. As we can observe CF1 values for 5 kg is 30.21 and values for 10 and 15 kg are taken as 30.04 (average), for more than 15 kg can be taken as 30.13(average of 3).
Then we find CF2 (common factor 2) with respective average daily gain (ADG) by the following formula (eq (2))
CF2 values are found to be 1.6. Therefore (see eq (3))
ME (Mcal/d) can be found by using the following formula (eq (4))
Where 0.28 is the common factor.
From the Table 1. Will find CF1 (common factor 1) for 5, 10, 15, 20, 25, 30 kg with respective metabolic body weight (BW^0.75). the formula of CF1 is given in eq (5).
CF1 values for 5, 10, 15, 20, 25, 30 kg are 5.68, 5.87, 5.77, 5.82, 5.81, 5.85 respectively. As we can observe CF1 values for 5 kg is 5.68 and values for 10 kg–30 kg are taken as 5.82 (average),
Then we find CF2 (common factor 2) with respective average daily gain (ADG) by the following formula (eq (6))
CF2 values are 0.46 for less than 10 kg and 0.44 for greater than 10 kg. Therefore (see eq (7))
The developed tool (RBT) uses VBA (Visual Basic Application) as front end and back end as excel. It is a simple excel file that is saved as .xlsm form and integrated with VBA code [25]. The user form or first page asks for input data, mainly body weight (BW) in kg and expected average daily gain (ADG) in g, depending upon which, it will calculate the minimum nutrient requirements, i.e., total DMI in ‘Kg’, CP in ‘g’, TDN in ‘g’. Then should be selected from the list on the second page from roughages, concentrate, and minerals. Once this information is fed, tool RBT will solve for minimization of cost with DMI, TDN, CP as constraints. The tool RBT followed the following linear programming model [26]. (see eq (8))
Objective Function:
DMI
TDN & CP:
Feeds:
Where
Ration balancing tool for growing goat – a Microsoft Excel VBA based software can calculate the nutritional requirements for animals, such as dry matter intake (DMI), crude protein (CP), total digestible nutrient (TDN), and metabolizable energy (ME), for which equations are derived by using common factor method based on the data of ICAR (2013). The table values of nutrients as per ICAR (2013) and calculated values as per software have high
Comparison of table values of DMI (kg/d) as per ICAR (2013) and calculated values as per software having high R^2 values.
Comparison of table values of TDN (g/d) as per ICAR (2013) and calculated values as per software have high R^2 values.
Comparison of table values of CP (g/d) as per ICAR (2013) and calculated values as per software have high R^2 values.
Once the nutrients requirements are found, the application asks the user to select the available feeds which are listed in the application. Then it will provide a balanced ration using LP model [27]. The expert nutritionist has examined the created application in NIANP, and the results of some specific animal categories (Goat 1 and Goat 2) are given in Table 3. The developed RBT will find the least-cost ration with the consumer selected feed without breaching the nutrient requirement shown in the sixth column of Table 3.
Animal Details | Nutrient Requirement | Feeds Selected | Suggested feed quantity with price and total cost | Nutrients from feed | |
---|---|---|---|---|---|
Weight (Kg): 15 ADG (g/d):75 | DMI(Kg):0.5 CP (g):77.74 TDN(g):349.5 ME(Mcal):1.24 | Name | Quantity | Cost (Rs) | DMI(Kg):0.54 CP (g):77.74 TDN(g):349.5 ME(Mcal):1.26 |
Maize Green fodder | 0.04 | 0.55 | |||
Multicut sorghum green fodder | 0.17 | 0.55 | |||
Ragi straw (dry) | 0.03 | 0.24 | |||
Wheat | 0.22 | 3.91 | |||
Soya DOC | 0.09 | 3.87 | |||
Concentrate Mix Type 1 | 0.08 | 2.20 | |||
MM | 0.01 | 0.61 | |||
Salt | 0.01 | 0.04 | |||
Total | 0.63 | 11.97 | |||
Weight (Kg): 20 ADG (g/d):100 | DMI(Kg):0.60 CP (g):99.51 TDN(g):444.76 ME(Mcal):1.58 | Multicut sorghum green fodder | 0.2 | 0.67 | DMI(Kg):0.67 CP (g):99.52 TDN(g):444.76 ME(Mcal):1.61 |
Maize | 0.14 | 3.18 | |||
Wheat | 0.16 | 2.88 | |||
Soya DOC | 0.12 | 5.26 | |||
Concentrate Mix Type I | |||||
MM | 0.01 | 0.75 | |||
Salt | 0.01 | 0.05 | |||
Total | 0.73 | 15.48 |
Feed formulation for two different goats based on DMI, CP, TDN and ME by RBT depending on the weight and average daily gain.
As per Table 3, It is observed that two different categories of goat listed for validation, DMI, CP, TDN and ME criteria, are determined depending on both the weight and average daily gain as in the second column of Table 3. The developed RBT will find the least-cost ration with the consumer selected feed without breaching the nutrient requirement shown in the fifth column. To find the optimal solution, the RBT uses the Excel solver. The Excel Solver is efficient in obtaining feasible solutions nonlinear model for goats and increased daily gain and milk yield [28]. The nutrients TDN and CP required for growing goat according to Mandal, 2005 [29] for goat 1 with the body weight of 20 kg and an ADG of 75 g are 351 g and 79 g, respectively, for goat 2 with the body weight of 20 kg and 100 g of ADG, the requirements are 446 g and 100 g respectively. The nutrients TDN and CP calculated by developed application for Goat 1 are 349.5 g and 77.74, and for Goat 2 are 444.7 g and 99.51 g. There is a very small difference 1.5 g (0.4%) and 1.26 g (0.3%) in TDN and CP for goat 1, for goat 2 TDN and CP difference is 1.3 g (1.6%) and 0.49 g (0.49%) between RBT and Mandal et al. (2017). The required nutrients for two different goat categories and calculated by balanced ration are shown in Figures 5 and 6 for goat1 and 2, respectively.
Graphical representation of required vs. calculated nutrients by balanced ration for goat 1.
Graphical representation of required vs. calculated nutrients by balanced ration for goat 2.
From the above studies and evaluation, it can be confirmed that the calculated values for DMI, TDN and CP are almost equal to the values of ICAR (2013). A Ration Balancing Tool (RBT)” is developed using Excel VBA, which gives a balanced ration for the goats with the available ingredients that satisfy all the nutrient requirements. Many software programs are available to customize ration for the lowest cost [30]. However, scanty applications are available for goat least-cost ration formulation. This study explains how the application is exceptional and more efficient and convenient compared to all other software programs, most of which are not user-friendly, and farmers must rely on expert assistance to implement it. For the commercial business reason, many software programs are developed for the client, wherein small dairy farmers still have to rely on specialists for optimized rationing. This tool is very simple to execute and user friendly. It is designed to determine the nutritional requirement of goats, depending on their weight and daily gain and to optimize goat ration at least cost.
Screenshot of the first page of developed VBA application showing the introduction, methodology and help sections.
Screenshot of the second page developed VBA application where the user can input the basic data.
Screenshot of the third page developed VBA application where users can select feeds from roughages, concentrate and minerals.
(a) Screenshot of the sub page developed VBA application where user can add new feed. (b) Screenshot of the fourth page developed VBA application where user can refine the feed.
1. Single goat ration cost.
2. Cost of 100 kg ration on dry matter basis.
3. Ration cost for the number of goats available.
Printouts can be taken for all the results.
The features of the developed application are as follows, firstly Data Maintenance; if no feed is listed, the feed with nutrient composition can be uploaded by the consumer while selecting the feed. It allows the consumer to reasonably apply the feed available locally and reduce the cost. Consumers can get optimized ration in maximum effective steps by selecting the animal data and picking the feeds and then tapping on the “Solve” icon to get the result as it is user-friendly. For Display and printing, after the solution is found, there is an option for the result to be printed on a fed basis with feed quantity and total DM intake per kg. System requirements are also minimal as All MS Office versions can be used, and no special hardware or RAM is needed. The macros and solver options in VBA reference need to be enabled. The application provides the result in three ways: cost of single goat ration: Here, the total DMI is provided for one goat. This will help the consumer get an optimized ration and provide the right amount of roughage, concentrate, and minerals to be included in the ration. Finally, the price of each feed is given in the result. Cost of 100 kg ration on dry matter basis: Here, it estimates 100 kg at a time, which can be fed to goats at periodic intervals. The amount of roughage, concentrates, and minerals to be added to make 100 kg and its cost will be shown. Ration cost for the number of goats available: Here, the ration will be estimated on a dry matter basis for the number of available goats. The output is given in Figure 11.
Screen shots of output result estimated on a dry matter basis for the number of available goats.
This study showed that how the excel VBA can be used to analyzing the nutrient requirement and producing a balanced ration for livestock (goat) are fundamental aspects of reducing goats’ feeding cost. Hence Excel Visual Basic Application (VBA) has been developed. Developed ‘RBT ‘for beneficial for dairy farmers, which is based on a linear programming model. The ICAR (2013) table values for nutrients and the software-calculated values have high R2 values (DMI-0.989; TDN- 1; CP-0.999). It can be confirmed from the aforementioned studies and evaluations that the computed values for DMI, TDN, and CP are nearly identical to the ICAR (2013) values. Just by giving the goat’s minimum input, the application will calculate the nutrient requirement and the balanced ration at the lowest cost. Adding extra feed allows the user to add the feed available, which can lower the cost. The answer produced by the application is verified by a nutritionist at the National Institute of Animal Nutrition and Physiology (NIANP), Bangalore. Hence, it is concluded that even this application could be used quite effectively by dairy farmers. By understanding the nutrient requirements, the same can be developed for other livestock animals such as cattle, buffalo, and pigs.
Raw data were generated at ICAR-National Institute of Animal Nutrition and Physiology. Derived data supporting the findings of this study are available from the author Prof. Rajendran on request. The authors thank all co-workers for their help and cooperation in this trial. Vishal Patil Conceptualized developed Methodology Data Collection, wrote the manuscript, Radha Gupta and Rajendran D Supervised and Validated. Ravinder Singh Kuntal assisted in Writing- Reviewing and Editing.
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Guadalajara International Book Fair
\n\n26 November - 04 December 2022, Guadalajara, Mexico
\n\nIntechOpen Represented by LSR Libros Servicios y Representaciones SA de CV
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. 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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. 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She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. 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