\r\n\tThe Japanese were revolutionizing quality improvement. As a result, Japan adopted a "total quality" approach to its strategies. In the United States, Total Quality Management (TQM) encompasses not only statistics but also approaches that encompass the entire organization. There were several subsequent quality-management initiatives. \r\n\tIn 1986, Motorola developed Six Sigma to improve its business processes by minimizing defects. A philosophy that views all work as a process, which can be identified, measured, analyzed, improved, and controlled. Generally, "Six Sigma quality" is an indicator that a process is well controlled.
\r\n
\r\n\tLean manufacturing (1988), also known as just-in-time manufacturing, derives from Toyota's 1930 operating model "The Toyota Way." Lean describes a set of management practices that reduce waste and increase productivity. \r\n\tThe ISO 9000 series of quality-control standards appeared in 1987. ISO 9001 integrates a process-oriented approach into enterprise management based on the plan-do-check-act method. The quality movement has matured as we enter the 21st century. ISO 9000 was revised in 2000 to emphasize customer satisfaction. The fifth edition of ISO 9001, published in 2015, emphasizes risk-based thinking to improve the application of the process approach. In addition to the manufacturing sector, quality has moved into service, healthcare, education, and government. For example, through standards such as ISO/IEC 17025 for testing and calibration laboratories and ISO 15189 for medical laboratories. \r\n\tMore recently, it has been recognized that the Fourth Industrial Revolution, Industry 4.0, best defines the present industry model. As its part, "Quality 4.0" refers to the future of quality and organizational excellence.
\r\n
\r\n\tThe book will aim to introduce a comprehensive overview of the up-to-date models used in quality management systems by experts in the field.
",isbn:"978-1-80356-729-7",printIsbn:"978-1-80356-728-0",pdfIsbn:"978-1-80356-730-3",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"7c2744454ba90e8d6cf507e167cc3779",bookSignature:"Dr. Paulo Pereira and Dr. Sandra Xavier",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11527.jpg",keywords:"Leadership, Customer Focus, Improvement, Process Approach, Planning, CAPA, Audit, Management Review, Evaluation, Lean Sigma, DMAIC, DMADV",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 24th 2022",dateEndSecondStepPublish:"June 8th 2022",dateEndThirdStepPublish:"August 7th 2022",dateEndFourthStepPublish:"October 26th 2022",dateEndFifthStepPublish:"December 25th 2022",remainingDaysToSecondStep:"21 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Pereira received his Ph.D. from the Catholic University of Portugal. He has over 20 years of experience as a consultant and auditor of quality management systems, and over 16 years of experience as a quality manager. He has been recruited as a quality and laboratory expert for seminars and professional laboratory meetings throughout Europe, Africa, and South America. Currently, he is the head of the R&D Department at the Portuguese Institute of Blood and Transplantation; a CLSI and EURACHEM fellow.",coeditorOneBiosketch:"Dr. Xavier received her Ph.D. from the University of Lisbon, Portugal. She has extensive experience in teaching and managing quality systems, and is a member of several Scientific Commissions and editorial boards.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"178637",title:"Dr.",name:"Paulo",middleName:null,surname:"Pereira",slug:"paulo-pereira",fullName:"Paulo Pereira",profilePictureURL:"https://mts.intechopen.com/storage/users/178637/images/system/178637.jpeg",biography:"Dr. Pereira received his Ph.D. in Biotechnology from the Catholic University of Portugal. He has been recruited as a quality and laboratory expert for seminars and professional laboratory meetings throughout Europe, Africa, and South America. He has more than twenty-five years of experience working in medical laboratories, having held key scientific leadership roles: 15+ years as a senior researcher; 10+ years as a consultant for a metrology laboratory based on ISO/IEC 17025 specifications and related standards; 20+ years as a consultant and auditor of quality management systems based on ISO 9001, ISO/IEC 17025, and ISO 15189 standards; 16+ years as the quality manager in the Portuguese Institute of Blood and Transplantation, including more than 6 years in national coordination; and 6+ years as a professor of Quality Assurance. Currently, he is the head of the R&D Department at the Portuguese Institute of Blood and Transplantation, Lisbon, Portugal. Dr. Pereira is the author of several peer-reviewed scientific articles and indexed books and chapters. He is an editor for several books. He serves as a member of several editorial boards. He is a member of the Clinical Laboratory and Standards Institute and Eurachem. 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She is a member of several Scientific Commissions of various meetings.",institutionString:"School of Nursing of Lisbon",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"453622",firstName:"Tea",lastName:"Jurcic",middleName:null,title:"Ms.",imageUrl:"//cdnintech.com/web/frontend/www/assets/author.svg",email:"tea@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"7710",title:"Quality Management and Quality Control",subtitle:"New Trends and Developments",isOpenForSubmission:!1,hash:"226e5d555cafed8a4d1b410959863661",slug:"quality-management-and-quality-control-new-trends-and-developments",bookSignature:"Paulo Pereira and Sandra Xavier",coverURL:"https://cdn.intechopen.com/books/images_new/7710.jpg",editedByType:"Edited by",editors:[{id:"178637",title:"Dr.",name:"Paulo",surname:"Pereira",slug:"paulo-pereira",fullName:"Paulo Pereira"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10198",title:"Response Surface Methodology in Engineering Science",subtitle:null,isOpenForSubmission:!1,hash:"1942bec30d40572f519327ca7a6d7aae",slug:"response-surface-methodology-in-engineering-science",bookSignature:"Palanikumar Kayaroganam",coverURL:"https://cdn.intechopen.com/books/images_new/10198.jpg",editedByType:"Edited by",editors:[{id:"321730",title:"Prof.",name:"Palanikumar",surname:"Kayaroganam",slug:"palanikumar-kayaroganam",fullName:"Palanikumar Kayaroganam"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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1. Introduction
Ethiopia is not only rich in sheep population but also rich in sheep genetic diversity, which developed by natural selection and potential genetic resources of sheep breeds [1]. In the highlands of the country, about 75% of sheep population are found, while the remaining 25% are distributed in the lowlands [2]. Sheep production is a major component of the livestock sector in Ethiopia, owing to the large population of 30.70 million sheep are estimated to be found in the country, out of which about 72.14% are females, and about 27.86% are males [3]. The small ruminants account for 40% of cash income earned by farm households, 19% of the total value of subsistence food derived from all livestock production, and 25% of total domestic meat consumption [4]. Smallholder sheep production is the major source of food security serving a diverse function, including cash income, savings, fertilizer, socio-cultural functions and fiber production. Sheep are particularly important for farmers in the subalpine highlands and pastoralist/agropastoralist where crop production is unreliable. Moreover, despites its socio-cultural importance, sheep resources significantly contributed for foreign currency earning accounting for the live animal exports [1].
The cool highland sheep production systems in most highland areas are characterized by erratic and unevenly distributed rainfall, recurrent drought, and scarcity in livestock feeds and feed that is poor in quality [5]. In those production environments, the role of sheep in supporting the livelihood of smallholder farmers is increasing due to recurrent crop failure [5, 6]. However, the sheep flocks are managed under traditional extensive systems with no or minimal inputs and improved technologies, which results in low productivity. They depend on natural pasture and fibrous crop residues for their survival, growth and reproduction. The available natural pasture lands are overloaded with livestock beyond optimum carrying capacity that has resulted in overgrazing and land degradation [7, 8]. This indicated the critical need of supplemental feed during the feed-deficient period and wise management of communal and private natural pasture grazing. A limited supply of nutrients in the sheep’s diet can lead to weight loss, low fertility, high mortality, increased risk of disease and poor wool growth. Sheep need a balanced diet containing energy (fat and carbohydrates), protein, vitamins, minerals, and water. Sheep and goat production in Ethiopia suffers feed shortages at all levels with an estimated 40% deficit in the national feed balance. This is aggravated by seasonal availability of forage and crop residues in the highlands and by recurrent and prolonged drought in the lowlands.
Therefore, the study was accomplished on, assessment of productive performance through on-station feedlot based and natural pasture grazing weight gain performance and carcass yield characteristics evaluation of indigenous Wollo highland sheep breed and their F1 crossbreds with 75% Awassi and pure indigenous Washera breed rams.
The specific objectives of the study are:
to evaluate on-station feedlot weight gain and carcass yield characteristics of Wollo highland sheep and their F1 crossbreds of Awassi and Washera sheep breeds.
to assess natural grass grazing value as basal diet for the study breeds supplemented by concentrated feed.
2. Material and methods
2.1 Description of the study area
This research was conducted from 2018 to 2019 in the two selected areas of Dessie Zuria and Kutaber districts in South Wollo Zone of Amhara Region, Ethiopia. The geographical location of South Wollo Zone is delimited with North Shewa and Oromia region in the Southern part, East Gojjam in the West, South Gondar in the Northwest, North Wollo in the North, Afar Region in the Northeast and Argobba district of the Oromia Zone in the Eastern part (Figure 1).
2.2 Experimental design and treatments
A 3 × 2 factorial experimental design arrangement of three genotype and two feeding type factors with six treatment levels (three genotypes by two feeding type’s combinations) and six replications were used. The three genotypes belonging to 50% Awassi F1 crosses, 50% Washera F1 crosses and 100% local Wollo highland lambs were grouped in to three by their genotypes and in to two by their feeding types of supplemented and non-supplemented groups for each genotypes. The supplemented and non-supplemented feeding types randomly assigned for each 36 experimental animals.
Both supplemented and non-supplemented groups grazed for 8 hours/day as a basal diet with rotational grazing system and animal holding of 36 sheep/0.5 ha paddock/day. The supplemented group fed at the rate of 1% of their body weight/day of concentrate mix diet, whereas the non-supplemented group fed only natural pasture grazing area for 8 hours/day from 8:00 AM to 5:30 PM with a 1 hour rest from 12:30 AM to 1:30 PM and had free access of drinking water.
2.3 Experimental animals grazing management
The grazing land characterized by both annual and perennial grass such as Cyperus rotundus, Dactylis glomerata Cynodon nlemfuensis, Cynodon dactylon, Cyperus polystachyos and Urochloa brizantha (Table 1). The size of natural pasture grazing area was 2.5 ha of land and that sub-divided into five paddocks with each individual paddock size was 0.5 ha.
Figure 1.
Description of the study area.
Local name
Scientific name
Growth form
Akirma
Cynodon nlemfuensis
Grass—perennial
Tult
Asarum canadense
Herb—annual
Sindedo
Urochloa brizantha
Grass—perennial
Serdo
Cynodon dactylon
Grass—annual
Gicha
Cyperus rotundus
Grass—annual
Gazia
Dactylis glomerata L.
Grass—perennial
Arintata
Trifolium repens
Herb—annual
Others
—
—
Muja
Snowdenia polystachya
Grass—annual
Gudign
Dichondra repens
Herb—annual
Ketema
Cyperus polystachyos
Grass—perennial
Bare land
—
—
Table 1.
Species composition of private owned natural pasture grass land.
2.4 Body weight gain and linear body measurements
Lambs were weighed at 15 days of interval for 1 year in the last week of each month using a 0.1 kg precision scale. Lambs were weighed at birth and fortnightly thereafter up to weaning. After weaning at the age of about 90 days they were weighed in 15 days interval together with the rest of the flock. Lamb body weights were adjusted by age.
The average daily weight gain (ADG) was calculated using the following formula at on-farm growth performance study:
ADG=dW2Kg+W1KgA∗1000E1
where ADG g = average daily gain in gram, W1 kg = birth weight or weight at the preceding age, W2 kg = weight at a given age, and A = age in days or days between weighing dates.
Average daily gain was calculated for the following stages of growth: (a) pre-weaning weight average daily gain (PreADG) ADG = birth to 90 days of age, (b) post-weaning weight average daily gain (PoADG) = birth to 365 days of age, and (c) weaning weight = at average body weight at 90 days.
Average daily weight gain of ram lambs in the on-station growth performance evaluation was also calculated using the following formula:
ADG=FWTKg+IWTKgAD∗100E2
where FWT = final body weight, IWT = initial body weight, and D = number of fattening days.
Linear body measurements were taken together with 3 months of interval measurements (from 3 months of age to 12 months). All body measurements were taken with a measuring tape in centimeter and measured to the nearest 0.5 cm. Linear body measurements traits were taken: (a) heart girth is the circumference of the chest posterior to the forelegs at right angles to the body axis, (b) wither height is the highest point measured as the vertical distance from the top of the shoulder to the ground, (c) body length is the distance between the crown and the sacrococcygeal joint, (d) tail width is directly behind the tuber ichiad, and (e) tail circumference is directly behind the tuber ichiad.
Model 1. On-station growth of initial and final body weight, average daily gain (ADG) of ram lambs (9 months–365 days of age):
Yijklm=μ+Bi+Fl+Bi×Flijm+eijklmE3
where Yijklm = average daily gain (ADG) and body weight change, μ = overall mean, Bi = fixed effect of the ith breed (i = Awassi F1 crossbred, Washera F1 crossbred and local Wollo highland breed), Fl = fixed effect of the feeding type (1 = supplemented, 2 = non-supplemented), (Bi × Fl)il = breed by feeding type interaction effect and eil = effect of the nth random error.
Model 2. Weight and linear body measurements of male lambs (90–365 days of age):
Yij=μ+Bi+Btj+eijE4
where Yij = body weight and linear body measurements at 90, 180, 270 and 365 days of age, μ = overall mean, Bi = fixed effect of the ith breed (i = Awassi F1 crossbred, Washera F1 crossbred and local Wollo highland breed), Btj = fixed effect of the jth birth type (j = single, twins), eij = effect of the oth random error.
Model 3. Body weight gain, carcass and non-carcass parameters:
Yijk=μ+Bi+Fj+Wk+eijk,E5
where Yijk = body weight gain, carcass and non-carcass parameter, μ = mean, Bi = effect of the ith breed (i = Awassi F1 crossbred, Washera F1 crossbred and local Wollo highland breed), Fj = the fixed effect of feeding type (j = supplemented, non-supplemented), Wk = the random effect of body weight (k = birth weight, pre-weaning weight ADG, weaning weight, post-weaning weight ADG and yearling weight, empty body weight, pre-slaughter weight), eijk = effect of the kth random error.
2.5 Data analysis
According to a 3 × 2 factorial statistical designs of the breed and diet as main effects and the PROC GLM of multivariate analysis package of the SAS Windows 9.0-2004 system used for those data fitted with the main factors of breed, feeding type, sex, birth type and parity effects on body weight gain response variable in the model. Initial body weight was also used as a covariate factor in the model to control the residual effects of initial body weight on consecutive rate of body weight gain. The dependent variables include body weight, average daily weight gain, survival rates, linear body measurements, reproductive traits and carcass yield characteristic parameters were considered in the GLM multivariate analysis of variance. The stepwise procedure of Pearson correlation of the SAS system was used to see the effects of association between body weight and linear body measurement traits. Tukey’s standardized range significance test was used to compare the different groups of mean.
3. Results
3.1 Effects of genotype and supplementation feed on ram lambs growth rate
Genotype and supplementation diet effect on ram lambs’ average body weight and their daily weight gain is presented in Table 2. Initial body weight had significant (p < 0.05) difference between genotypes and used in the covariate analysis model to avoid its residual effect on consecutive body weight gain and to quantify the genotype effect. However, it has non-significant difference within genotypes. The between and within genotype variations were continued throughout 10, 20 and 30 days experimental period except supplemented Washera F1 crossbreds and Wollo highland breed lambs and which were significantly higher than their non-supplemented group at 10 and 20 days treatment period, respectively. Despite the fact that at 30, 40, 50 and 60 days of feed treatment period the supplemented group of Wollo highland breed lambs had non-significant differences with both supplemented and non-supplemented Washera crossbred lambs and between breed variation eliminated. At 40 and 50 days, treatment period, except Wollo highland lambs the other genotypes have insignificant differences between supplemented and non-supplemented groups. Conversely, at 60 days of treatment period supplemented Wollo highland breed lambs had non-significant variation with both supplemented and non-supplemented Washera F1 crossbred lambs and vice versa. Awassi F1 crossbred lambs significantly (p < 0.05) higher average weight gain than both Wollo highland and Washera F1 cross ram lambs throughout the experimental period (Table 2).
Awassi genotype
Wollo genotype
Washera genotype
ABW (kg)
T1
T2
T1
T2
T1
T2
Sig.L
IBW
31.6 ± 1.0a
31.5 ± 0.8a
21.9 ± 0.7b
21.4 ± 0.5b
26.4 ± 0.7c
26.6 ± 0.7c
***
10 days
33.4 ± 0.9a
34.0 ± 0.9a
26.9 ± 0.9b
24.5 ± 0.9b
29.0 ± 0.5c
27.5 ± 0.5d
*
20 days
33.3 ± 1.1a
34.1 ± 1.1a
26.6 ± 1.1c
24.2 ± 1.1b
28.8 ± 0.6c
26.9 ± 0.6c
*
30 days
36.7 ± 1.3a
36.9 ± 1.3a
28.4 ± 1.3b,c
26.3 ± 1.3b
30.3 ± 0.7c
29.0 ± 0.7c
*
40 days
37.8 ± 1.3a
37.7 ± 1.3a
29.3 ± 1.3b
27.0 ± 1.3d
30.6 ± 0.7c
29.2 ± 0.7c
*
50 days
38.3 ± 1.7a
36.1 ± 1.7b
30.8 ± 1.7c,e
28.4 ± 1.7d
31.1 ± 0.9e
29.4 ± 0.9c,d
*
60 days
38.8 ± 1.8a
35.8 ± 1.8b
32.4 ± 1.7c
29.8 ± 1.8d
32.1 ± 1.0c
29.9 ± 1.0d
**
70 days
39.9 ± 1.8a
37.3 ± 1.8b
33.3 ± 1.8d
30.4 ± 1.8c
32.2 ± 1.0c,d
30.6 ± 1.0e,c
**
80 days
41.4 ± 1.8a
38.2 ± 1.8b
34.4 ± 1.8c
31.1 ± 1.8d
33.1 ± 1.0c
31.3 ± 1.0d
**
FBW
45.5 ± 1.4a
42.4 ± 1.4b
35.2 ± 1.3c
31.6 ± 1.4d
34.4 ± 0.7c
32.4 ± 0.7d
***
BWC
16.1 ± 1.1a
13.4 ± 1.1b
8.9 ± 1.1c
7.5 ± 1.1d
6.0 ± 0.6e
5.9 ± 0.6e
**
ADG (g)
178.5 ± 12.3a
148.3 ± 12.4b
98.4 ± 12.2c
83.5 ± 12.3d
66.6 ± 6.7e
65.2 ± 6.7e
**
Table 2.
Genotype and supplemented diet effect on ram lambs body weight gain.
P < 0.05, **P < 0.01, ***P < 0.001.
ABW, average body weight gain; FBW, final body weight gain; BWC, body weight change; ADG, average daily weight gain; T1, supplemented; T2, not-supplemented; superscript with the same letter is not significant and different letters has significant difference (across the row); SE, standard error of the mean.
The total body weight changes from initial to final body weight higher in supplemented Awassi crossbred lambs and followed by their non-supplemented group. Supplemented and non-supplemented Wollo highland lambs observed better growth performance than Washera F1 crossbreds. Therefore, on-station feed supplementation effect had fastest growth performance record with Awassi F1 crossbred lambs than Wollo highland and Washera F1 crossbred lambs. Supplemented Wollo highland lambs had faster growth rates than their non-supplemented group. Supplemented Washera crossbred lambs had a comparable body weight change to non-supplemented group.
Even though, Wollo highland breed had faster body weight change and average daily gain than Washera F1 crossbred lambs, the supplemented group of Washera crossbred lambs had higher final body weight gain than supplemented Wollo highland breed lambs. The final body weight of non-supplemented Washera crossbred lambs had higher than non-supplemented Wollo highland lambs.
3.2 Genotypes and supplementation effect on carcass characteristic performance
Carcass and non-carcass yield characteristics included, pre-slaughtered weight, slaughter body weight, empty body weight, fasting loss, hot carcass weight, cold carcass weight, total edible proportion, non-carcass organs, rib-eye area, fat and lean meat thickness and commercial yield were presented in Table 2.
Slaughtered and empty body weight bases of the supplemented and non-supplemented groups did not significant difference for each genotype. However, significant variations recorded between the three genotypes. Subsequent to 24 hours of fasting period (except water) the body weight losses and hot carcass weight had comparable value within breeds. However, Awassi crossbred lambs lost more than Washera crossbred and Wollo highland breed lambs. Even though Awassi F1 crossbred lambs lost higher body weight than others during fasting period, it is significantly (P < 0.05) higher hot carcass weight than Washera F1 crossbreds and Wollo highland ram lambs. Nevertheless, fasting loss and hot carcass weight have comparable value between supplemented and non-supplemented Wollo highland and Washera crossbred lambs.
Fat thickness of both supplemented and non-supplemented groups of Awassi crossbred lambs had significantly higher than Wollo highland and non-supplemented Washera crossbred lambs. Despite the fact that, supplemented Washera crossbred lambs, had comparable fat thickness with supplemented Awassi crossbred lambs. Awassi crosses had significantly higher a total non-carcass weight than both Washera and Wollo highland breed lambs, but did not show within breed difference. Between supplemented and non-supplemented Washera genotype and supplemented local Wollo highland breed did not have significant variation of total non-carcass components and non-supplemented Wollo highland lambs significantly lower than others.
Slaughtered body weight had strong positive and significant correlation with empty body weight, hot and cold carcass weight, rib-eye area (cm2), fat thickness (mm2) and slight positive correlation with lean thickness (mm2). However, it had inverse correlation with commercial yield % (cold carcass weight/slaughtered body weight × 100) carcass trait. Empty body weight has strong and positive correlation with cold and hot carcass weight, and rib-eye area (cm2). However, poor and positively associated with lean meat thickness (mm2).
Hot carcass weight had perfect positive significant correlation with rib-eye area (cm2) of lean meat composition, medium positive correlation with fat thickness and poorly correlated with amount of commercial yield (Table 3). The cold carcass weight trait has positive and intermediate correlation with rib-eye area and with lean meat thickness and poorly positive correlation with commercial yield feature. Likewise, rib-eye area carcass trait contents had medium positive association with fat thickness and lean meat thickness attribute. However, it had poor and positive correlation with commercial yield percentage composition, while fat thickness amount of the carcass had positive and medium correlation with lean meat thickness in the entire carcass, but negatively correlated with commercial yield percentage composition. In other ways lean meat content of the carcass had poor positive correlation with commercial yield of the whole carcass composition (Table 3).
Carcass traits
Awassi F1 crossbreds
Wollo highland breed
Washera F1 crossbreds
T1
T2
T1
T2
T1
T2
Sig. L
SBW (kg)
47.4 ± 0.8a
44.6 ± 0.6b
32.5 ± 1.4c
29.3 ± 1.1d
32.6 ± 0.5c
32.2 ± 0.5c
***
EBW(kg)
35.3 ± 1.3a
32.4 ± 1.3a
24.5 ± 1.7b
20.5 ± 1.7b
26.9 ± 0.9c
26.8 ± 0.9c
**
HCW (kg)
20.8 ± 1.6a
20.2 ± 1.6a
14.7 ± 1.2b
13.5 ± 1.2b
16.0 ± 0.5c
13.2 ± 0.5b
***
CCW (kg)
18.3 ± 1.4a
18.2 ± 1.4a
11.7 ± 1.0b
11.6 ± 1.0b
14.9 ± 0.4c
12.5 ± 0.4c,b
**
HCWDP (%)
43.9 ± 3.2a
45.3 ± 3.2b
45.2 ± 3.2b
46.1 ± 3.2b
49.1 ± 0.3c
41.0 ± 0.3d
*
CCWDP (%)
38.6 ± 2.9a
40.8 ± 2.9b
36 ± 5.2c
39.6 ± 5.2a,b
45.7 ± 1.8d
38.8 ± 1.8a
*
TEP (kg)
25.1 ± 1.8a
23.8 ± 1.8a
17.4 ± 1.6b
17.2 ± 1.6b
19.6 ± 0.7c
17.6 ± 0.7b
**
REA (cm2)
15.9 ± 0.2a
15.5 ± 0.2a
7.3 ± 0.1b
6.5 ± 0.1b
9.2 ± 0.1c
7.3 ± 0.1b
**
TNCW (kg)
14.5 ± 1.3a
12.2 ± 1.3a,b
10.8 ± 1.3b
6.9 ± 1.3c
10 ± 1.3b
12.9 ± 1.3b
*
FT (mm)
0.3 ± 0.1a
0.3 ± 0.1a
0.2 ± 0.0b
0.2 ± 0.0b
0.3 ± 0.2a
0.2 ± 0.2b
*
Table 3.
Analysis of variability for genotype and diet effects on carcass traits.
T1, supplemented; T2, non-supplemented; SBW, sloughter body weight; EBW, empty body weight; HCW, hot carcass weight; CCW, cold carcass weight; HCWDP, hot carcass weight dressing percentage; CCWDP, cold carcass weight dressing percentage; TEP, total edible propertion; REA, rib-eye area; TNCW, total non-carcass weight. Superscript with the same letter is not significant and different letters has significant difference.
3.4 Genotype and supplementation effects on carcass morphometric traits
Carcass morphometric characteristics of the present study were described by carcass length, lean meat weight, lean meat length, compactness index, chest width, shoulder width, and lean meat thickness presented in Table 4. Hence, the length of the carcass and lean meat had significantly higher for Awassi and followed by Washera crossbred lambs. Between the supplemented and non-supplemented groups of each genotypes, comparable carcass and lean meat length were recorded, however, significantly different between genotypes. Lean meat thickness significantly higher for both supplemented and non-supplemented Awassi F1 crossbred lambs. Between supplemented and non-supplemented groups of Wollo highland breed and Washera, crossbred lambs had significant difference.
Body weight (kg)
SBW
EBW
HCW
CCW
REA
LMT
EBW
0.87**
HCW
0.82**
0.77**
CCW
0.86**
0.79**
0.98***
REA (cm2)
0.82**
0.77**
0.99***
0.98***
LMT (mm2)
0.52*
0.50*
0.54*
0.554*
0.54*
CY (%)
−0.15
−0.01
0.42
0.36
0.42
0.08
Table 4.
Pearson correlation coefficient of carcass yield characterestics.
Correlation is significant at the 0.001 level (two-tailed).
Correlation is significant at the 0.01 level (two-tailed).
Correlation is significant at the 0.05 level (two-tailed).
SBW, slaughter body weight; EBW, empty body weight; HCW, hot carcass weight; CCW, cold carcass weight; REA, rib-eye area; LMT, lean meat thickness; CY, commercial yield.
The carcass composition of lean meat weight amount is significantly higher with Awassi crossbred lambs than Washera crossbred and Wollo highland breed lambs. Supplemented Wollo highland lambs and Washera crossbred lambs had proportional amount of lean meat weight. The carcass compactness index is measured by grams of lean meat per centimeters of its length. Carcass compactness index, chest and shoulder width had comparable records for all genotypes except chest width for Awassi genotype.
3.5 Genotype and supplementation feed effects on non-carcass fat distribution
The effects of genotype and supplementation diet effect on non-carcass fat distribution presented in Table 5. Thus, the non-carcass fat contents around the scrotal fat organ had not significant variation between supplemented and non supplemented group of each genotypes. However, between Wollo highland breed and Awassi crossbred lambs had a significant variation of scrotal fat contents. Likewise, Washera and Awassi crossbred lambs had significant differences between supplemented and non supplemented groups of scrotal fat contents. While, kidney fat composition of Awassi crossbred lambs and Wollo highland breed lambs had significantly lower than that of Washera crossbred lambs (Table 5).
Carcass morphometric traits
Awassi F1 crossbreds
Wollo highland breed
Washera F1 crossbreds
T1
T2
T1
T2
T1
T2
Carcass length (cm)
74.3 ± 1.2a
73.7 ± 1.2a
63.0 ± 1.9b
64.0 ± 1.9b
70.3 ± 2.2c
68.0 ± 2.2c
Lean meat thickness (mm)
12.5 ± 2.4a
11.0 ± 2.4a
9.0 ± 0.7b
6.4 ± 0.7c
12.0 ± 0.5a
6.3 ± 0.5c
Lean meat weight (kg)
0.7 ± 0.03a
0.7 ± 0.03a
0.5 ± 0.1b
0.5 ± 0.1b
0.6 ± 0.1b
0.5 ± 0.1b
Lean meat length (cm)
55.3 ± 1.2a
54.7 ± 1.2a
44.0 ± 1.9b
45.0 ± 1.9b
51.3 ± 2.2c
49. ± 2.2c
Compactness index (g/cm)
12.1 ± 0.8
12.0 ± 0.8
11.8 ± 0.8
11.9 ± 0.8
12.4 ± 0.9
10.5 ± 0.9
Chest width (cm)
13.9 ± 0.6a
13.7 ± 0.6a
9.2 ± 1.0b
8.1 ± 1.0b
10.9 ± 0.9b
8.8 ± 0.9b
Shoulder width (cm)
17.7 ± 0.6
18.1 ± 0.6
14.4 ± 0.6
14.2 ± 0.6
17.1 ± 0.6
15.0 ± 0.6
Table 5.
Between and within genotype carcass morphometric traits variability.
T1, supplemented; T2, non-supplemented; cm, centimeters, kg, kilograms, mm, millimeters, g, gram. Superscript with the same letter is not significant and different letters has significant difference.
Whereas, significant difference recorded between three genotypes of total non carcass fat contents. Both supplemented and non supplemented group of Awassi F1 crossbred lambs had higher composition of total non-carcass fat contents followed by Washera crossbred lambs. In general all supplemented groups were comprised of higher numerical value of non carcass fat composition, but not significantly different with non supplemented groups.
3.6 Genotype and feed effects on non-carcass edible and non-edible components
According to intellectual prohibited cultural and religious taboo of the local communities the edible components of non-carcass organs were presented as liver, tongue, heart, kidney, empty gastrointestinal part and tail fat were the most common. Hence, liver and heart weight had comparable value for Wollo highland and Washera crossbred lambs; however, Awassi crossbred had significantly higher amount of liver and heart weight. At the same time, non-significant record was observed between supplemented and non-supplemented groups of all genotypes. While the kidney and empty gastrointestinal weight had comparable value for all genotypes and feeding type factors, there was no significant difference both within and between genotypes and feeding types. Whereas the tail weight had comparable value between the three genotypes, Washera crossbred had a numerically higher quantity of tail weight than others (Table 6).
Non-carcass fat traits (g)
Wollo highland breed
Awassi F1 crossbreds
Washera F1 crossbreds
T1
T2
T1
T2
T1
T2
Scrotal fat
8.7 ± 2.9c
10.7 ± 2.1c
33 ± 6.7b
40 ± 6.7b
13.7 ± 4.4c
15.7 ± 4.4c
Pelvic fat
29.3 ± 3.5a
26.7 ± 3.5a
30.7 ± 3.1a
27.7 ± 3.1a
47.0 ± 10.6c
38.3 ± 10.6c
Kidney fat
25.3 ± 2.0a
23.3 ± 2.0a
60 ± 18a
63 ± 18.0a
171.0 ± 52.4c
89.3 ± 52.4c
Mesentery fat
55.3 ± 8.5a
43.3 ± 8.5a
414 ± 38.7b
317.7 ± 38.7b
233.3 ± 64.1c
145.0 ± 64.1c
Overall
117.7 ± 12.6a
103.6 ± 12.6a
537.7 ± 54.7c
448.4 ± 54.7d
465 ± 129.7c
288.3 ± 129.7b
Table 6.
Non-carcass fat distribution traits variability between and within genotypes.
T1, supplemented; T2, non-supplemented; g, grams. Superscript with the same letter is not significant and different letters has significant difference.
Except kidney weight of non-supplemented Awassi and Washera F1 crossbreds and supplemented Wollo highland breed lambs, the edible non-carcass components not significant variation between supplemented and non-supplemented groups. However, except kidney weight and GIT empty weight, genotype had significant variation on non-carcass edible components. Except tail fat weight composition, in all edible non-carcass components of the Awassi crossbred lambs had the largest portion (Table 6).
Wollo highland breed had a comparable tail fat composition with Awassi crossbred lambs. However, both genotype and supplementation diet did not had significant differences with kidney and empty gastrointestinal weight of supplemented and non-supplemented groups. Subsequently, the non-edible, non-carcass components were skin, head, testicle and genital organ, blood, bladder, pancreas, feet, digestive contents and spleen which prohibited by the local communities cultural and religious taboo.
4. Discussion
4.1 Genotype and supplemented diet effects on body weight gain and carcass traits
The availability and supply of animal feed in the tropics is not constant in terms of both quantity and quality particularly in arid and semiarid regions seasonal fluctuation in the growth rate of animal in these regions [9, 10]. This is particularly true in the study area, where the main source of animal feed is grazing on natural pasture. For this reason, to use whatever available resource more economically, it will be advantageous to identify those breeds of animals which are more efficient meat producers [11] or animals which have high performance in feed conversion efficiency to produce saleable products [11].
4.2 Effects of genotype and supplementation on body weight gain performance
Genotypes and supplementation feed effects on ram lambs’ body weight gain presented in Table 2. Initially the body weight gain of the three genotypes significantly different (p < 0.05) each other and the differences were come from breed effects but not significant differences within group in each treatment. To avoid the effects of initial body weight on the successive body weight gain, covariate analysis was used and the adjusted initial body weight at 26.56 kg of all genotypes. In the present study, significantly higher average daily weight gain observed on the supplemented group implied that they were adequately fed and their maintenance and growth nutrient requirements were satisfied compared with non-supplemented groups (grazing only).
The average daily weight gain (ADG), the rate of body weight change and final body weights of supplemented group of Awassi, and Washera F1 crossbred and Wollo highland breed ram lambs were significantly higher (p < 0.05) than non-supplemented groups. As a result, Awassi F1 crossbred lambs’ growth rate had significantly greater (p < 0.05) than both Wollo highland and Washera F1 crossbred ram lambs throughout the experimental period and followed by supplementing Wollo highland breed ram lambs. The reason behind this might be the genetic potential difference of the three genotypes affecting average daily weight gain efficiency with different extent. Therefore, genotype is the limiting factor affecting average daily weight gain of lambs and in agreement with reported by Hammell and Laforest [12] for Polled Dorset, Hampshire and Romanov breeds.
The total amount of body weight change and the rate of daily weight gain indicated Wollo highland breed lambs were significantly greater than both supplemented and non-supplemented groups of Washera F1 crossbred lambs. This indicated improved grazing management condition and supplementation diet of Wollo highland breed lambs can have comparable body weight gain potential with their Washera F1 crossbreds with the same management condition [13, 14, 15].
In general the Awassi F1 crossbred ram lambs have a promising growth performance with supplementation of local available concentrate feed. Hence, with controlled management condition of natural pasture grazing has contributed to better growth performance of ram lambs body weight gain. Furthermore, Washera F1 crossbreed lambs have an imperative body weight change and can be another alternative to enhance genetic potential of pure local Wollo highland breed, and in addition to this, inbreeding coefficient risk can be reduced. Moreover, cost-effective concentrate feed supplementation on natural pasture grazing need appropriate attention by fatteners, and other sheep producers. Together with this private controlled grazing management, system had also played a great role to improve the body weight gain of ram lambs through quality pasture production.
4.3 Effects of genotype and supplemented feed on carcass yield characteristics
Carcass composition used as tool to characterize breeds for possible identification of potential genetic resource for lean lamb production and also to identify management alternatives to suit different breeds [16]. Therefore, breed is known to influence not only carcass composition and quality but also carcass conformation as well, differences in carcass merits between breeds is likely to govern the choice and development of breeds for specific production objectives.
Slaughter and empty body weight between supplemented and non-supplemented groups variation not significant for all genotypes. The reason behind this might be less significant variation between supplemented and non-supplemented body weight before slaughter and relatively comparable amount of fasting loss. Nevertheless, significant variations between the three genotypes recorded, and which in agreement with Orr [17] and Lakew et al. [18]. Subsequent to 24 hours of fasting period, the body weight losses had a comparable amount for all genotypes and not significant variation observed. The loss of rumen contents through defecation and urination effects of fasting period not significantly different among genotypes (Table 7).
Non-carcass components
Awassi crosses (means)
Wollo highland breed (means)
Washera crosses (means)
T1
T2
T1
T2
T1
T2
SE
P-value
I. Edible non-carcass traits
Liver (g)
717.0a
541.3a
332.0b
384.3b
445.0c
453.0c
76.0
**
Tongue (g)
137.8a
143.2a
109.3b
114.3b
91.9c
89.8c
7.0
***
Heart (g)
190.3a
127.3a
61.3c
68.3c
68.3c
75.3c
25.5
**
Kidney (g)
63.3a
66.0b
64.3a,b
59.0c
54.0c
66.0b
31.4
*
GIT empty (g)
1900.0
1633.3
1611.3
2215.0
1779.3
1633.3
330
ns
Tail fat (g)
987.3
951.0
1106.7
920.0
1151.3
1213.3
100.9
ns
II. Non-edible non-carcass traits
Skin (g)
3600.0a
3766.7a
3700.0a
3133.3b
5100.0c
5033.3c
255.0
**
Head (g)
1773.3a
1733.3a
2110.0b
2206.7b
2660.0c
2763.3c
134.9
**
Testicle (g)
420.0a
420.0a
310.0b
310.0b
540.0a
430.0a
56.0
***
Blood (g)
1336.7a
1300.0a
873.3b
937.3b
2033.3c
1823.3c
181.3
**
Bladder (g)
67.3a
68.7a
57.3b
63.3b
72.3.0a
64.0a
2.3
**
Feet (g)
247.7a
249.7a
214.0a
194.7b
203.7b
217.7a
16.4
*
Digestive content (g)
8400.0c
8300c
4222.0a
5551.7b
3466.7a
4337.3a
725.2
**
Spleen (g)
41.7
44.0
32.7
45.0
33.7
30.3
4.7
ns
Table 7.
Genotype and diet effects on edible and non-edible non-carcass components.
T1, supplemented; T2, non-supplemented; ns, non-significant; GIT, gastrointestinal track and SE, standard error of the mean. Superscript with the same letter is not significant and different letters has significant difference.
Hot carcass weight has comparable value between supplemented and non-supplemented groups. However, between genotypes a significant variation (p < 0.001) reported and which in agreement with Orr [17] and Lakew et al. [18]. Therefore, Awassi F1 crossbred ram lambs significantly higher (p < 0.001) hot carcass weight than Wollo highland and Washera F1 crosses (Table 2). This is because of higher slaughtered body weight and higher average daily weight gain (ADG) effect and their comparable fasting loss. Assefu [19, 20] reported there was no breed effect in hot carcass weight between Horro and Washera breeds and which disagree with present study.
Cold carcass weight used as commercial carcass yield indicator trait used for productive performance tools to evaluate the productivity of a given meat animals. Awassi crossbred lambs’ cold carcass weight significantly (p < 0.05) greater than both Washera crosses and Wollo highland breed lambs. Within each genotype, cold carcass weight did not have significant difference because of the higher amount of chilling loss rate of supplemented groups (Table 7). This indicated that, the supplemented feed does not bring significant impact on cold carcass weight and agreement with Awgichew [10] for Menz and Horro breed lambs and Jorge et al. [21] for Chilote and Suffolk breeds in Chile Island. The chilling loss of cold carcass weight may vary between 1 and 7%, usually found close to 2.5% [22]. Moreover, sex, weight, fat covering of the carcass, temperature, and humidity in the cold storage chamber and the handling of the carcasses [23, 24] influence cold carcass characteristic.
Dressing percentage is described as the proportion of carcass weight to slaughtered body weight and it helps to assess meat productivity of the animals. Nutrition influences dressing percentage through variation in weight of mesentery contents and variation in actual organ weights [25, 26]. In agreement with the present finding, Awgichew [10] reported, regardless of the clear tendency of Horro lambs having a heavier hot and cold carcass weight, but did not differ significantly from Menz breed in dressing % and the loss of carcass moisture (shrinking %) after an overnight cooling. The present finding reported, hot carcass weight dressing percentage (HCCWDP) does not have significant difference both between and within genotype and which in agreement with Awgichew [10] and Jorge et al. [21]. Concurring with this report, an experimental trial conducted by Mazemder et al. [27] on grazing local sheep supplemented and with non-supplemented of 100, 200 and 300 g of concentrate feed/day; dressing percentage was similar among the treatments.
Rib-eye muscle area is mostly used as a tool to indicate the proportion of carcass muscling [28, 29]. In the present study the supplementation diet did not have a significant impact on rib-eye muscle area but numerical difference was observed. In line with the current finding, Gizaw [1] reported supplementation did not have significant effect on rib-eye muscle area in Somali goats fed hay and supplemented with different levels of peanut cake and wheat bran mixture. However, unlike this finding, Matiwas et al. [28] and Alemu [32] reported supplementation diet had a significant and positive effect on rib-eye muscle area. In concurrence with this finding, Matiwas et al. [31], Alemu [32]; Simret and Gizaw [30] reported rib-eye area had a significant variation between breeds. However, did not significant variation between supplemented and non-supplemented groups of Awassi crosses and Wollo highland breed lambs (Table 7). Nevertheless, supplemented and non-supplemented groups of Washera crossbreds had significant differences of rib-eye area composition. This fact is an indicator of better muscle development of supplementing Washera crosses than non-supplemented one. Hence, this rib-eye area muscle development is one of the merits to select Washera F1 crossbred lambs for meat production objective. Both supplemented and non-supplemented Wollo highland and non-supplemented Washera crossbred lambs have relatively comparable rib-eye area muscle development (Table 7).
Except dressing percentage, almost all carcass characteristic extent both supplemented and non-supplemented Awassi crossbred had significantly higher than Wollo highland and Washera F1 crossbred lambs. Hence, crossbreeding effect on genetic improvement practices using Awassi exotic breed had significant response associated with growth and carcass yield characteristic traits. As a result Awassi F1 crossbred lambs had potential effect on meat production improvement objective and advisable to be selected for further breed productivity improvement program.
4.4 Genotype and supplemented feed effects on non-carcass fat distribution
The effects of genotype and supplementation diet on non-carcass fat distribution was presented in Table 6. Thus, non-carcass fat contents around the scrotal organ had not significant variation between supplemented and non-supplemented groups of the three genotypes. However, between Wollo highland breed lambs and Awassi F1 crossbred lambs, significant variation of fat around scrotal organ observed. Likewise, between supplemented and non-supplemented groups of Washera and Awassi F1 crossbred lambs have significant difference fat around scrotal organ recorded. Subcutaneous fat content between Wollo highland and Awassi crossbred lambs had comparable value. However, Awassi crossbred and Wollo highland breed lambs significantly lower subcutaneous fat content than Washera crossbred lambs. The reason behind this, on fat deposition efficiency of Washera F1 crosses genotype effect has more noticeable than Awassi crosses and Wollo highland breed.
The current study showed mesentery fat, kidney fat and subcutaneous fat decreased in non-supplemented ram lambs fed on natural pasture forage diet only. The current result is in agreement with reported by Karim et al. [33] and Papi et al. [34] on the concept of lambs with high forage quality tended to deposit less subcutaneous and intestinal fat contents. Lambs fed a concentrate diet displayed considerably greater fat accumulation than lambs raised on forage based diets [35]. The reduced non-carcass fat attributed to lower energy intake from forage [33]. In addition, high starch consumption the supplemented concentrate diets produces higher amounts of propionate, which ultimately increases insulin secretion and stimulates fat synthesis [35]. In agreement with this finding, Ibrahim et al. [29], Salo et al. [36], Roberto et al. [37] and Abebe and Tamir [38] reported the total fat contents of non-carcass components were significantly affected by the type of diet used. However, in the current finding, in addition to the effects of diet, genotype effects also significant (P < 0.05) different on total non-carcass fat contents. Even though, supplemented Awassi and Washera crossbred lambs had comparable total non-carcass fat composition, Washera F1 crossbred lambs showed comparatively higher fat contents than Awassi F1 crossbreds in relation to their body weight difference.
4.5 Genotype and supplemented feed effects on edible and non-edible, non-carcass part
Accordingly, intellectual prohibited cultural and religious taboo of local communities, edible components of non-carcass organs, which presented as liver, tongue, heart, kidney, empty gastrointestinal content and tail fat are the most common and presented in Table 6. Hence, liver and heart weight comparable value between Wollo highland and Washera crossbred lambs; however, Awassi crossbred lambs had significantly (p < 0.05) higher than the other. The reason behind this might be larger body size and physiological appearance of the genotype. However, non-significant variation between supplemented and non-supplemented groups of all genotypes were recorded, while the kidney and intestine weight had a comparable amount for all genotypes and feeding type. Roughage part of animal feed obvious to feel rumen content and the the green forge grazing was equally accessible to all genotypes and which was the reason for comparable intestinal weight. Whereas the tail size had comparable value for Awassi crossbred and Wollo highland breed ram lambs, Washera crossbred lambs had a significantly (P < 0.05) larger tail size than other two genotypes. This also indicated that Washera F1 crossbred ram-lambs shown larger fat development nature and that might be because of largest tail weight.
In agreement with current finding, Riley et al. [39] and Teklu [40] were reported the majority of edible offal components was not affected (P > 0.05) by the supplemented feed. As a remarkable feature of Awassi crossbred lambs more advanced with liver, tongue and heart weight. This perceptible difference resulted from large body size and genotype effect. In concurrence with the current result, Riley et al. [39] indicated that differences in internal organs were more influenced by age, breed and sex of the animals rather than plane of nutrition, whereas kidney and empty gastrointestinal track weight cover the larger portions of edible non-carcass components compared with all genotypes, which aligned with Teklu [40]. This implies animals consume more feed, their stomach enlarged to accommodate the larger ingesta and thicker to resist the workload on it and this may increase the volume and weight of the gastrointestinal tract as a whole.
Except lung with trachea and spleen, all non-edible offal components were not affected by supplemented diet and indicating that variation of supplementation diet not influenced the non-edible non-carcass components. The non-edible non-carcass contents of head, digestive content and blood volume significant difference (p < 0.05) among genotypes and this might be slaughtered body weight differences and the inherent genotype effect. In agreement with the current study, Prasad and Kirton [41] reported live weight status of the animals could affect the production efficiency of carcass offal and considered as depressing factor for hot and cold carcass weight extent and their dressing percentage. However, the nutritional effect not significantly visible for most non-edible non-carcass component weight and which in agreement with Teklu [40] but disagree with Michael and Yaynshet [42]. In general the larger extent of non-carcass non-edible components could be reduced the edible carcass and non-carcass amount, hence, through breed selection task, need to be considered the non-carcass non-edible content of genotype.
5. Conclusion and recommendation
The study conducted at feedlot productive performance evaluation of Wollo highland sheep breed and their F1 crossbreeds of Awassi and Washera sheep in Ethiopia. The objectives of the research is grazing and feedlot based productive performance evaluation of Wollo highland sheep breed and their F1 crosses.
The average daily weight gain (ADG), total body weight change and final body weights of supplemented group Awassi F1 crossbred and Wollo highland ram lambs significantly higher than non-supplemented groups. Awassi F1 crossbred lambs growth performance significantly higher than Wollo highland and Washera F1 crossbred lambs and followed by supplemented Wollo highland breed lambs. Wollo highland breed had ability to increase their body weight compared with other selected indigenous breed types of the country and have potential value for fattening purpose and productive potential genetic improvement practice, as far as their nutritional requirement is maintained.
The effect of genotypes on average daily weight gain of Awassi crossbred ram lambs had the largest value of breed selection in the current study. Therefore, the effect of both genotype and supplementation diet have an advanced value for lamb body weight gain improvement practices. Moreover, cost effective concentrate feed supplementation on natural pasture controlled grazing have to give appropriate attention by smallholder sheep producers and fatteners.
Carcass composition used as a tool to characterize breeds for possible identification of potential genetic resource of lean meat type of lamb production and identify management alternatives to suit different breeds. Differences in carcass merits between genotypes are likely to govern the choice and development of breeds for specific production objective. Natural pasture controlled grazing management important alternative for productive and organic product improvement practices.
Supplementation diet does not have significant effect on hot carcass weight dressing percentage however, further research is important to confirm at different level of supplementation feeding trial. Cold carcass weight dressing percentage (CCWDP) has a significant difference between supplemented and non-supplemented groups of each of the three genotype in the present study and its important parameter for carcass productivity improvement practice.
Awassi F1 crossbred progenies designated for promising attributes for higher body weight gain and carcass yield characteristics productive trait and good fertility rate; however, further research verification activities suggested with different blood level of crossbred progenies performance evaluation. The genotype and supplementation diet effect has profound factors to enhance productive and farmers’ production objectives decision. Hence, researchers need to investigate farmers’ interest and potential of available breed type through genetic and phenotype performance study. Effective concentrate feed supplementation on controlled natural pasture grazing had significant impact on ram lambs productive performance improvement and it is crucial to create appropriate understanding for fatteners, traders and other sheep producers.
Acknowledgments
Mehamed Ali (private sheep farm owner) and Dessie Zuria District smallholder farmers have participated with allowed their sheep flocks for inventory purpose. Medhin G/Cherkos, Tadesse Mergiaw, Tilahun Gezahegn and Ayiten Mekete participated through data collection as enumerator. Addis Ababa (AAU) and Wollo University (WU) have participated in providing Research Grant. Department of Animal Production Study (DAPS) in Addis Ababa University, participated through assistance from the beginning to the end of data collection process and the whole thesis work.
Conflict of interest
The authors declare no conflict of interest.
Funding
The work of this research project has done by the funding support of Addis Ababa University thematic project, Minister of Education, and Wollo University collaboration.
Abbreviations
CSA
Central Statistics Authority
EPA
extension planning area
SPS
sanitary and phytosanitary standards
UNCTD
United Nations Conference on Trade and Development
\n',keywords:"body weight, carcass, Awassi and Washera, F1 crossbred and Wollo highland",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/72724.pdf",chapterXML:"https://mts.intechopen.com/source/xml/72724.xml",downloadPdfUrl:"/chapter/pdf-download/72724",previewPdfUrl:"/chapter/pdf-preview/72724",totalDownloads:399,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:30,impactScoreQuartile:2,hasAltmetrics:0,dateSubmitted:"November 26th 2019",dateReviewed:"March 31st 2020",datePrePublished:"July 6th 2020",datePublished:"January 14th 2021",dateFinished:"July 6th 2020",readingETA:"0",abstract:"In the study area, sheep flocks are managed under traditional extensive systems with no or minimal inputs and improved technologies, which results in low productivity. The available natural pasture lands are overloaded with livestock beyond optimum carrying capacity that has resulted in overgrazing and land degradation. This indicates the critical need of supplemental feed during feed-deficient period. The objective of the research was assessment of productive performance through on-station feedlot and natural pasture grazing effect on weight gain and carcass yield characteristics evaluation. The average daily weight gain (ADG), total body weight change and final body weights of supplemented groups significantly higher than (p < 0.05) non-supplemented groups. Hence, supplemented and non-supplemented Awassi crossbreds had higher daily weight gain and followed by supplemented Wollo highland group. Between genotypes, there is significant difference (p < 0.05) of rib-eye area, empty body weight, hot and cold carcass weight and cold carcass dressing percentage. Conversely, Wollo highland sheep has exhibited compensatory growth rate than others. Awassi crossbred lambs has higher weight gain and faster growth performance followed by Washera crossbred one. Therefore, local breed productive performance improvement practices have to continue and need adjustment of breeding strategies with a definite breeding plan.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/72724",risUrl:"/chapter/ris/72724",book:{id:"8468",slug:"sheep-farming-an-approach-to-feed-growth-and-health"},signatures:"Tadesse Amare Sisay, Gebeyehu Goshu Negia and Berhan Tamir Mersso",authors:[{id:"316037",title:"Ph.D.",name:"Tadesse",middleName:"Sisay",surname:"Amare",fullName:"Tadesse Amare",slug:"tadesse-amare",email:"workeamare@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Wollo University",institutionURL:null,country:{name:"Ethiopia"}}},{id:"316038",title:"Prof.",name:"Gebeyehu",middleName:null,surname:"Goshu Negia",fullName:"Gebeyehu Goshu Negia",slug:"gebeyehu-goshu-negia",email:"ggoshu2000@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Addis Ababa University",institutionURL:null,country:{name:"Ethiopia"}}},{id:"317608",title:"Prof.",name:"Berhan",middleName:null,surname:"Tamir Mersso",fullName:"Berhan Tamir Mersso",slug:"berhan-tamir-mersso",email:"berhantamir@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Addis Ababa University",institutionURL:null,country:{name:"Ethiopia"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Material and methods",level:"1"},{id:"sec_2_2",title:"2.1 Description of the study area",level:"2"},{id:"sec_3_2",title:"2.2 Experimental design and treatments",level:"2"},{id:"sec_4_2",title:"2.3 Experimental animals grazing management",level:"2"},{id:"sec_5_2",title:"2.4 Body weight gain and linear body measurements",level:"2"},{id:"sec_6_2",title:"2.5 Data analysis",level:"2"},{id:"sec_8",title:"3. Results",level:"1"},{id:"sec_8_2",title:"3.1 Effects of genotype and supplementation feed on ram lambs growth rate",level:"2"},{id:"sec_9_2",title:"3.2 Genotypes and supplementation effect on carcass characteristic performance",level:"2"},{id:"sec_10_2",title:"3.3 Carcass yield traits correlation coefficient analysis",level:"2"},{id:"sec_11_2",title:"3.4 Genotype and supplementation effects on carcass morphometric traits",level:"2"},{id:"sec_12_2",title:"3.5 Genotype and supplementation feed effects on non-carcass fat distribution",level:"2"},{id:"sec_13_2",title:"3.6 Genotype and feed effects on non-carcass edible and non-edible components",level:"2"},{id:"sec_15",title:"4. Discussion",level:"1"},{id:"sec_15_2",title:"4.1 Genotype and supplemented diet effects on body weight gain and carcass traits",level:"2"},{id:"sec_16_2",title:"4.2 Effects of genotype and supplementation on body weight gain performance",level:"2"},{id:"sec_17_2",title:"4.3 Effects of genotype and supplemented feed on carcass yield characteristics",level:"2"},{id:"sec_18_2",title:"4.4 Genotype and supplemented feed effects on non-carcass fat distribution",level:"2"},{id:"sec_19_2",title:"4.5 Genotype and supplemented feed effects on edible and non-edible, non-carcass part",level:"2"},{id:"sec_21",title:"5. Conclusion and recommendation",level:"1"},{id:"sec_22",title:"Acknowledgments",level:"1"},{id:"sec_25",title:"Conflict of interest",level:"1"},{id:"sec_22",title:"Funding",level:"1"},{id:"sec_25",title:"Abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'Gizaw S, Johan A, Olivier H, Hans K, Johann S, Dessie T, Van der Z, Herbert H. 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Department of Animal Science, College of Agriculture, Wollo University, Ethiopia
Department of Animal Production Studies, College of Veterinary Medicine and Agriculture, Addiss Ababa University, Ethiopia
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1. Introduction
A signal is a function that conveys information about the behavior or attributes of some phenomenon [1]. On the other hand, information can be anything. A waveform can have multiple overlapping information in the same space–time. The signal in a waveform is subjective, it can be color for one and shape for the other. In electrophysiology, waveform under inspection can be separated into two as the signal of interest and noise. The signal can be electrocardiography (ECG), Electroencephalogram (EEG), or any other physiological signal, noise is any unwanted wave source ınterfering with the signal. If we consider EEG as the signal, it is recorded from the scalp by electrodes and consists of the overall electrical activities of neural populations and a contribution of glial cells [2]. EEG has a wide range of use in both clinical practice and engineering applications in medicine, particularly neurology, sleep, and epilepsy research.
2. Background
The EEG recording environment and subject related electrical activities during recording deteriorate the signal quality. Artifacts are undesired signals that may introduce changes in the measurements and affect the signal of interest [3]. EEG can be contaminated in frequency or time domain by artifacts that are resulted from internal sources of physiologic activities and movement of the subject and/or external sources of environmental interferences, equipment, movement of electrodes and cables [4]. Artifact types and sources are listed in the Table 1. External artifacts can be prevented by proper shielding, grounding cables, isolating and moving cables away from recording sites since they act as antennas during operation. On the other hand, internal or physiological artifacts are challenging for researchers because of their inclusion of signal or resemblance to the signals. The most important artifacts in a typical EEG recording are ocular electro-oculogram (EOG) artifacts and muscular (EMG) artifacts.
Artifact
Type
Source
Eye blink
Ocular
Internal/Physiological
Eye movement
Ocular
Internal/Physiological
REM Sleep
Ocular
Internal/Physiological
Scalp contractions
Muscle
Internal/Physiological
Glossokinetic artifact
Muscle
Internal/Physiological
Chewing
Muscle
Internal/Physiological
Talking
Muscle
Internal/Physiological
EKG
Cardiac
Internal/Physiological
Swallowing
Muscle
Internal/Physiological
Respiration
Respiratory
Internal/Physiological
Galvanic Skin Response
Skin
Internal/Physiological
Sweating
Skin
Internal/Physiological
Electrode movement
Instrumental
External/Extra-physiological
Electrode Impedence Imbalance
Instrumental
External/Extra-physiological
Cable movement
Instrumental
External/Extra-physiological
Electromagnetic coupling
Electromagnetic
External/Extra-physiological
Powerline
Electrical
External/Extra-physiological
Head movement
Movement
External/Extra-physiological
Body movement
Movement
External/Extra-physiological
Limbs movement
Movement
External/Extra-physiological
Table 1.
EEG artifact types and sources. Adapted from [4, 5].
2.1 Ocular artifacts
Electrical potentials due to eye opening/closure, blinks, eyelid flutter and eye movements propagate over the scalp and produce hostile EOG artifacts in the recorded EEG. Eye movements are major sources of contamination of EEG. The origin of this contamination is disputable. Cornea-retinal dipole movement, retinal dipole movement and eyelid movement are the three main proposed causes of the eye movement related voltage potential [6]. The direction of eye movements affects the shape of the EOG waveform while a square-like EOG wave is produced by vertical eye movements and blinks which leads to a spike-shaped waveform [7]. Blinks which are attributable to the eyelid moving over the cornea, occurring at intervals of 1-10s, generate a characteristic brief potential of between 0.2 s and 0.4 s duration due to eyelid movement over cornea [8, 9]. The blinking artifact generally has an amplitude much larger than that of the background EEG [6]. It is advantageous to have a reference EOG channel during EEG recording for the cancellation of ocular artifact from EEG activity [3].
2.2 Muscular artifacts
Electrical activity on the body surface due to the contracting muscles are recorded via Electromyogram (EMG) [3]. Since independent myogenic activities of head, face and neck muscles are conducted through the entire scalp, it can be monitored in the EEG [10, 11]. The amplitude of this type of artifact is dependent on the type of muscle and the degree of tension [3, 12]. The frequency range of EMG activity is wide, being maximal at frequencies higher than 30 Hz [13, 14].
2.3 Cardiac artifacts
The electrical potential due to cardiac activity can exhibit itself in the EEG as ECG artifacts. Typical high frequency waveforms similar to EKG P-QRS-T shape are characteristics of EKG artifacts in EEG [15].
2.4 Other artifacts
Head, body and limb movements cause irregular high voltage artifacts. Artifacts can be produced by tremors in patients such as Parkinson disease and movement disorders. Changing patient position into a calm comfortable stable position helps reducing artifacts. Another prevention for respiratory related movement artifacts is to use a towel or a firm material support for the neck. The changes in the impedance or electrical potential between scalp and electrode may cause electrode artifacts. These can result from poor electrode contact, broken lead, electrolyte gel insufficiency. This type of artifact usually exhibits itself in sudden electrode pops. These electrode artifacts can be eliminated by using proper electrolyte gel, checking electrode impedance, changing the broken electrodes, and shifting the electrode position slightly.
3. Artifact handling methods
A typical EEG recording system is shown in Figure 1. At the heart of a recording setup is the biopotential amplifier. It should have high common mode rejection ratios, however it should not have high gains, this can saturate the signal due to large half-cell potentials at the electrodes. Unequal electrode impedances are major sources of common mode artifacts such as powerline.
Figure 1.
EEG recording system and experiment setup.
Environmental artifacts can be eliminated by bringing the electrodes leads closer together, moving the electrodes and subject away from the noise sources, using single isolated earth for the whole setup, and shielding the cables, machines and artifact sources with a metal tape connected to the common earth. Moreover, the environmental conditions should satisfy the following requirements for proper recordings. These can be listed as, quiet atmosphere, comfortable temperature and humidity, controlled proper lighting, using a comfortable bed or chair, and separating the powerline of the EEG system from the other machines in the lab.
3.1 Averaging methods to suppress ERP artifacts
Event Related Potentials (ERP) are electrical signals generated in response to internal or external events and they are recorded by EEG [16]. In evoked potentials, each stimulus produces an evoked potential embedded in EEG. However, since the ERP or evoked potential signals are generally subtle in EEG, averaging of many epochs are needed to make them distinguishable. An ensemble averaging method to enhance the ERPs was defined by [17]. This relies on the assumption that by synchronous averaging of each epoch, signal ERP amplitude adds constructively and EEG background noise diminishes destructively.
In ERP and evoked potential research, artifacts contaminate the final ensemble average signal of interest. One method to overcome this adverse effect is to benefit from a weighted averaging [18]. In weighted averaging technique each epoch is weighted inversely with the non-stationary noise maximum amplitude in the epoch. In [19], each trial’s contribution to ensemble average is multiplied by a weight according to its correlation with the rest of the data. This factor is inversely related to its probability of being an artifact. For example, a large amplitude EEG is likely to be an artifact and the contribution factor for the trial involving large amplitudes will be low whereas the factor for a small amplitude EEG is high (Figure 2). Davila and Mobin [20] showed that weighted averaging of auditory EP has higher SNR than conventional ensemble averaging. John et al. [21] studied the effects of such techniques as sample-weighted averaging, noise-weighted averaging, amplitude based artifact rejection, percentage based artifact rejection, and normal averaging on the steady state auditory evoked potentials. It concluded in favor of weighted averaging for better SNR of steady state responses. On the other hand, according to [22], weighted averaging underestimates the ERP signal amplitude. Determination of the optimal weighting factor is not straightforward and this limits the performance of the weighting averaging method. Mühler and Specht [23] developed a method called ‘sorted averaging’. In sorted averaging, epochs are sorted with RMS values from small to large, since noisy artifactual epochs have large RMS values compared to low noise signals. The signal averaging is performed by addition of epochs from the low noise RMS to large RMS sorted order until a maximum peak of SNR2 is obtained [24]. This eliminates the high RMS noisy epochs and yields a better ERP waveform. Compared to weighted averaging, sorted averaging had significantly higher SNR2 [23].
Figure 2.
Various EEG artifacts are shown.
Median averaging is another approach to ERP artifact handling and it is based on taking the median points of all the epochs and adding them to form a median average instead of classic mean average [25]. Some advantages of the median averaging are that; it elicits hidden signals more clearly and it is not affected by infrequent large artifacts that much compared to mean averaging [25]. Özdamar and Kalayci [26] supported the advantages of median averaging over the conventional mean averaging in a study on the ABR signals. Median averaging is an efficient way to remove adverse effects of the outliers on the final averaged signal, yet it also removes the valuable data in the outliers causing significant loss of information [27, 28].
3.2 Artifact handling methods for EEG
Artifact avoidance, artifact rejection, manual rejection, automatic rejection, and artifact removal are the common methods to deal with artifacts [29]. Although it seems a simple solution to cancel EOG and EMG artifacts by instructing subject to avoid blinking or movement, it can result in change of amplitudes in evoked potentials as well as the additional cognitive load [29, 30, 31]. On the other hand, artifact rejection or manual rejection may require a person dedicated to this purpose of eliminating artifacts visually one by one in an EEG. Moreover, the artifact detection by an expert may be subjective, tedious, and time consuming. In addition, it can not be applicable to online removal [3]. However, automatic rejection can automate this artifact rejection procedure but it can eliminate non-artifact signals if not properly tuned. The automatic rejection of artifact containing EEG can depend on artifact amplitude based or EEG segment RMS based artifact detection and rejection. An example of a simple blink artifact removal is depicted in Figure 3. Since blinks have low frequency content compared to EEG, by low pass filtering, EEG can be reduced while blink artifact still remains at a high voltage level. Thus, an amplitude threshold based artifact rejection can be applied. As seen from Figure 3, red traces are the EEG and blue are the low pass filtered EEG signal. While a simple artifact rejection (without low pass filtering) using a threshold of 20 μV will produce false positives (red traces over 20 μV), in the low pass filtered EEG these false positives are prevented.
Figure 3.
Low pass filtering based EEG blink rejection. Red is raw EEG, blue is low pass filered EEG with 6th order Butteworth low pass filter at 8 Hz cut off. The detected artifact containing EEG epochs are shown in dashed rectangles.
Usually one or two channels are dedicated to detect EOG artifacts. There are two widely used procedures for EOG artifacts, first EOG rejection where EEG trials with EOG artifacts having VEOG greater than a preset threshold are omitted, and second EOG correction where the effect of eye movement is tried to be removed from EEG [6].
Artifacts can distort the EEG in a way that the electrophysiologists or physicians can be misled in their clinical interpretation [32]. This makes artifact removal critical in the pre-processing phase prior to analysis. There are many methods to remove artifacts such as Artifactual Segment Rejection, Filtering, Wiener filtering, Adaptive Filtering, Time-Frequency Representation, Wavelet Transform, Discrete Wavelet Transform (DWT), Adaptive Noise Cancelation (ANC), Wavelet Packet Transform (WPT), Kalman Filtering, Linear Regression, Blind Source Separation (Principal Component Analysis (PCA), Independent Component Analysis (ICA), Canonical Correlation Analysis (CCA), Minor Components Analysis (MCA)), Source Decomposition, Empirical Mode Decomposition (EMD), Support Vector Machine (SVM), and hybrid methods [3, 4, 29, 33, 34, 35, 36, 37, 38]. A functional dedicated artifact channel which provides complementary aid to identify ECG/EOG is required to remove ocular or cardiac artifacts in the most of the available methods [4].
Regression is a common and well established technique in artifact removal, yet it cannot be used to remove muscle noise or line noise, since these type of artifacts have no reference channels [39]. Having a good regressor (e.g., an EOG) is critical in both time and frequency domain regression methods. It is an inherent weakness that eye movements and EEG signals are bidirectional. When unacceptable amount of data are lost in artifact rejection, delicate artifact removal methods which will preserve the essential EEG signals while removing artifacts are necessary [39]. One of the most important artifacts is EOG. EEG regions infected with EOG can be rejected from overall EEG signal with simplest artifact rejection where these portions are detected by EOG channels, however these regions still carry brain signals in addition to ocular artifacts and total rejection or subtraction of EOG from them results in loss of brain data [40, 41, 42].
Blind Source Separation (BSS) algorithms utilize multiple channels in an unsupervised learning algorithm to extract brain related activity from the ensemble EEG signal which can be assumed a linear superposition of brain signals, noise and artifacts [38]. Three common BSS algorithms are Independent Component Analysis (ICA), Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA).
ICA, a BSS method, is often used to remove EEG artifacts based on statistical approach of spatial filtering and separation of multiple channel EEG data into spatially fixed and temporally independent components [39, 43, 44]. Since the EEG sources and artifacts are usually of different origins, they can be assumed to be linear summation of each independent components. ICA method finds these statistically independent components and enable us to eliminate artifactual ones from the desired EEG [45]. On the other hand, ICA provides extraction of the eye related signals present in the EOG, and removal of this information or artifact, rather than the complete EOG which still has some brain activity [40], is possible. However, detection and removal of transient artifacts such as head and neck muscle contractions and movement are difficult with ICA [46]. Moreover, adapting ICA as an online method requires high computational power [46]. On the other hand, an advantage of ICA is that it does not rely on a reference channel [39]. However, many artifact removal algorithms are compared in [3], and Revised Aligned-Artifact Average (RAAA) and Second Order Blind Identification (SOBI) and Adaptive Mixture of Independent Component Analyzers (AMICA) are the preferred artifact removal methods for EOG, EMG and ECG artifacts.
PCA uses orthogonal transform of correlated time domain signal into linearly uncorrelated principal components (PCs) [47]. These principal components possess as much as variance of the EEG as possible. Artifact containing PCs can be eliminated if they are uncorrelated with the brain EEG. Application of PCA into ocular artifacts was provided in [48].
CCA is also another method utilized in removing artifacts. In CCA second order statistics are employed, correlation between two multivariate datasets are maximized by canonical variables. CCA offers shorter computational time compared to ICA [38].
Another method is filtering in frequency domain. Usually a high-pass filter starting from 0.5-1 Hz is applied for baseline drift removal. Notch filters are used to remove powerline-noise. Another one, EMG activity of contracting scalp sites can hinder the signals of interest in the EEG recordings during an epileptic seizure [49]. It was possible to remove this high frequency content EMG activity from EEG spectra by filtering out signals over 25 Hz. Adaptive Filters, Wiener Filtering and Bayesian Filters are three filtering methods applied in EEG signal preprocessing. Adaptive Filters are the most commonly used for artifact removal [47]. In Adaptive Filtering a reference channel for artifacts is subtracted from the EEG recursively. This reference is multiplied by a weight factor obtained from the output of the filter by a learning algorithm and this weighted reference is subtracted from the recorded EEG yielding output artifact free EEG changing adaptively [50].
In wavelet transform, many scaled and time shifted wavelets are used to produce coefficients for the particular signal and wavelet type by convolution of the signal and wavelets. These coefficients indicate similarity between the corresponding wavelet and the signal. In artifact removal via wavelet transform, the main idea is that the signal which can be highly correlated with a basis mother wavelet and can be separated from artifacts which might have no correlation to the principal mother wavelet [50]. Some examples of Wavelet Transform in artifact removal are for ocular artifact removal as in [51, 52].
3.3 EEG pre-processing pipelines available
Recently many preprocessing pipelines have been introduced in order to reduce the burden of artifact handling by an expert one by one visual inspection. This laborious task can be fastened by using existing automatized preprocessing methods in order. An efficient pre-processing pipeline not only helps the artifact management time but also provides objective evaluation with predefined criteria compared to highly subjective artifact handling by a human expert. The preprocessing pipelines usually consist of the combination of the following stages; filtering, re-referencing, bad channel identification (and interpolation), bad channel and epoch removal, artifact detection using ICA, artifact correction and removal [53], see Figure 4.
Figure 4.
APP artifact management flow diagram from [53].
Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER) [54] algorithm is a state of the art method which is available in EEGLAB toolbox [55]. FASTER has filtering, line noise removal, bad channel detection and interpolation, segmentation, and artifact rejection on segments by identifying bad channels, blinks, eye movements and muscular artifacts using combination of statistical thresholding and ICA [56]. It requires an extra EOG channel. The Automatic Pre-processing Pipeline (APP) removes powerline noise, bad channels, eye movements, blinks and muscular artifacts using ICA to identify artifactual components [53], see Figure 4. However, it also requires extra EOG channels. Da Cruz et al. [53] has found that APP performs better than FASTER yielding higher amplitude in ERP study. Another pipeline is Tool for Automated Processing of EEG data (TAPEEG) [57]. It uses automated routines of FASTER and Fieldtrip for artifact identification and performed similar to visually analysis by an expert [58]. TAPEEG handles the resting state EEG data as well. Both FASTER and TAPEEG are based on z- scores and have difficulty in handling outliers, this leads to loss of signal content due to false positive artifact detection and rejections [53]. Another standardized preprocessing method for large EEG datasets, PREP pipeline, handles line noise removal, bad channel detection, and referencing to standardize and normalize the data before processing [58]. It is also available as plug-in in EEGLAB toolbox.
Automagic is a toolbox developed for standardized handling of large growing EEG/ERP datasets by time [56]. The power of Automagic comes from the fact that it exploits many existing pipelines and methods, such as PREP pipeline for bad channel identification and for average referencing, Cleanline [59] to remove power line noise, EOG regression [60], Multiple Artifact Rejection Algorithm (MARA), ICA or robust PCA for artifact correction [61]. MARA is a plug-in available in EEGLAB which automatically identifies artifacts not only ocular or muscular but also any general artifactual source component in ICA [61]. Pedroni et al. [59] showed that combination of a preprocessing pipeline to identify bad channels and MARA method is efficient to remove most of the artifacts.
None of the methods offers a perfect robust and high accurate management of all types of artifacts. In general, they are all limited with the training dataset and fail to achieve high success with new type of artifactual data.
3.4 Simultaneous EEG and f-MRI artifact handling
Since EEG is widely used as a clinical tool to monitor or diagnose patients, doctors can be misguided in case of artifacts and EEG can be misinterpreted. For this reason, artifact removal becomes a crucial point for some cases such as epilepsy monitoring in an EEG/fMRI recording room. Today EEG and fMRI are two distinct but closely related and complementary methods. While fMRI provides high spatial resolution for localization of phenomena in the brain, EEG on the other hand results in better temporal resolution [62, 63, 64, 65]. One should be careful about the experiments involving both fMRI and EEG because there are many unwanted electromagnetic sources interfering with EEG. For example, the false identification of spikes are highly possible since residuals of Ballistocardiogram (BCG) artifacts have similar shapes as epileptic spikes [66]. The factors that can lead to differences in the artifact are linked to the subject and experimental setup, [67]. There are imaging artifacts, cardiac related Ballistocardiogram artifacts (BCG), EOG and EMG artifacts in an EEG inside MRI [44]. Static field (B0) and the time-varying fields of radio-frequency excitations and of imaging gradients, generate artifacts in the EEG known as Ballistocardiogram (BCG) and imaging artifacts [44, 68, 69, 70]. The pulse artifact which can be observed in EEGs recorded inside MR scanners easily, is due to a fundamental cause that any movement of electrically conductive muscles in a static magnetic field generates electromagnetic induction and it is proportional to the static field, generally larger at higher field strengths [67, 71]. Pulsations of the scalp arteries are the main cause of this type of BCG artifact [72, 73]. The study of Grouiller et al. [44] compared different imaging artifact removal techniques and various cardiac artifact correction techniques in both simulated EEG data and in real experimental data. They concluded that there is no key for every door, some algorithms work well for some case and others might work well for other cases. Certain algorithms may be preferred depending on the type of data and analysis method [44]. Another algorithm, adaptive Optimal Basis Set (aOBS), automatically eliminates BCG artifacts yet preserving the neural origin signals in EEG [74]. It can be used efficiently for simultaneous fMRI and EEG recordings.
3.5 Sleep stage classification artifact handling
Manual artifact detection is still the most common method for artifact handling for sleep stage classification, however, the long time required and the difficulty to apply it to large datasets poses the main disadvantages [75]. Malafeev et al. [75] compared 12 simple algorithms that are applicable with a single EEG channel for ease of use. It was found that automatic artifact detection in EEG during sleep within large datasets is possible with simple algorithms. Among these, Power thresholding 25–90 Hz (PT25), Power thresholding 45–90 Hz (PT45) and Autoregressive (AR) models had Reciever Operating Characteristic (ROC) areas above 0.95. In addition, online detection is also possible with the majority of these simple algorithms.
3.6 BCI Artifact handling
Artifact removal in BCI applications are getting more attention. By studies it was shown that artifacts generated by EOG and EMG activities affect the neurological signals utilized in a BCI system [10, 76]. Although there are extensive researches into artifact removal for BCIs and developed efficient methods such as Fully Online and Automated Artifact Removal (FORCe), Lagged Auto-Manual Information Clustering (LAMIC), Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER) and K-Singular Value Decomposition (K-SVD), the field lacks an effective artifact removal [12, 54, 77, 78, 79, 80, 81, 82]. The surrogate-based artifact removal (SuBAR) technique proposed by Chavez et al. [33] effectively cancels EOG and EMG artifacts from single-channel EEG. Chang et al. [83] proposed a method for detection of eye artifact from single prefrontal channel which is useful for headband-type wearable EEG devices with a few frontal EEG channels. Compared to conventional methods the accuracy of detecting ocular artifact contaminated epochs was significantly better. Daily-life EEG-BCIs are getting popular and artifact removal techniques for these BCIs must have some critical features such as; must be performed outdoor, with portable wearable wireless device, with real EEG signals, compatible with daily life tasks, must have simple electrical montage, must use dry electrodes, must remove complex artifacts, must work only EEG without reference, must work online and must work with single electrode channel. More research into artifact removal other than ocular and cardiac artifacts is necessary especially for those daily-life EEG BCIs [36].
While ICA and PCA are common artifact removal methods, Artifact Subspace Reconstruction (ASR), which is a powerful automated artifact removal method available for both online real-time and offline, can be applied to prevent transient and large artifact [46, 84]. It also does not require additional channel and cleans the data from artifacts.
4. Conclusion
The number of artifact handling techniques and algorithms are increasing drastically, however the artifact problem is still challenging for many applications. Particularly, the internal or physiologic artifacts are difficult to distinguish and remove. While simple measures such as artifact avoidance and artifact rejection can be utilized in some applications, most of the cases require special methods dedicated to handle artifacts in order to significantly reduce their harmful effects on signal of interest. Due to the varying nature of artifacts a generic method for all sorts of artifacts is still missing. However preprocessing pipelines provides some efficient approaches to this challenge. In future, the progress in machine learning and deep learning based approaches may yield more efficient, accurate and robust artifact removal options. Online artifact removal methods such as ASR must be developed to overcome various artifacts in daily life to be efficient for BCIs.
\n',keywords:"Artifact, Artifact removal methods, EEG, EEG preprocessing, Muscular artifacts, Ocular artifacts, Preprocessing pipelines",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/77731.pdf",chapterXML:"https://mts.intechopen.com/source/xml/77731.xml",downloadPdfUrl:"/chapter/pdf-download/77731",previewPdfUrl:"/chapter/pdf-preview/77731",totalDownloads:245,totalViews:0,totalCrossrefCites:2,dateSubmitted:null,dateReviewed:"June 28th 2021",datePrePublished:"July 29th 2021",datePublished:"May 18th 2022",dateFinished:"July 29th 2021",readingETA:"0",abstract:"There are various obstacles in the way of use of EEG. Among these, the major obstacles are the artifacts. While some artifacts are avoidable, due to the nature of the EEG techniques there are inevitable artifacts as well. Artifacts can be categorized as internal/physiological or external/non-physiological. The most common internal artifacts are ocular or muscular origins. Internal artifacts are difficult to detect and remove, because they contain signal information as well. For both resting state EEG and ERP studies, artifact handling needs to be carefully carried out in order to retain the maximal signal. Therefore, an effective management of these inevitable artifacts is critical for the EEG based researches. Many researchers from various fields studied this challenging phenomenon and came up with some solutions. However, the developed methods are not well known by the real practitioners of EEG as a tool because of their limited knowledge about these engineering approaches. They still use the traditional visual inspection of the EEG. This work aims to inform the researchers working in the field of EEG about the artifacts and artifact management options available in order to increase the awareness of the available tools such as EEG preprocessing pipelines.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/77731",risUrl:"/chapter/ris/77731",signatures:"İbrahim Kaya",book:{id:"10654",type:"book",title:"Brain-Computer Interface",subtitle:null,fullTitle:"Brain-Computer Interface",slug:"brain-computer-interface",publishedDate:"May 18th 2022",bookSignature:"Vahid Asadpour",coverURL:"https://cdn.intechopen.com/books/images_new/10654.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83962-529-9",printIsbn:"978-1-83962-522-0",pdfIsbn:"978-1-83962-530-5",isAvailableForWebshopOrdering:!0,editors:[{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",fullName:"Ibrahim Kaya",slug:"ibrahim-kaya",email:"ibrahimkaya21@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Izmir Kâtip Çelebi University",institutionURL:null,country:{name:"Turkey"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Background",level:"1"},{id:"sec_2_2",title:"2.1 Ocular artifacts",level:"2"},{id:"sec_3_2",title:"2.2 Muscular artifacts",level:"2"},{id:"sec_4_2",title:"2.3 Cardiac artifacts",level:"2"},{id:"sec_5_2",title:"2.4 Other artifacts",level:"2"},{id:"sec_7",title:"3. Artifact handling methods",level:"1"},{id:"sec_7_2",title:"3.1 Averaging methods to suppress ERP artifacts",level:"2"},{id:"sec_8_2",title:"3.2 Artifact handling methods for EEG",level:"2"},{id:"sec_9_2",title:"3.3 EEG pre-processing pipelines available",level:"2"},{id:"sec_10_2",title:"3.4 Simultaneous EEG and f-MRI artifact handling",level:"2"},{id:"sec_11_2",title:"3.5 Sleep stage classification artifact handling",level:"2"},{id:"sec_12_2",title:"3.6 BCI Artifact handling",level:"2"},{id:"sec_14",title:"4. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Priemer R. Introductory signal processing. Vol. 6. World Scientific; 1991'},{id:"B2",body:'Da Silva FL. 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Department of Biomedical Engineering, Izmir Katip Celebi University, Izmir, Turkey
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He operates in the area of Materials and Engineering Physics, with emphasis on Fracture Mechanics and Fractal Instrumentation Specifies General use. In their Professional Activities interacted with 39 co-workers in co-authorship of scientific papers.\r\n\tHe was a researcher at the University of São Paulo São Carlos - São Paulo - Brazil in the 1985-1995 period where he worked in the Brazilian Space project developing silicon-germanium alloys for Thermoelectric Generators Radioisotopes. Researcher at the Federal University of Paraná - Curitiba - Paraná - Brazil since 2006.\r\n\tPhD in Numerical Methods in Engineering at the Federal University of Paraná and Ponta Grossa State University. He studied a PhD in Materials Science and Engineering - Inter USP São Carlos since 1995 and stopped in 2002. Master in Physics in 1995, the Physics Institute of São Carlos, University of São Paulo, São Carlos - São Paulo - Brazil. BS in Physics in 1991, the Institute of Physics of São Carlos, University of São Paulo, São Carlos - São Paulo - Brazil; He had scholarship from FAPESP, CNPq, CAPES, and Johnson & Johnson,\r\n\tHe has several publications and contributions to national and international articles and book chapters. Published 15 articles in specialized journals, 3 chapters of Book, 63 works in Conference Proceedings. He has 1 Technological Product, 3 software, 2 Processes and Techniques and 43 other items of Technical Production. He participated in 40 events in Brazil and other countries. He directed 20 works of Scientific Initiation and 3 Work Completion of course in the areas of Materials and Metallurgical Engineering, Physics and Mechanical Engineering.\r\n\tReceived three awards and/or honors. Between 1985 and 2016 he participated in 20 research projects, and coordinated 9 of these. In 2006 he was quoted in Marquis Who\\'s who in the Book Mechanical Area fracture and according to ScienceDirect\\'s TOP25 Hottest Articles has the third most read article in 2005 in the Engineering Subarea of Fracture Mechanics of the Journal Theo Appl Frac. Mec.\r\n\tAmong his contributions include the discovery of the J-R curve fracture resistance of a material roughness is proportional to your set, defined by dL/dLo, where L is the rough path of the crack and Lo is the projected path. He was the first to develop an image processing method for obtaining the surface roughness of a crack in calculating the J-R curve fracture resistance in fractured materials. Developed an image processing method for the profile of a set of broken material; Produced an analysis software and fracture simulation materials. Developed a method for in-vitro measurements of the Sun Protection Factor (SPF) of Sunscreens products for Johnson & Johnson.\r\n\tIn his curriculum, the most frequent terms in the context of scientific, technological and Artistic-Cultural are: Fracture Mechanics, Fractal, Fractal Dimension, Growth and cracks propagation, Thermoelectric Ceramics, Power Thermoelectric, Thermoelectric Generator, Semiconductors, Effect Seebeck and Peltier effects. 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IntechOpen’s team of Scientific Advisors supports the publishing team by providing editorial and academic input and ensuring the highest quality output of free peer-reviewed articles. The Boards consist of independent external collaborators who assist us on a voluntary basis. Their input includes advising on new topics within their field, proposing potential expert collaborators and reviewing book publishing proposals if required. Board members are experts who cover major STEM and HSS fields. All are trusted IntechOpen collaborators and Academic Editors, ensuring that the needs of the scientific community are met.
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Physical Sciences, Technology and Engineering Board
\\n\\n
Chemistry
\\n\\n
\\n\\t
Ayben Kilislioglu - Department of Chemical Engineering Istanbul University, İstanbul, Turkey
\\n\\t
Goran Nikolic - Faculty of Technology, University of Nis, Leskovac, Serbia
\\n\\t
Mark T. Stauffer - Associate Professor of Chemistry, The University of Pittsburgh, USA
\\n\\t
Margarita Stoytcheva - Autonomous University of Baja California Engineering Institute Mexicali, Baja California, Mexico
Joao Luis Garcia Rosa - Associate Professor Bio-inspired Computing Laboratory (BioCom) Department of Computer Science University of Sao Paulo (USP) at Sao Carlos, Brazil
\\n\\t
Jan Valdman - Institute of Mathematics and Biomathematics, University of South Bohemia, České Budějovice, Czech Republic Institute of Information Theory and Automation of the ASCR, Prague, Czech Republic
\\n
\\n\\n
Earth and Planetary Science
\\n\\n
\\n\\t
Jill S. M. Coleman - Department of Geography, Ball State University, Muncie, IN, USA
\\n\\t
İbrahim Küçük Erciyes - Üniversitesi Department of Astronomy and Space Sciences Melikgazi, Kayseri, Turkey
\\n\\t
Pasquale Imperatore - Electromagnetic Environmental Sensing (IREA), Italian National Council of Research (CNR), Naples, Italy
\\n\\t
Mohammad Mokhtari - Director of National Center for Earthquake Prediction International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran
\\n
\\n\\n
Engineering
\\n\\n
\\n\\t
Narottam Das - University of Southern Queensland, Australia
\\n\\t
Jose Ignacio Huertas - Energy and Climate Change Research Group; Instituto Tecnológico y Estudios Superiores de Monterrey, Mexico
Likun Pan - Engineering Research Center for Nanophotonics and Advanced Instrument, Ministry of Education, Department of Physics, East China Normal University, China
\\n\\t
Mukul Chandra Paul - Central Glass & Ceramic Research Institute Jadavpur, Kolkata, India
\\n\\t
Stephen E. Saddow - Electrical Engineering Department, University of South Florida, USA
\\n\\t
Ali Demir Sezer - Marmara University, Faculty of Pharmacy, Department of Pharmaceutical Biotechnology, İstanbul, Turkey
\\n\\t
Krzysztof Zboinski - Warsaw University of Technology, Faculty of Transport, Warsaw, Poland
\\n
\\n\\n
Materials Science
\\n\\n
\\n\\t
Vadim Glebovsky - Senior Researcher, Institute of Solid State Physics, Chernogolovka, Russia Expert of the Russian Fund for Basic Research, Moscow, Russia
\\n\\t
Jianjun Liu - State Key Laboratory of High Performance Ceramics and Superfine Microstructure of Shanghai Institute of Ceramics, Chinese Academy of Sciences, China
\\n\\t
Pietro Mandracci - Department of Applied Science and Technology, Politecnico di Torino, Italy
\\n\\t
Waldemar Alfredo Monteiro - Instituto de Pesquisas Energéticas e Nucleares Materials Science and Technology Center (MSTC) São Paulo, SP, Brazil
Toshio Ogawa - Department of Electrical and Electronic Engineering, Shizuoka Institute of Science and Technology, Toyosawa, Fukuroi, Shizuoka, Japan
\\n
\\n\\n
Mathematics
\\n\\n
\\n\\t
Paul Bracken - Department of Mathematics University of Texas, Edinburg, TX, USA
\\n
\\n\\n
Nanotechnology and Nanomaterials
\\n\\n
\\n\\t
Muhammad Akhyar - Farrukh Nano-Chemistry Lab. Registrar, GC University Lahore, Pakistan
\\n\\t
Khan Maaz - Chinese Academy of Sciences, China & The Pakistan Institute of Nuclear Science and Technology, Pakistan
\\n
\\n\\n
Physics
\\n\\n
\\n\\t
Izabela Naydenova - Lecturer, School of Physics Principal Investigator, IEO Centre College of Sciences and Health Dublin Institute of Technology Dublin, Ireland
\\n\\t
Mitsuru Nenoi - National Institute of Radiological Sciences, Japan
\\n\\t
Christos Volos - Physics Department, Aristotle University of Thessaloniki, Greece
\\n
\\n\\n
Robotics
\\n\\n
\\n\\t
Alejandra Barrera - Instituto Tecnológico Autónomo de México, México
\\n\\t
Dusan M. Stipanovic - Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign
\\n\\t
Andrzej Zak - Polish Naval Academy Faculty of Navigation and Naval Weapons Institute of Naval Weapons and Computer Science, Gdynia, Poland
Petr Konvalina - Faculty of Agriculture, University of South Bohemia in České Budějovice, Czech Republic
\\n
\\n\\n
Biochemistry, Genetics and Molecular Biology
\\n\\n
\\n\\t
Chunfa Huang - Saint Louis University, Saint Louis, USA
\\n\\t
Michael Kormann - University Children's Clinic Department of Pediatrics I, Pediatric Infectiology & Immunology, Translational Genomics and Gene Therapy in Pediatrics, University of Tübingen, Tübingen, Germany
\\n\\t
Bin WU - Ph.D. HCLD Scientific Laboratory Director, Assisted Reproductive Technology Arizona Center for Reproductive Endocrinology and Infertility Tucson, Arizona , USA
\\n
\\n\\n
Environmental Sciences
\\n\\n
\\n\\t
Juan A. Blanco - Senior Researcher & Marie Curie Research Fellow Dep. Ciencias del Medio Natural, Universidad Publica de Navarra Campus de Arrosadia, Pamplona, Navarra, Spain
\\n\\t
Mikkola Heimo - University of Eastern Finland, Kuopio, Finland
\\n\\t
Bernardo Llamas Moya - Politechnical University of Madrid, Spain
\\n\\t
Toonika Rinken - Department of Environmental Chemistry, University of Tartu, Estonia
\\n
\\n\\n
Immunology and Microbiology
\\n\\n
\\n\\t
Dharumadurai Dhanasekaran - Department of Microbiology, School of Life Sciences, Bharathidasan University, India
Isabel Gigli - Facultad de Agronomia-UNLPam, Argentina
\\n\\t
Milad Manafi - Department of Animal Science, Faculty of Agricultural Sciences, Malayer University, Malayer, Iran
\\n\\t
Rita Payan-Carreira - Universidade de Trás-os-Montes e Alto Douro, Departamento de Zootecnia, Portugal
\\n
\\n\\n
Medicine
\\n\\n
\\n\\t
Mazen Almasri - King Abdulaziz University, Faculty of Dentistry Jeddah, Saudi Arabia Dentistry
\\n\\t
Craig Atwood - University of Wisconsin-Madison, USA Stem Cell Research, Tissue Engineering and Regenerative Medicine
\\n\\t
Oreste Capelli - Clinical Governance, Local Health Authority, Modena, Italy Public Health
\\n\\t
Michael Firstenberg - Assistant Professor of Surgery and Integrative Medicine NorthEast Ohio Medical University, USA & Akron City Hospital - Summa Health System, USA Surgery
\\n\\t
Parul Ichhpujani - MD Government Medical College & Hospital, Department of Ophthalmology, India
Amidou Samie - University of Venda, SA Infectious Diseases
\\n\\t
Shailendra K. Saxena - CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India Infectious Diseases
\\n\\t
Dan T. Simionescu - Department of Bioengineering, Clemson University, Clemson SC, USA Stem Cell Research, Tissue Engineering and Regenerative Medicine
\\n\\t
Ke Xu - Tianjin Lung Cancer Institute Tianjin Medical University General Hospital Tianjin, China Oncology
\\n
\\n\\n
Ophthalmology
\\n\\n
\\n\\t
Hojjat Ahmadzadehfar - University Hospital Bonn Department of Nuclear Medicine Bonn, Germany Medical Diagnostics, Engineering Technology and Telemedicine
\\n\\t
Miroslav Blumenberg - Department of Ronald O. Perelman Department of Dermatology; Department of Biochemistry and Molecular Pharmacology, Dermatology, NYU School of Medicine, NY, USA Dermatology
\\n\\t
Wilfred Bonney - University of Dundee, Scotland, UK Medical Diagnostics, Engineering Technology and Telemedicine
\\n\\t
Christakis Constantinides - Department of Cardiovascular Medicine University of Oxford, Oxford, UK Medical Diagnostics, Engineering Technology and Telemedicine
\\n\\t
Atef Mohamed Mostafa Darwish - Department of Obstetrics and Gynecology , Faculty of Medicine, Assiut University, Egypt Gynecology
\\n\\t
Ana Polona Mivšek - University of Ljubljana, Ljubljana, Slovenia Midwifery
\\n\\t
Gyula Mozsik - First Department of Medicine, Medical and Health Centre, University of Pécs, Hungary
\\n\\t
Shimon Rumelt - Western Galilee-Nahariya Medical Center, Nahariya, Israel Ophthalmology
\\n\\t
Marcelo Saad - S. Paulo Medical College of Acupuncture, SP, Brazil Complementary and Alternative Medicine
\\n\\t
Minoru Tomizawa - National Hospital Organization Shimoshizu Hospital, Japan Gastroenterology
\\n\\t
Pierre Vereecken - Centre Hospitalier Valida and Cliniques Universitaires Saint-Luc, Belgium Dermatology
\\n
\\n\\n
Gastroenterology
\\n\\n
\\n\\t
Hany Aly - Director, Division of Newborn Services The George Washington University Hospital Washington, USA Pediatrics
\\n\\t
Yannis Dionyssiotis - National and Kapodistrian University of Athens, Greece Orthopedics, Rehabilitation and Physical Medicine
\\n\\t
Alina Gonzales- Quevedo Instituto de Neurología y Neurocirugía Havana, Cuba Mental and Behavioural Disorders and Diseases of the Nervous System
\\n\\t
Margarita Guenova - National Specialized Hospital for Active Treatment of Haematological Diseases, Bulgaria
\\n\\t
Eliska Potlukova - Clinic of Medicine, University Hospital Basel, Switzerland Edocrinology
\\n\\t
Raymond L. Rosales -The Royal and Pontifical University of Santo Tomas, Manila, Philippines & Metropolitan Medical Center, Manila, Philippines & St. Luke's Medical Center International Institute in Neuroscience, Quezon City, Philippines Mental and Behavioural Disorders and Diseases of the Nervous System
\\n\\t
Alessandro Rozim - Zorzi University of Campinas, Departamento de Ortopedia e Traumatologia, Campinas, SP, Brazil Orthopedics, Rehabilitation and Physical Medicine
\\n\\t
Dieter Schoepf - University of Bonn, Germany Mental and Behavioural Disorders and Diseases of the Nervous System
\\n
\\n\\n
Hematology
\\n\\n
\\n\\t
Hesham Abd El-Dayem - National Liver Institute, Menoufeyia University, Egypt Hepatology
\\n\\t
Fayez Bahmad - Health Science Faculty of the University of Brasilia Instructor of Otology at Brasilia University Hospital Brasilia, Brazil Otorhinolaryngology
\\n\\t
Peter A. Clark - Saint Joseph's University Philadelphia, Pennsylvania, USA Bioethics
\\n\\t
Celso Pereira - Coimbra University, Coimbra, Portugal Immunology, Allergology and Rheumatology
\\n\\t
Luis Rodrigo - Asturias Central University Hospital (HUCA) School of Medicine, University of Oviedo, Oviedo, Spain Hepatology & Gastroenterology
\\n\\t
Dennis Wat - Liverpool Heart and Chest Hospital NHS Foundation Trust, UK Pulmonology
\\n
\\n\\n
Social Sciences and Humanities Board
\\n\\n
Business, Management and Economics
\\n\\n
\\n\\t
Vito Bobek - University of Applied Sciences, FH Joanneum, Graz, Austria
Joao Luis Garcia Rosa - Associate Professor Bio-inspired Computing Laboratory (BioCom) Department of Computer Science University of Sao Paulo (USP) at Sao Carlos, Brazil
\n\t
Jan Valdman - Institute of Mathematics and Biomathematics, University of South Bohemia, České Budějovice, Czech Republic Institute of Information Theory and Automation of the ASCR, Prague, Czech Republic
\n
\n\n
Earth and Planetary Science
\n\n
\n\t
Jill S. M. Coleman - Department of Geography, Ball State University, Muncie, IN, USA
\n\t
İbrahim Küçük Erciyes - Üniversitesi Department of Astronomy and Space Sciences Melikgazi, Kayseri, Turkey
\n\t
Pasquale Imperatore - Electromagnetic Environmental Sensing (IREA), Italian National Council of Research (CNR), Naples, Italy
\n\t
Mohammad Mokhtari - Director of National Center for Earthquake Prediction International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran
\n
\n\n
Engineering
\n\n
\n\t
Narottam Das - University of Southern Queensland, Australia
\n\t
Jose Ignacio Huertas - Energy and Climate Change Research Group; Instituto Tecnológico y Estudios Superiores de Monterrey, Mexico
Likun Pan - Engineering Research Center for Nanophotonics and Advanced Instrument, Ministry of Education, Department of Physics, East China Normal University, China
\n\t
Mukul Chandra Paul - Central Glass & Ceramic Research Institute Jadavpur, Kolkata, India
\n\t
Stephen E. Saddow - Electrical Engineering Department, University of South Florida, USA
\n\t
Ali Demir Sezer - Marmara University, Faculty of Pharmacy, Department of Pharmaceutical Biotechnology, İstanbul, Turkey
\n\t
Krzysztof Zboinski - Warsaw University of Technology, Faculty of Transport, Warsaw, Poland
\n
\n\n
Materials Science
\n\n
\n\t
Vadim Glebovsky - Senior Researcher, Institute of Solid State Physics, Chernogolovka, Russia Expert of the Russian Fund for Basic Research, Moscow, Russia
\n\t
Jianjun Liu - State Key Laboratory of High Performance Ceramics and Superfine Microstructure of Shanghai Institute of Ceramics, Chinese Academy of Sciences, China
\n\t
Pietro Mandracci - Department of Applied Science and Technology, Politecnico di Torino, Italy
\n\t
Waldemar Alfredo Monteiro - Instituto de Pesquisas Energéticas e Nucleares Materials Science and Technology Center (MSTC) São Paulo, SP, Brazil
Toshio Ogawa - Department of Electrical and Electronic Engineering, Shizuoka Institute of Science and Technology, Toyosawa, Fukuroi, Shizuoka, Japan
\n
\n\n
Mathematics
\n\n
\n\t
Paul Bracken - Department of Mathematics University of Texas, Edinburg, TX, USA
\n
\n\n
Nanotechnology and Nanomaterials
\n\n
\n\t
Muhammad Akhyar - Farrukh Nano-Chemistry Lab. Registrar, GC University Lahore, Pakistan
\n\t
Khan Maaz - Chinese Academy of Sciences, China & The Pakistan Institute of Nuclear Science and Technology, Pakistan
\n
\n\n
Physics
\n\n
\n\t
Izabela Naydenova - Lecturer, School of Physics Principal Investigator, IEO Centre College of Sciences and Health Dublin Institute of Technology Dublin, Ireland
\n\t
Mitsuru Nenoi - National Institute of Radiological Sciences, Japan
\n\t
Christos Volos - Physics Department, Aristotle University of Thessaloniki, Greece
\n
\n\n
Robotics
\n\n
\n\t
Alejandra Barrera - Instituto Tecnológico Autónomo de México, México
\n\t
Dusan M. Stipanovic - Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign
\n\t
Andrzej Zak - Polish Naval Academy Faculty of Navigation and Naval Weapons Institute of Naval Weapons and Computer Science, Gdynia, Poland
Petr Konvalina - Faculty of Agriculture, University of South Bohemia in České Budějovice, Czech Republic
\n
\n\n
Biochemistry, Genetics and Molecular Biology
\n\n
\n\t
Chunfa Huang - Saint Louis University, Saint Louis, USA
\n\t
Michael Kormann - University Children's Clinic Department of Pediatrics I, Pediatric Infectiology & Immunology, Translational Genomics and Gene Therapy in Pediatrics, University of Tübingen, Tübingen, Germany
\n\t
Bin WU - Ph.D. HCLD Scientific Laboratory Director, Assisted Reproductive Technology Arizona Center for Reproductive Endocrinology and Infertility Tucson, Arizona , USA
\n
\n\n
Environmental Sciences
\n\n
\n\t
Juan A. Blanco - Senior Researcher & Marie Curie Research Fellow Dep. Ciencias del Medio Natural, Universidad Publica de Navarra Campus de Arrosadia, Pamplona, Navarra, Spain
\n\t
Mikkola Heimo - University of Eastern Finland, Kuopio, Finland
\n\t
Bernardo Llamas Moya - Politechnical University of Madrid, Spain
\n\t
Toonika Rinken - Department of Environmental Chemistry, University of Tartu, Estonia
\n
\n\n
Immunology and Microbiology
\n\n
\n\t
Dharumadurai Dhanasekaran - Department of Microbiology, School of Life Sciences, Bharathidasan University, India
Isabel Gigli - Facultad de Agronomia-UNLPam, Argentina
\n\t
Milad Manafi - Department of Animal Science, Faculty of Agricultural Sciences, Malayer University, Malayer, Iran
\n\t
Rita Payan-Carreira - Universidade de Trás-os-Montes e Alto Douro, Departamento de Zootecnia, Portugal
\n
\n\n
Medicine
\n\n
\n\t
Mazen Almasri - King Abdulaziz University, Faculty of Dentistry Jeddah, Saudi Arabia Dentistry
\n\t
Craig Atwood - University of Wisconsin-Madison, USA Stem Cell Research, Tissue Engineering and Regenerative Medicine
\n\t
Oreste Capelli - Clinical Governance, Local Health Authority, Modena, Italy Public Health
\n\t
Michael Firstenberg - Assistant Professor of Surgery and Integrative Medicine NorthEast Ohio Medical University, USA & Akron City Hospital - Summa Health System, USA Surgery
\n\t
Parul Ichhpujani - MD Government Medical College & Hospital, Department of Ophthalmology, India
Amidou Samie - University of Venda, SA Infectious Diseases
\n\t
Shailendra K. Saxena - CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India Infectious Diseases
\n\t
Dan T. Simionescu - Department of Bioengineering, Clemson University, Clemson SC, USA Stem Cell Research, Tissue Engineering and Regenerative Medicine
\n\t
Ke Xu - Tianjin Lung Cancer Institute Tianjin Medical University General Hospital Tianjin, China Oncology
\n
\n\n
Ophthalmology
\n\n
\n\t
Hojjat Ahmadzadehfar - University Hospital Bonn Department of Nuclear Medicine Bonn, Germany Medical Diagnostics, Engineering Technology and Telemedicine
\n\t
Miroslav Blumenberg - Department of Ronald O. Perelman Department of Dermatology; Department of Biochemistry and Molecular Pharmacology, Dermatology, NYU School of Medicine, NY, USA Dermatology
\n\t
Wilfred Bonney - University of Dundee, Scotland, UK Medical Diagnostics, Engineering Technology and Telemedicine
\n\t
Christakis Constantinides - Department of Cardiovascular Medicine University of Oxford, Oxford, UK Medical Diagnostics, Engineering Technology and Telemedicine
\n\t
Atef Mohamed Mostafa Darwish - Department of Obstetrics and Gynecology , Faculty of Medicine, Assiut University, Egypt Gynecology
\n\t
Ana Polona Mivšek - University of Ljubljana, Ljubljana, Slovenia Midwifery
\n\t
Gyula Mozsik - First Department of Medicine, Medical and Health Centre, University of Pécs, Hungary
\n\t
Shimon Rumelt - Western Galilee-Nahariya Medical Center, Nahariya, Israel Ophthalmology
\n\t
Marcelo Saad - S. Paulo Medical College of Acupuncture, SP, Brazil Complementary and Alternative Medicine
\n\t
Minoru Tomizawa - National Hospital Organization Shimoshizu Hospital, Japan Gastroenterology
\n\t
Pierre Vereecken - Centre Hospitalier Valida and Cliniques Universitaires Saint-Luc, Belgium Dermatology
\n
\n\n
Gastroenterology
\n\n
\n\t
Hany Aly - Director, Division of Newborn Services The George Washington University Hospital Washington, USA Pediatrics
\n\t
Yannis Dionyssiotis - National and Kapodistrian University of Athens, Greece Orthopedics, Rehabilitation and Physical Medicine
\n\t
Alina Gonzales- Quevedo Instituto de Neurología y Neurocirugía Havana, Cuba Mental and Behavioural Disorders and Diseases of the Nervous System
\n\t
Margarita Guenova - National Specialized Hospital for Active Treatment of Haematological Diseases, Bulgaria
\n\t
Eliska Potlukova - Clinic of Medicine, University Hospital Basel, Switzerland Edocrinology
\n\t
Raymond L. Rosales -The Royal and Pontifical University of Santo Tomas, Manila, Philippines & Metropolitan Medical Center, Manila, Philippines & St. Luke's Medical Center International Institute in Neuroscience, Quezon City, Philippines Mental and Behavioural Disorders and Diseases of the Nervous System
\n\t
Alessandro Rozim - Zorzi University of Campinas, Departamento de Ortopedia e Traumatologia, Campinas, SP, Brazil Orthopedics, Rehabilitation and Physical Medicine
\n\t
Dieter Schoepf - University of Bonn, Germany Mental and Behavioural Disorders and Diseases of the Nervous System
\n
\n\n
Hematology
\n\n
\n\t
Hesham Abd El-Dayem - National Liver Institute, Menoufeyia University, Egypt Hepatology
\n\t
Fayez Bahmad - Health Science Faculty of the University of Brasilia Instructor of Otology at Brasilia University Hospital Brasilia, Brazil Otorhinolaryngology
\n\t
Peter A. Clark - Saint Joseph's University Philadelphia, Pennsylvania, USA Bioethics
\n\t
Celso Pereira - Coimbra University, Coimbra, Portugal Immunology, Allergology and Rheumatology
\n\t
Luis Rodrigo - Asturias Central University Hospital (HUCA) School of Medicine, University of Oviedo, Oviedo, Spain Hepatology & Gastroenterology
\n\t
Dennis Wat - Liverpool Heart and Chest Hospital NHS Foundation Trust, UK Pulmonology
\n
\n\n
Social Sciences and Humanities Board
\n\n
Business, Management and Economics
\n\n
\n\t
Vito Bobek - University of Applied Sciences, FH Joanneum, Graz, Austria
Denis Erasga - De La Salle University, Phillippines
\n\t
Rosario Laratta - Associate Professor of Social Policy and Development Graduate School of Governance Studies, Meiji University, Japan
\n
\n\n
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Research continuously innovates to develop efficient and cheap methods to sustain clean water for developing countries. Developing nations are a broad term that includes countries that are less industrialised and have lower per capita income levels than developed countries. This chapter will discuss clean water for drinking water purposes. Pollution concerns of water in developing countries will be categorised in terms of physical, chemical and biological pollutants such as turbidity, organic matter and bacteria. Natural and anthropogenic pollution concerns linking with seasonal factors will be outlined. The multi-barrier approach to drinking water treatment will be discussed. Abstraction points used will be researched. Water treatment systems, medium- to small-scale approaches, will be discussed. 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In it, the child gets involved independently. And so it prevents negative behaviors from occurring due to leisure and the need for attention, also favoring concentration.",book:{id:"10624",slug:"contemporary-developments-and-perspectives-in-international-health-security-volume-2",title:"Contemporary Developments and Perspectives in International Health Security",fullTitle:"Contemporary Developments and Perspectives in International Health Security - Volume 2"},signatures:"José Vilelas",authors:[{id:"343636",title:"Associate Prof.",name:"José",middleName:"Manuel",surname:"Vilelas",slug:"jose-vilelas",fullName:"José Vilelas"}]},{id:"75646",doi:"10.5772/intechopen.96039",title:"Neurological Complications in COVID-19: Implications on International Health Security and Possible Interventions of Phytochemicals",slug:"neurological-complications-in-covid-19-implications-on-international-health-security-and-possible-in",totalDownloads:252,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Global health security or international health security (IHS) includes any natural or man-made phenomenon that challenged human health and well-being including emerging infectious diseases such as the current global pandemic: COVID-19. Since the sudden outburst of COVID-19 pandemic in 2019, many COVID-19 patients have exhibited neurological symptoms and signs. Till now, there is no known effective established drug against the highly contagious COVID-19 infection despite the frightening associated mortality rate. This chapter aims to present the mechanism of action of coronavirus-2 (SARS-CoV-2), the clinical neurological manifestations displayed by COVID-19 patients, impact on the global health system and present phytochemicals with neuroprotective ability that can offer beneficial effects against COVID-19 mediated neuropathology. Reports from COVID-19 clinical studies, case reports, and other related literature were evaluated. Neurological complications of COVID-19 include anosmia, acute cerebrovascular disease, acute disseminated post-infectious encephalomyelitis, encephalitis, etc. Also, SARS-CoV-2 соuld be a neurotropic vіruѕ due to its iѕоlаtіоn from сеrеbrоѕріnаl fluіd. Multірlе nеurоlоgісаl dаmаgе displayed by COVID-19 patients might be due to hyperinflammation associated with SARS-CoV-2 infections. Kolaviron, resveratrol, vernodalin, vernodalol, and apigenin are natural phytochemicals with proven anti-inflammatory and therapeutic properties that could extenuate the adverse effects of COVID-19. The phytochemicals have been documented to suppress JNK and MAPK pathways which are essential in the pathogenesis of COVID-19. They also showed significant inhibitory activities against SARS-CoV-2 main protease. Taken together, these phytochemicals may offer neuroprotective benefits against COVID-19 mediated neuropathology and suppress the burden of the pandemic on IHS.",book:{id:"10624",slug:"contemporary-developments-and-perspectives-in-international-health-security-volume-2",title:"Contemporary Developments and Perspectives in International Health Security",fullTitle:"Contemporary Developments and Perspectives in International Health Security - Volume 2"},signatures:"Johnson Olaleye Oladele, Oluwaseun Titilope Oladele, Oyedotun M. Oyeleke and Adenike T. Oladiji",authors:[{id:"335880",title:"Dr.",name:"Johnson Olaleye",middleName:null,surname:"Oladele",slug:"johnson-olaleye-oladele",fullName:"Johnson Olaleye Oladele"},{id:"342648",title:"Mrs.",name:"Oluwaseun Titilope",middleName:null,surname:"Oladele",slug:"oluwaseun-titilope-oladele",fullName:"Oluwaseun Titilope Oladele"},{id:"342649",title:"Prof.",name:"Adenike T.",middleName:null,surname:"Oladiji",slug:"adenike-t.-oladiji",fullName:"Adenike T. Oladiji"},{id:"346531",title:"Dr.",name:"Oyedotun M.",middleName:null,surname:"Oyeleke",slug:"oyedotun-m.-oyeleke",fullName:"Oyedotun M. Oyeleke"}]},{id:"61814",doi:"10.5772/intechopen.78304",title:"Inequalities in Households’ Environmental Sanitation Practices in a Developing Nation’s City: The Example of Ile-Ife, Nigeria",slug:"inequalities-in-households-environmental-sanitation-practices-in-a-developing-nation-s-city-the-exam",totalDownloads:984,totalCrossrefCites:0,totalDimensionsCites:2,abstract:"A new global movement that emerged as a post 2015 development agenda is the sustainable development goals (SDGs). While the central objective of SDGs is to end poverty in all its forms, focus on water and sanitation rested on the fundamental concern for equity; moving from just service delivery to service delivery for all. Hence, the study reported in this chapter was set to examine the state of households’ environmental sanitation practices in different residential areas of Ile-Ife, Nigeria. A three-stage multi-sampling procedure was adopted in selecting 283 households’ heads for survey. Findings of study showed that 23.6, 41.2, and 68.4% of households in the core, transition, and sub-urban residential areas of Ile-Ife, respectively, have source of water within their residential building. Study established that households’ toilet facilities differ significantly in the study area, as respondents socio-economic characteristics varied across the identified residential areas of Ile-Ife. The study thus posited that, if cities in Nigeria and other developing nations will keep tract with timelines of the SDGs on water and sanitation, drastic, and realistic steps must be taken in addressing identified inequalities. This is a way to guaranty adequate hygiene and improved quality of life.",book:{id:"6682",slug:"the-relevance-of-hygiene-to-health-in-developing-countries",title:"The Relevance of Hygiene to Health in Developing Countries",fullTitle:"The Relevance of Hygiene to Health in Developing Countries"},signatures:"Faniran Gbemiga and Ojo Deborah",authors:[{id:"232193",title:"Dr.",name:"Gbemiga",middleName:null,surname:"Faniran",slug:"gbemiga-faniran",fullName:"Gbemiga Faniran"},{id:"233650",title:"Mrs.",name:"Deborah",middleName:null,surname:"Ojo",slug:"deborah-ojo",fullName:"Deborah Ojo"}]}],mostDownloadedChaptersLast30Days:[{id:"73634",title:"Supply Chain Management and Restart of Economy in Post COVID-19",slug:"supply-chain-management-and-restart-of-economy-in-post-covid-19",totalDownloads:712,totalCrossrefCites:0,totalDimensionsCites:2,abstract:"The increase in World Trade has led to significant growth in world GDP over last 100 years particularly. Supply chains have become the major enablers of world trade and the world is connected through supply chains. Any disruptions in any part of the world has led to disruptions in supply chains and economic recessions. Crisis like Tsunamis, earthquakes, 911 terror attacks, epidemics/pandemics like COVID-19 etc. have affected the businesses worldwide. COVID-19 pandemic has precipitated economic crisis due to disruption of supply chains and suppressed demand for many products and services worldwide. International Monetary Fund (IMF) has projected global economic growth to be negative 4.9%. This economic crisis has resulted in substantial erosion of market capitalization across the globe. The impact of COVID-19 is very significant on both health of the people and economy worldwide. Almost all businesses and governments are trying its best to save people from health and economic crisis. This requires rebuilding of supply chains through appropriate configuration with reliable sources of supply, collaboration, manufacturing and distribution of goods and services. Sectors like essential items, pharmaceutical, e-commerce have started early recovery of economy. However, other sectors require suitable interventions from government, business organizations in their policies and practices and use of digital technologies for economic recovery.",book:{id:"10624",slug:"contemporary-developments-and-perspectives-in-international-health-security-volume-2",title:"Contemporary Developments and Perspectives in International Health Security",fullTitle:"Contemporary Developments and Perspectives in International Health Security - Volume 2"},signatures:"Venkataramanaiah Saddikuti, Sagar Galwankar and Akilesh Sai Saddikuti Venkat",authors:[{id:"292211",title:"Associate Prof.",name:"Venkataramanaiah",middleName:null,surname:"Saddikuti",slug:"venkataramanaiah-saddikuti",fullName:"Venkataramanaiah Saddikuti"},{id:"293168",title:"Dr.",name:"Sagar C.",middleName:null,surname:"Galwankar",slug:"sagar-c.-galwankar",fullName:"Sagar C. Galwankar"},{id:"321650",title:"Mr.",name:"Akilesh Sai",middleName:null,surname:"S V",slug:"akilesh-sai-s-v",fullName:"Akilesh Sai S V"}]},{id:"63707",title:"Drinking Water Treatment and Challenges in Developing Countries",slug:"drinking-water-treatment-and-challenges-in-developing-countries",totalDownloads:7898,totalCrossrefCites:13,totalDimensionsCites:24,abstract:"Safe drinking water remains inaccessible to many humans in the developing countries. Research continuously innovates to develop efficient and cheap methods to sustain clean water for developing countries. Developing nations are a broad term that includes countries that are less industrialised and have lower per capita income levels than developed countries. This chapter will discuss clean water for drinking water purposes. Pollution concerns of water in developing countries will be categorised in terms of physical, chemical and biological pollutants such as turbidity, organic matter and bacteria. Natural and anthropogenic pollution concerns linking with seasonal factors will be outlined. The multi-barrier approach to drinking water treatment will be discussed. Abstraction points used will be researched. Water treatment systems, medium- to small-scale approaches, will be discussed. The processes involved in removing the contaminants including physical processes such as sedimentation, filtration such as slow-sand filtration, coagulation and flocculation, and disinfectant processes such as chlorination will be reviewed. Other important methods including solar disinfection, hybrid filtration methods and arsenic removal technologies using innovative solid phase materials will be included in this chapter. Rainwater harvesting technologies are reviewed. Safe storage options for treated water are outlined. Challenges of water treatment in rural and urban areas will be outlined.",book:{id:"6682",slug:"the-relevance-of-hygiene-to-health-in-developing-countries",title:"The Relevance of Hygiene to Health in Developing Countries",fullTitle:"The Relevance of Hygiene to Health in Developing Countries"},signatures:"Josephine Treacy",authors:[{id:"238173",title:"Dr.",name:"Josephine",middleName:null,surname:"Treacy",slug:"josephine-treacy",fullName:"Josephine Treacy"}]},{id:"63322",title:"Challenges to Hygiene Improvement in Developing Countries",slug:"challenges-to-hygiene-improvement-in-developing-countries",totalDownloads:2600,totalCrossrefCites:7,totalDimensionsCites:13,abstract:"Hygiene is defined as conditions or practices conducive to maintaining health and preventing disease. Hygiene has been shown to reduce diarrheal diseases and assist to improve social outcomes in the community. Improving hygiene faces several problems especially in countries with low income per capita of population. Currently, many developing countries already struggle to cope with consistent water shortages and rapid urbanization causing more pressure to limited resources which in turn result in poor hygienic practices in the communities. The common types of hygiene include personal hygiene, water hygiene, food hygiene, and hygiene during waste handling. Different nongovernmental and governmental organizations face different challenges in achieving high levels of hygiene in communities. Some of these challenges include poverty, lack of political commitment, lack of full community participation, inadequate gender inclusion, inadequate data, lack of coordination among actors, and behavioral issues. To reduce these challenges, several measures have been proposed including community empowerment, pushing for equitable access to hygiene needs, advocating for political commitment, promoting gender equity, and enhancing youth involvement.",book:{id:"6682",slug:"the-relevance-of-hygiene-to-health-in-developing-countries",title:"The Relevance of Hygiene to Health in Developing Countries",fullTitle:"The Relevance of Hygiene to Health in Developing Countries"},signatures:"Save Kumwenda",authors:[{id:"233913",title:"Mr.",name:"Save",middleName:null,surname:"Kumwenda",slug:"save-kumwenda",fullName:"Save Kumwenda"}]},{id:"63180",title:"Understanding the Hygiene Needs of People Living with HIV and AIDs in Southern African Developing Community (SADC) Countries",slug:"understanding-the-hygiene-needs-of-people-living-with-hiv-and-aids-in-southern-african-developing-co",totalDownloads:831,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This paper seeks to draw attention to the significance of integrating hygiene practices to HIV and AIDs programs in Southern African Developing Countries (SADC)—a region severely burdened by the disease. Integrating hygiene, in particular the habit of handwashing with soap and water, can reduce mortality rates and improve the livelihoods of people living with HIV and AIDS (PLWHA)—akin to Florence Nightingale’s moment (1850s). The paper uses survey data attained from PLWHA (South Africa) as case point to provide empirical views by PLWHA regarding their views and perceptions about hygiene practices and significance. Key observations are that: PLWHA lack sufficient knowledge on handwashing practices and apparently ignorant about their exposure and extent of vulnerability to opportunistic infections. This paper concludes by making a call for integration of hygiene (especially handwashing with soap and water) as part and parcel of HIV and AIDS programs as this will positively impact livelihoods of PLWHA in SADC. The paper ends continuous monitoring of WASH programs across SADC new 90-90-90 water-sanitation-hygiene indicator scoreboard necessary for continuous monitoring of WASH programs across SADC and equally other developing countries.",book:{id:"6682",slug:"the-relevance-of-hygiene-to-health-in-developing-countries",title:"The Relevance of Hygiene to Health in Developing Countries",fullTitle:"The Relevance of Hygiene to Health in Developing Countries"},signatures:"Ephias M. Makaudze",authors:[{id:"234230",title:"Dr.",name:"Ephias",middleName:null,surname:"Makaudze",slug:"ephias-makaudze",fullName:"Ephias Makaudze"}]},{id:"75488",title:"Management of Blood Supply and Blood Demand to Ensure International Health Security",slug:"management-of-blood-supply-and-blood-demand-to-ensure-international-health-security",totalDownloads:248,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Maintaining international health security requires proactive and reactive activities and actions to minimise the negative impact of any health event that threatens public health. Blood transfusion services are a critical part of healthcare services, and blood and blood products can neither be synthesized nor stored for a long period. So, proper management of blood supply and blood demand is mandatory to preserve adequate safe blood. A failure to manage blood inventory and the resulting blood shortage are considered national and international health security threats because maintaining an adequate supply of safe blood is lifesaving for many patients. Blood shortages lead to the failure of blood transfusion services that ends with the collapse of the health system and health insecurity if health authorities do not take immediate corrective action. An imbalance between blood supply and blood demand is not only a threat to health security, but also poses some of the greatest threats to the national and international economy and security. The perception of health issues as an international health security threat is associated with benefits through attracting political and decision-makers’ attention and support. The global health policies and international health regulations concerning the management of blood supply and blood demand should be implemented and updated regularly. The information provided by this chapter addresses the management of blood supply and blood demand as an international health security issue and provides guidance in planning for proper management of blood inventory to avoid a sudden blood shortage and its catastrophic consequences.",book:{id:"10624",slug:"contemporary-developments-and-perspectives-in-international-health-security-volume-2",title:"Contemporary Developments and Perspectives in International Health Security",fullTitle:"Contemporary Developments and Perspectives in International Health Security - Volume 2"},signatures:"Amar Ibrahim Omer Yahia",authors:[{id:"336945",title:"Dr.",name:"Amar",middleName:"Ibrahim Omer",surname:"Yahia",slug:"amar-yahia",fullName:"Amar Yahia"}]}],onlineFirstChaptersFilter:{topicId:"1335",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:8,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:286,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:9,numberOfPublishedChapters:101,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"
\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
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\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
",coverUrl:"https://cdn.intechopen.com/series/covers/24.jpg",latestPublicationDate:"April 24th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"262440",title:"Prof.",name:"Usha",middleName:null,surname:"Iyer-Raniga",slug:"usha-iyer-raniga",fullName:"Usha Iyer-Raniga",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRYSXQA4/Profile_Picture_2022-02-28T13:55:36.jpeg",biography:"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. Usha has been a keynote speaker as well as an invited speaker at national and international conferences, seminars and workshops. Her teaching experience includes teaching in Asian countries. She has advised Austrade, APEC, national, state and local governments. She serves as a reviewer and a member of the scientific committee for national and international refereed journals and refereed conferences. She is on the editorial board for refereed journals and has worked on Special Issues. Usha has served and continues to serve on the Boards of several not-for-profit organisations and she has also served as panel judge for a number of awards including the Premiers Sustainability Award in Victoria and the International Green Gown Awards. Usha has published over 100 publications, including research and consulting reports. Her publications cover a wide range of scientific and technical research publications that include edited books, book chapters, refereed journals, refereed conference papers and reports for local, state and federal government clients. She has also produced podcasts for various organisations and participated in media interviews. She has received state, national and international funding worth over USD $25 million. Usha has been awarded the Quarterly Franklin Membership by London Journals Press (UK). Her biography has been included in the Marquis Who's Who in the World® 2018, 2016 (33rd Edition), along with approximately 55,000 of the most accomplished men and women from around the world, including luminaries as U.N. Secretary-General Ban Ki-moon. In 2017, Usha was awarded the Marquis Who’s Who Lifetime Achiever Award.",institutionString:null,institution:{name:"RMIT University",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:5,paginationItems:[{id:"91",title:"Sustainable Economy and Fair Society",coverUrl:"https://cdn.intechopen.com/series_topics/covers/91.jpg",isOpenForSubmission:!0,editor:{id:"181603",title:"Dr.",name:"Antonella",middleName:null,surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo",profilePictureURL:"https://mts.intechopen.com/storage/users/181603/images/system/181603.jpg",biography:"Antonella Petrillo is a Professor at the Department of Engineering of the University of Naples “Parthenope”, Italy. She received her Ph.D. in Mechanical Engineering from the University of Cassino. Her research interests include multi-criteria decision analysis, industrial plant, logistics, manufacturing and safety. She serves as an Associate Editor for the International Journal of the Analytic Hierarchy Process. She is a member of AHP Academy and a member of several editorial boards. She has over 160 Scientific Publications in International Journals and Conferences and she is the author of 5 books on Innovation and Decision Making in Industrial Applications and Engineering.",institutionString:null,institution:{name:"Parthenope University of Naples",institutionURL:null,country:{name:"Italy"}}},editorTwo:null,editorThree:null},{id:"92",title:"Health and Wellbeing",coverUrl:"https://cdn.intechopen.com/series_topics/covers/92.jpg",isOpenForSubmission:!0,editor:{id:"348225",title:"Prof.",name:"Ann",middleName:null,surname:"Hemingway",slug:"ann-hemingway",fullName:"Ann Hemingway",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035LZFoQAO/Profile_Picture_2022-04-11T14:55:40.jpg",biography:"Professor Hemingway is a public health researcher, Bournemouth University, undertaking international and UK research focused on reducing inequalities in health outcomes for marginalised and excluded populations and more recently focused on equine assisted interventions.",institutionString:null,institution:{name:"Bournemouth University",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null},{id:"93",title:"Inclusivity and Social Equity",coverUrl:"https://cdn.intechopen.com/series_topics/covers/93.jpg",isOpenForSubmission:!0,editor:{id:"210060",title:"Prof. Dr.",name:"Ebba",middleName:null,surname:"Ossiannilsson",slug:"ebba-ossiannilsson",fullName:"Ebba Ossiannilsson",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6LkBQAU/Profile_Picture_2022-02-28T13:31:48.png",biography:'Professor Dr. Ebba Ossiannilsson is an independent researcher, expert, consultant, quality auditor and influencer in the fields of open, flexible online and distance learning (OFDL) and the "new normal". Her focus is on quality, innovation, leadership, and personalised learning. She works primarily at the strategic and policy levels, both nationally and internationally, and with key international organisations. She is committed to promoting and improving OFDL in the context of SDG4 and the future of education. Ossiannilsson has more than 20 years of experience in her current field, but more than 40 years in the education sector. She works as a reviewer and expert for the European Commission and collaborates with the Joint Research Centre for Quality in Open Education. Ossiannilsson also collaborates with ITCILO and ICoBC (International Council on Badges and Credentials). She is a member of the ICDE Board of Directors and has previously served on the boards of EDEN and EUCEN. Ossiannilsson is a quality expert and reviewer for ICDE, EDEN and the EADTU. She chairs the ICDE OER Advocacy Committee and is a member of the ICDE Quality Network. She is regularly invited as a keynote speaker at conferences. She is a guest editor for several special issues and a member of the editorial board of several scientific journals. She has published more than 200 articles and is currently working on book projects in the field of OFDL. Ossiannilsson is a visiting professor at several international universities and was recently appointed Professor and Research Fellow at Victoria University of Wellington, NZ. Ossiannilsson has been awarded the following fellowships: EDEN Fellows, EDEN Council of Fellows, and Open Education Europe. She is a ICDE OER Ambassador, Open Education Europe Ambassador, GIZ Ambassador for Quality in Digital Learning, and part of the Globe-Community of Digital Learning and Champion of SPARC Europe. On a national level, she is a quality developer at the Swedish Institute for Standards (SIS) and for ISO. She is a member of the Digital Skills and Jobs Coalition Sweden and Vice President of the Swedish Association for Distance Education. She is currently working on a government initiative on quality in distance education at the National Council for Higher Education. 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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.",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. 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",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology"},{id:"6",title:"Viral Infectious Diseases",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.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. This series is intended for doctors, engineers, and scientists involved in biomedical engineering or those wanting to start working in this field.",coverUrl:"https://cdn.intechopen.com/series/covers/7.jpg",latestPublicationDate:"May 7th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:3,numberOfPublishedChapters:96,numberOfPublishedBooks:12,editor:{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:null,institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda",middleName:"R.",surname:"Gharieb",fullName:"Reda Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. Osma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDv7QAG/Profile_Picture_1626602531691",institutionString:null,institution:{name:"Universidad de Los Andes",institutionURL:null,country:{name:"Colombia"}}},{id:"69697",title:"Dr.",name:"Mani T.",middleName:null,surname:"Valarmathi",fullName:"Mani T. Valarmathi",profilePictureURL:"https://mts.intechopen.com/storage/users/69697/images/system/69697.jpg",institutionString:"Religen Inc. | A Life Science Company, United States of America",institution:null},{id:"205081",title:"Dr.",name:"Marco",middleName:"Vinícius",surname:"Chaud",fullName:"Marco Chaud",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDGeQAO/Profile_Picture_1622624307737",institutionString:null,institution:{name:"Universidade de Sorocaba",institutionURL:null,country:{name:"Brazil"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/145270",hash:"",query:{},params:{id:"145270"},fullPath:"/profiles/145270",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)}()