Academic literature on the topic 'Cattle Genetics'
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Journal articles on the topic "Cattle Genetics"
Pirchner, F. "The Genetics of Cattle." Journal of Animal Breeding and Genetics 117, no. 6 (December 2000): 416. http://dx.doi.org/10.1046/j.1439-0388.2000.00259.x.
Full textWillis, Malcolm B. "The Genetics of Cattle." Heredity 84, no. 1 (January 2000): 131–32. http://dx.doi.org/10.1046/j.1365-2540.2000.0696b.x.
Full textEdwards, J. H. "The genetics of cattle." Journal of Genetics 80, no. 3 (December 2001): 155–58. http://dx.doi.org/10.1007/bf02717912.
Full textMacHugh, David E., Mark D. Shriver, Ronan T. Loftus, Patrick Cunningham, and Daniel G. Bradley. "Microsatellite DNA Variation and the Evolution, Domestication and Phylogeography of Taurine and Zebu Cattle (Bos taurus and Bos indicus)." Genetics 146, no. 3 (July 1, 1997): 1071–86. http://dx.doi.org/10.1093/genetics/146.3.1071.
Full textStock, Frauke, and Diane Gifford-Gonzalez. "Genetics and African Cattle Domestication." African Archaeological Review 30, no. 1 (March 2013): 51–72. http://dx.doi.org/10.1007/s10437-013-9131-6.
Full textBradley, Daniel G., Ronan T. Loftus, Patrick Cunningham, and David E. MacHugh. "Genetics and domestic cattle origins." Evolutionary Anthropology: Issues, News, and Reviews 6, no. 3 (1998): 79–86. http://dx.doi.org/10.1002/(sici)1520-6505(1998)6:3<79::aid-evan2>3.0.co;2-r.
Full textBishop, M. D., S. M. Kappes, J. W. Keele, R. T. Stone, S. L. Sunden, G. A. Hawkins, S. S. Toldo, R. Fries, M. D. Grosz, and J. Yoo. "A genetic linkage map for cattle." Genetics 136, no. 2 (February 1, 1994): 619–39. http://dx.doi.org/10.1093/genetics/136.2.619.
Full textMannen, H., S. Tsuji, R. T. Loftus, and D. G. Bradley. "Mitochondrial DNA Variation and Evolution of Japanese Black Cattle (Bos taurus)." Genetics 150, no. 3 (November 1, 1998): 1169–75. http://dx.doi.org/10.1093/genetics/150.3.1169.
Full textCrow, J. F. "Erwin Schrödinger and the hornless cattle problem." Genetics 130, no. 2 (February 1, 1992): 237–39. http://dx.doi.org/10.1093/genetics/130.2.237.
Full textVermeersch, A., and G. Opsomer. "Digital dermatitis in cattle." Vlaams Diergeneeskundig Tijdschrift 88, no. 5 (October 31, 2019): 247–58. http://dx.doi.org/10.21825/vdt.v88i5.15996.
Full textDissertations / Theses on the topic "Cattle Genetics"
Wang, Wei. "Plasminogen polymorphism in dairy cattle." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=26174.
Full textAfolayan, Raphael Abiodun. "Genetics of growth and development in cattle." Title page, table of contents and abstract only, 2003. http://web4.library.adelaide.edu.au/theses/09PH/09pha2579.pdf.
Full textPryce, Jennie Elizabeth. "Genetics of health and fertility in dairy cattle." Thesis, University of Edinburgh, 1997. http://hdl.handle.net/1842/23523.
Full textObike, Onyemauchechi Mercy. "Genetics of health and lameness in dairy cattle." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4113.
Full textGuarini, Aline Rocha [UNESP]. "Genetic relationship between reproductive traits in Nellore cattle." Universidade Estadual Paulista (UNESP), 2013. http://hdl.handle.net/11449/92557.
Full textThe aim of this study was to estimate genetic parameters between scrotal circumference obtained at 18 months of age (SC) and reproductive traits measured directly in Nellore females, such as number of calvings at 53 months (NC53), heifers rebreeding (HR) and stayability (STAY) in order to investigate the possibility of using traits measured directly in females as a selection criteria in cattle breeding programs, besides, studying and evaluating if number of calvings at 53 months could be used as an alternative way for measuring longevity in cattle herds. Two methods were applied for estimating variance components in order to predict breeding values: restricted maximum likelihood (REML) and Bayesian inference. The average estimates of heritability by bivariate model using REML were equal to 0.013 ± 0.003, 0.057 ± 0.007, 0.039 ± 0.007 and 0.530 ± 0.013 for NC53, STAY, HR and SC, respectively. Using the Bayesian method, the estimates were 0.22 ± 0.009, 0.19 ± 0.025, 0.15 ± 0.021 and 0.52 ± 0.019 for NC53, STAY, HR and SC, respectively. Based on the correlations between reproductive traits measured in females, the selection of animals for NC53 will cause anticipation on genetic evaluation of bulls for longevity, based on the performance of their daughters, from 76 to 53 months
Ali, Abdirahman. "Quantitative genetics and genomics of production and disease in beef cattle." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/12296.
Full textBrown, Pamela. "Cloning and characterisation of MHC class 1 genes in cattle." Thesis, University of Edinburgh, 1990. http://hdl.handle.net/1842/30048.
Full textSirol, Mirella Leme Franco Geraldini [UNESP]. "Análise da heterogeneidade de variância em características de crescimeno de bovinos da raça nelore." Universidade Estadual Paulista (UNESP), 2007. http://hdl.handle.net/11449/104056.
Full textCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Universidade Estadual Paulista (UNESP)
Foram utilizados dados de 116406 bovinos da raça Nelore, participantes do Programa de Melhoramento Genético da Raça Nelore (PMGRN), nascidos entre 1995 e 2005, com o objetivo de estimar parâmetros genéticos para os pesos padronizados aos 120(P120), 210(P210), 365(P365), 450(P450) e 730(P730) dias de idade e para os ganhos em peso do nascimento aos 120(GP120), dos 120 aos 210 (GP210), dos 210 aos 365(GP365), dos 365 aos 450(GP450) e dos 450 aos 730(G730), além de avaliar a tendência genética das características citadas, tanto para efeito direto como materno. Os componentes de variância foram estimados pelo método de máxima verossimilhança restrita utilizando o programa AIREMLF90, sob modelo animal, o qual incluiu como efeitos fixos, os grupos de contemporâneos e idade da vaca ao parto e como aleatórios, efeito genético aditivo direto para todas as características estudadas e efeito genético materno para P120, P210, P365, GP120, GP210 e GP365. As estimativas de herdabilidade direta foram 0,21, 0,22, 0,22, 0,34, 0,28, para cada peso, respectivamente, e 0,19, 0,20, 0,18, 0,18 e 0,20, para os respectivos ganhos em peso. As herdabilidades maternas foram 0,26, 0,25 e 0,12, para P120, P210 e P365 e 0,23, 0,17, 0,12 para GP120, GP210 e GP365. As correlações direto-maternas foram todas negativas, exceto para P365 (0,06). As tendências genéticas diretas foram todas positivas. As tendências maternas foram quase nulas para todas as características. As estimativas de herdabilidade para os pesos padronizados e para os ganhos em peso indicam que a seleção pode promover mudanças genéticas. As herdabilidades maternas para P120, P210, P365 e GP365 indicam que a seleção nestas características pode contribuir para melhorar a habilidade materna do rebanho. Os ganhos genéticos diretos observados, para todas as características estão aquém dos ganhos potenciais da raça Nelore...
Data of 116406 bovines of the Nellore beef cattle, participants of the Programa de Melhoramento Genético da Raça Nelore (PMGRN), been born between 1995 and 2005 were used with the objective to estimate genetic parameters for the 120-days weight (P120), 210-days weight (P210), 365-days weight (P365), 450-days weight (P450) and 730-days weight (P730) and for the weight gain from birth to 120(GP120), from 120 to 210(GP210), from 210 to 365(GP365), from 365 to 450(GP450) and from 450 to 730 days weight(GP730), besides evaluating the genetic trends of the traits, so much for the direct effect as for the maternal. The variance components were estimated by the restricted maximum likelihood method using the program AIREMLF90. The animal model included fixed effects for contemporary groups and age of the dam at calving, and also included random effects for genetic direct effects for all the studied traits and genetic maternal effect for P120, P210, P365, GP120, GP210 and GP365. The estimative of direct heritability were 0,21, 0,22, 0,22, 0,34, 0,28, for each weight, respectively and 0,19, 0,20, 0,18, 0,18 and 0,20, for the respective weight gains. The maternal heritability were 0,26, 0,25 and 0,12, for P120, P210 and P365 and 0,23, 0,17, 0,12 for GP120, GP210 and GP365. The direct-maternal correlations were all negatives except for P365 (0,06). The direct genetic trends were all positive ones. The maternal trends were almost null for all the traits. The estimative of heritability for the adjusted weights and for the weight gains indicated that the selection could promote genetic changes. The maternal heritability for P120, P210, P365 and GP365 indicated that the selection in these traits could contribute to improve the maternal ability of the herd. The direct genetic gain observed, for all the traits were on this side of the potential gain of the Nellore beef cattle... (Complete abstract click electronic access below)
Brotherstone, Susan H. "Genetics of production, type and herd life in dairy cattle." Thesis, University of Edinburgh, 1994. http://hdl.handle.net/1842/12813.
Full textBudeli, Mutshinya Ananias. "Genetics evaluation of tick resistance in South African Bonsmara cattle." Thesis, University of Limpopo (Turfloop Campus), 2010. http://hdl.handle.net/10386/883.
Full textThe objectives of the study were to estimate genetic parameters for tick resistance and to evaluate the effect of the level of tick infestation on the estimates of genetic parameters in South African Bonsmara cattle. Field data of repeated tick count records (n = 11 280) on 1 176 animals were collected between 1993 and 2005 by ten breeders participating in the National Beef Recording and Improvement Scheme. The distribution of tick count records were normalized using a Box-Cox transformation. Data were divided into 7 sub-data sets based on the mean tick count per contemporary group, to facilitate the investigation of the effect of level of tick infestation on the derived genetic parameters. A repeatability animal model including the fixed effects of contemporary group and age of animal at tick counting and random effects of the direct additive genetic, permanent environmental and residual effects was used to estimate genetic parameters using REML procedures. The additive genetic variances for tick count ranged from 0.01 to 0.08. Variances for the permanent environment ranged from 0.00 to 0.03. Phenotypic variance decreased with increasing mean tick count level while additive genetic variance increased with increasing mean tick count level. The heritability also increased with mean tick count level until a mean tick count level of ≥30. The highest heritability estimate obtained in the current study was 0.17 for data with mean tick count level ≥25. These results suggest that sufficient genetic variation for tick count exists in the Bonsmara cattle. Therefore genetic selection for tick resistance is feasible even though genetic progress may be slow.
the Limpopo Department of Agriculture (LDA) and the Department of Science and Technology (DST)
Books on the topic "Cattle Genetics"
Garrick, D. J., and A. Ruvinsky, eds. The genetics of cattle. Wallingford: CABI, 2015. http://dx.doi.org/10.1079/9781780642215.0000.
Full text1933-, Millar P., Lauvergne J. J, and Dolling, C. H. S. 1925-, eds. Mendelian inheritance in cattle 2000. Wangeningen: Wageningen Pers, 2000.
Find full textEAAP-Seminar, Study Commissions on Cattle Production and Animal Genetics (1988 Kiel Germany). New selection schemes in cattle: Nucleus programmes : proceedings of the EAAP-Seminar Study Commissions on Cattle Production and Animal Genetics, Kiel, Federal Republic of Germany, 1-2 December, 1988. Wageningen: Pudoc, 1989.
Find full textZavala, Daniel A. F. Villagomez. Synaptonemal complex analysis of chromosome translocations in pigs and cattle. Uppsala: Sveriges Lantbruksuniversitet, 1993.
Find full textV, Stepani͡u︡k E., and Zakharov I. A, eds. Ot͡s︡enka sily st͡s︡eplenii͡a︡ genov maloplodnykh selʹskokhozi͡a︡ĭstvennykh zhivotnykh na osnove populi͡a︡t͡s︡ionno-genealogicheskikh dannykh. Syktyvkar: Akademii͡a︡ nauk SSSR, Komi filial, In-t biologii, 1987.
Find full textWomack, James E. Bovine genomics. Ames, Iowa: Wiley-Blackwell, 2012.
Find full textBovine genomics. Ames, Iowa: Wiley-Blackwell, 2012.
Find full textVerschoor, Chris P. Unraveling the genetics of bovine Johne's disease. Hauppauge, N.Y: Nova Science Publishers, 2010.
Find full textSigurðardʹottir, Sunna. Studies of the class II genes of the major histocompatibility complex in cattle. Uppsala: Swedish University of Agricultural Sciences, Dept. of Animal Breeding and Genetics, 1991.
Find full textQuinn, Katherine. The genetic evaluation of calving ease and related traits in Ireland. Dublin: University College Dublin, 1998.
Find full textBook chapters on the topic "Cattle Genetics"
Rege, J. E. O., Joel Ochieng, and Olivier Hanotte. "Livestock genetics and breeding." In The impact of the International Livestock Research Institute, 59–102. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781789241853.0059.
Full textSchmutz, Sheila M. "Genetics of Coat Color in Cattle." In Bovine Genomics, 20–33. Oxford, UK: Wiley-Blackwell, 2012. http://dx.doi.org/10.1002/9781118301739.ch3.
Full textSimm, Geoff, Geoff Pollott, Raphael Mrode, Ross Houston, and Karen Marshall. "Beef cattle breeding." In Genetic improvement of farmed animals, 292–318. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789241723.0292.
Full textSimm, Geoff, Geoff Pollott, Raphael Mrode, Ross Houston, and Karen Marshall. "Dairy cattle breeding." In Genetic improvement of farmed animals, 234–91. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789241723.0234.
Full textDaigle, Courtney, Andy D. Herring, and Fuller W. Bazer. "Breeding and Welfare: Genetic Manipulation of Beef and Dairy Cattle." In The Welfare of Cattle, 93–108. Boca Raton : Taylor & Francis, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/b21911-11.
Full textSingh Kuntal, Ravinder, Radha Gupta, D. Rajendran, and Vishal Patil. "Binary Coded Genetic Algorithm to Solve Ration Formulation Problem." In Livestock Ration Formulation for Dairy Cattle and Buffalo, 27–43. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003231714-4.
Full textSchutz, M. M., V. Maciuc, K. Gay, and T. Nennich. "18. Survey of genetic selection on pasture-based dairy farms in the USA and Romania." In Cattle husbandry in Eastern Europe and China, 223–30. The Netherlands: Wageningen Academic Publishers, 2014. http://dx.doi.org/10.3920/978-90-8686-785-1_18.
Full textSimm, Geoff, Geoff Pollott, Raphael Mrode, Ross Houston, and Karen Marshall. "The origins and rôles of today's livestock breeds." In Genetic improvement of farmed animals, 1–10. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789241723.0001.
Full textSingh Kuntal, Ravinder, Radha Gupta, D. Rajendran, and Vishal Patil. "Least Cost Feed Formulation for Dairy Cattle during Pregnancy by Using Real Coded Genetic Algorithm." In Livestock Ration Formulation for Dairy Cattle and Buffalo, 45–68. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003231714-5.
Full textKasarda, Radovan, and Nina Moravčíková. "Genetic Uniqueness of Local Cattle Populations as Part of Homeland Heritage." In Environmental History, 127–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58092-6_9.
Full textConference papers on the topic "Cattle Genetics"
Neumann, G. B., P. Korkuć, P. Arends, M. J. Wolf, K. May, S. König, and G. A. Brockmann. "238. Phylogenetic analysis and nucleotide diversity of 69 cattle breeds including German Black Pied cattle using WGS." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_238.
Full textTalenti, A., J. Powell, D. Wragg, E. Paxton, M. Chepkwony, A. Miyunga, R. Njeru, et al. "417. Expanding the cattle reference graph genome." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_417.
Full textRönnegård, L., I. Hansson, and W. F. Fikse. "109. Heritability of social interactions in dairy cattle." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_109.
Full textT.M. Brown-Brandl, J.A. Nienaber, R.A. Eigenberg, T.L. Mader, J.L. Morrow, and J.W. Dailey. "Relative Heat Tolerance Among Cattle of Different Genetics." In 2003, Las Vegas, NV July 27-30, 2003. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2003. http://dx.doi.org/10.13031/2013.14093.
Full textHay, E., S. Toghiani, A. J. Roberts, T. Paim, L. A. Kuehn, and H. D. Blackburn. "193. Genetic architecture of a composite beef cattle population." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_193.
Full textLu, D., A. Garcia, S. Miller, and K. Retallick. "368. Haplotypes affecting pulmonary arterial pressure in Angus cattle." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_368.
Full textOget-Ebrad, C., G. C. M. Moreira, L. Karim, W. Coppieters, C. Charlier, M. Georges, and T. Druet. "201. Fine-scale study of meiotic recombination in cattle." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_201.
Full textJanuarie, D. A., E. D. Cason, and F. W. C. Neser. "219. Genetic characterization of the indigenous Sanga cattle of Namibia." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_219.
Full textSegelke, D., H. Alkhoder, and J. Wabbersen. "134. Image-based cattle conformation prediction using deep learning methods." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_134.
Full textSoma, P., B. B. Kooverjee, and M. M. Scholtz. "223. Runs of homozygosity in Nguni and Bonsmara cattle populations." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_223.
Full textReports on the topic "Cattle Genetics"
Mishra, Bishnu P., Julie A. L. Cavanagh, and James M. Reecy. Identifying genetic cause of Dwarfism in American Angus cattle. Ames (Iowa): Iowa State University, January 2004. http://dx.doi.org/10.31274/ans_air-180814-407.
Full textGarrick, Dorian J., Rohan L. Fernando, Kadir Kizilkaya, and James M. Reecy. High-Density SNP Genotypes for Predicting Genetic Merit of Beef Cattle. Ames (Iowa): Iowa State University, January 2009. http://dx.doi.org/10.31274/ans_air-180814-506.
Full textSun, Xiaochen, Hailin Su, and Dorian J. Garrick. Genetic Difference of Five Beef Cattle Breeds Characterized by Genome-wide SNPs and Haplotypes. Ames (Iowa): Iowa State University, January 2016. http://dx.doi.org/10.31274/ans_air-180814-498.
Full textTait, Richard G., Shu Zhang, Travis Knight, Daryl R. Strohbehn, Donald C. Beitz, and James M. Reecy. Genetic Correlations of Fatty Acid Concentrations with Carcass Traits in Angus-Sired Beef Cattle. Ames (Iowa): Iowa State University, January 2008. http://dx.doi.org/10.31274/ans_air-180814-501.
Full textSu, Hailin, Dorian J. Garrick, Bruce Golden, and Lauren Hyde. Estimation of Genetic Parameters for Carcass Traits and Their Corresponding Ultrasound Measurements in Crossbred Beef Cattle. Ames (Iowa): Iowa State University, January 2016. http://dx.doi.org/10.31274/ans_air-180814-486.
Full textBrosh, Arieh, Gordon Carstens, Kristen Johnson, Ariel Shabtay, Joshuah Miron, Yoav Aharoni, Luis Tedeschi, and Ilan Halachmi. Enhancing Sustainability of Cattle Production Systems through Discovery of Biomarkers for Feed Efficiency. United States Department of Agriculture, July 2011. http://dx.doi.org/10.32747/2011.7592644.bard.
Full textWeller, Joel, Harris Lewin, Micha Ron, George Wiggans, and Paul VanRaden. A Systematic Genome Search for Genes Affecting Economic Traits Dairy Cattle with the Aid of Genetic Markers. United States Department of Agriculture, April 1999. http://dx.doi.org/10.32747/1999.7695836.bard.
Full textGutierrez, Gustavo A., P. Jeff Berger, and Mary H. Healey. Joint Genetic Analysis of Conception and Maintenance of Pregnancy in Dairy Cattle Using a Linear-Threshold Model. Ames (Iowa): Iowa State University, January 2008. http://dx.doi.org/10.31274/ans_air-180814-948.
Full textWeller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.
Full textSaatchi, Mahdi, and Rohan L. Fernando. Empirical Progeny Equivalent for Genotyped Animals in Multi-breed Beef Cattle Genetic Evaluations Using Single-step Bayesian Regression Model. Ames (Iowa): Iowa State University, January 2018. http://dx.doi.org/10.31274/ans_air-180814-483.
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