Breeding programs in dairy cattle - current and future considerations

1988 ◽  
Vol 12 ◽  
pp. 129-152
Author(s):  
A. E. Freeman

Methods of evaluating dairy cattle using mixed models with Best Linear Unbiased Prediction properties have progressed from the sire model to the animal model. Definitions of effects in models need refinement, particularly for contemporary groups. Pedigree selection and progeny testing is the standard for producing sires used in artificial insemination, but multiple ovulation and embryo transfer schemes are being tried. Efficient production is necessary under conditions of surplus. Efficiency can be achieved by higher production per cow and reducing costs by improved reproduction, increased herd life, reduced health costs, and reduced dystocia. Preferential treatment is a major problem. New biotechnological developments such as bovine somatotropin, mitochondrial genetics, sexing semen, embryo transfers, cloning, transgenic animals, and markers are considered as potential new technologies that may be useful for dairy cattle improvement.

1980 ◽  
Vol 60 (3) ◽  
pp. 621-626 ◽  
Author(s):  
L. R. SCHAEFFER ◽  
HOON SONG ◽  
J. W. WILTON

Three methods of evaluating beef sires for weaning weight with data obtained from an organized young sire progeny testing program were compared. Information from Agriculture Canada’s National Beef Sire Monitoring Program was utilized along with computational procedures based on best linear unbiased prediction. The methods were applied to data from the Canadian Simmental Association as an illustration of the methods. A model which incorporates the proofs of the reference sires into the comparisons with test bulls was considered more appropriate than the other two models compared. The results also showed that even in an organized progeny test program, test bulls are not truly mated to cows of equal merit or across equal herd environments.


2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 22-23
Author(s):  
Michael M Lohuis

Abstract Dairy cattle breeding programs have been transformed from conventional progeny-testing schemes to genomic selection paired with nucleus herd breeding in the span of one decade. This was spurred by the simultaneous advances in low-cost SNP genotyping, genomic selection methodology and reproductive biotechnologies. The rates of genetic progress have approximately doubled in this time but so have increases in inbreeding levels. This was driven by intense competition between AI studs and farmer adherence to common selection indices which has concentrated selection on very elite segments of juvenile age groups. This has led to speculation on the need for alternative indices and selection for novel traits in order to differentiate breeding programs and customize selection for unique farm conditions. This will be made more possible by the advent of on-farm sensor technology and artificial intelligence algorithms. Large commercial dairies are increasingly experimenting with crossbreeding with varying levels of success and this will require a new approach by breeding programs to focus both on purebred and crossbred performance. In addition, the potential exists for use of gene-editing to further enable value-added traits to be added into breeding programs. In parallel with breeding program advancements, consumer trends are also changing to include more interest in specialty dairy products with implied differences in digestibility, health or environmental impacts. Identifying technologies and traits that will add value either on the farm as well as at the consumer level will be a challenge for today’s breeders and producers. Some new technologies, such as gene editing, can pose consumer acceptance challenges if they are perceived to be used carelessly or for the wrong reasons. Careful choices will need to be made to continue to improve profitability, functionality and health of dairy cattle while also meeting higher consumer standards for animal welfare, health and the environment.


1990 ◽  
Vol 14 ◽  
pp. 13-22
Author(s):  
M. K. Curran

AbstractThis paper is a review of practical sheep breeding improvement schemes and techniques in the UK. Recent breed population changes in each of the broad categories of hill, longwool/crossing, longwool ewe, terminal sire and shortwool ewe breeds are outlined. Current or planned improvement programmes are reported for Welsh Mountain, Beulah, Scottish Blackface, Border Leicester, Cambridge, Friesland, Romney, Texel, Suffolk, Lleyn and Merino breeds. The techniques of genetic improvement currently available are discussed including some costs and likely genetic gains; techniques include group breeding schemes, artificial insemination, multiple ovulation and embryo transplant, best linear unbiased prediction and transgenic methods. The application of these techniques and contribution they could make to future sheep improvement are assessed.


Author(s):  
R.B. Land ◽  
G. Simm ◽  
R. Thompson ◽  
J.A. Woolliams

Dairying is the largest single sector of British agriculture. European milk production is however in surplus and the imposition of quotas has put pressure on the industry. It has also constrained the interaction of the industry with market forces and hence its potential for progressive development. The greater the pressure the more important is efficency and hence the greater the need for and the benefits from genetic improvement. This paper reviews breeding objectives for dairy cattle, and considers the opportunities for the uptake of new technologies such as multiple ovulation and embryo transfer, and physiological predictors of genetic merit.Concentration on clear and limited breeding goals is crucial to the success of any breeding programme. This is probably the principal factor underlying the greater genetic progress achieved in North America and New Zealand than in Europe.Gibson (1987) has estimated that the optimum ratio of fat:protein In milk for processing is currently about 1.65:1 (i.e. 5.6% fat would be required to match the current average protein production of about 3.4%). Even with a 30% fall In consumption of dairy fat, the optimum fat % in milk for manufacturing would still be 3.8—4.7%.


1995 ◽  
Vol 1995 ◽  
pp. 129-129
Author(s):  
R Mrode ◽  
G J T Swanson

A multi-variate animal model Best Linear Unbiased Prediction (BLUP) on milk, fat and protein yields in different lactations, as different traits, is the optimum method for genetic evaluation in dairy cattle for production. However, this is computationally demanding and usually a repeatability model is performed separately for milk, fat and protein yields. A simulation study by Visscher (1991) showed that the repeatability model on canonical transformed yield rather than on observed yield was a better approximation to a multi-variate analysis using selection index. The aim of this study is to verify, using an animal model, the efficiency of the repeatability model relative to a multi-variate analysis on observed or transformed yields.


Author(s):  
G.J.T. Swanson ◽  
H J Bellamy

The Artificial Insemination organisation of the Milk Marketing Board (MMB) (now Genus) progeny tests approximately 100 Friesian/Holstein bulls each year in co-operating milk recorded herds. In 1983 a linear assessment evaluation scheme was introduced in order to describe the conformation of animals in a more objective way. In conjunction with the Holstein Friesian Society it was agreed to score 16 main traits in the assessment scheme. The MMB also included a seventeenth trail, Beef Shape. The linear assessment scores are analysed by Best Linear Unbiased Prediction to provide sire evaluations on the bulls in the progeny testing scheme. The purpose of this study was to evaluate the environmental and genetic parameters for the traits assessed in the scheme during the first two years.


1983 ◽  
Vol 63 (3) ◽  
pp. 511-522 ◽  
Author(s):  
T. R. BATRA ◽  
A. J. McALLISTER ◽  
A. J. LEE ◽  
C. Y. LIN ◽  
G. L. ROY ◽  
...  

Data on body weights and dimensions from birth to 82 wk of age on 1216 heifers of the National Cooperative Dairy Cattle Breeding Project were analyzed using best linear unbiased prediction (BLUP) procedures. The effects of station, year of birth, dam's parity, line of sire, line of dam, interaction between line of sire and line of dam and sires within sire line were estimated. Age at first calving was included in the model as a covariate for body weights and dimensions taken after 50 wk of age. All effects except sire were assumed to be fixed. The effect of station was significant (P < 0.01) for all traits studied. The effects of year of birth and dam's parity were significant (P < 0.05) for more than half of the traits studied. Line of sire, line of dam and their interaction effects were significant (P < 0.05) for most of the body weights and dimensions. The effect of line of dam was much greater than line of sire for all traits. The non-additive genetic effect from crossing lines H and A resulted in a 1.9–3.8% increase in body weights and up to 1.6% increase in body dimensions taken from birth to 82 wk of age. Key words: Body weights, dimensions, pureline, crossline, dairy cattle


1979 ◽  
Vol 59 (1) ◽  
pp. 203-206 ◽  
Author(s):  
T. R. BATRA

The Best Linear Unbiased Prediction method is used to evaluate dairy sires in Canada. Milk and fat production records of 2-yr-old Ayrshire, Guernsey, Holstein and Jersey cows calved from 1958 through 1975 were used in the sire evaluation done in November 1976. Genetic trends were estimated as twice the change in weighted average of sire proofs per year. Genetic trends for milk and fat production were 1.32 and 1.62 BCA for Ayrshire; 1.50 and.88 BCA for Guernsey;.72 and.80 BCA for Holstein; and.60 and.54 BCA for Jersey, respectively.


BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Ainhoa Calleja-Rodriguez ◽  
Jin Pan ◽  
Tomas Funda ◽  
Zhiqiang Chen ◽  
John Baison ◽  
...  

Abstract Background Genomic selection (GS) or genomic prediction is a promising approach for tree breeding to obtain higher genetic gains by shortening time of progeny testing in breeding programs. As proof-of-concept for Scots pine (Pinus sylvestris L.), a genomic prediction study was conducted with 694 individuals representing 183 full-sib families that were genotyped with genotyping-by-sequencing (GBS) and phenotyped for growth and wood quality traits. 8719 SNPs were used to compare different genomic with pedigree prediction models. Additionally, four prediction efficiency methods were used to evaluate the impact of genomic breeding value estimations by assigning diverse ratios of training and validation sets, as well as several subsets of SNP markers. Results Genomic Best Linear Unbiased Prediction (GBLUP) and Bayesian Ridge Regression (BRR) combined with expectation maximization (EM) imputation algorithm showed slightly higher prediction efficiencies than Pedigree Best Linear Unbiased Prediction (PBLUP) and Bayesian LASSO, with some exceptions. A subset of approximately 6000 SNP markers, was enough to provide similar prediction efficiencies as the full set of 8719 markers. Additionally, prediction efficiencies of genomic models were enough to achieve a higher selection response, that varied between 50-143% higher than the traditional pedigree-based selection. Conclusions Although prediction efficiencies were similar for genomic and pedigree models, the relative selection response was doubled for genomic models by assuming that earlier selections can be done at the seedling stage, reducing the progeny testing time, thus shortening the breeding cycle length roughly by 50%.


Author(s):  
Ângela Martins ◽  
Virgínia Santos ◽  
Mário Silvestre

ResumoA história do melhoramento genético animal acompanha a história da Humanidade, começando com a domesticação do primeiro animal, que terá sido o cão, ao qual se seguiram os bovinos, ovinos e todas as outras espécies que deram origem às raças domésticas da atualidade. Inicialmente a seleção de reprodutores era efetuada de forma empírica. No século XVIII R. Bakewell foi pioneiro na utilização de registos produtivos e testes de descendência. No final deste século começaram a ser estabelecidos os livros genealógicos de diversas raças. No século XIX, os avanços científicos protagonizados por C. Darwin e G. Mendel são fundamentais para que, na primeira metade do século XX se desenvolva a maior parte da teoria do melhoramento animal, com o contributo de vários investigadores (R. Fisher, S. Wright, J. Haldane). Jay Lush ficou conhecido como o pai do melhoramento animal moderno. Defendeu que em vez da aparência subjetiva, o melhoramento animal deve-se basear em conhecimentos da genética quantitativa e da estatística. Charles Henderson apresentou o método Best Linear Unbiased Prediction (BLUP) para a estimativa do valor genético aditivo e sugeriu a integração da genealogia completa da população para incluir as relações genéticas entre os indivíduos. A evolução dos computadores permitiu a implementação generalizada do BLUP no final da década de 1980. Nos últimos tempos T. Meuwissen e M. Goddard desenvolveram a forma de incorporar informação do ADN em grande escala no modelo animal para estimar os valores genómicos. Palavras-chave: genética, melhoramento animal Abstract The history of animal breeding follows the history of humanity, beginning with the domestication of the first animal, which was the dog, followed by the cattle, sheep and all other species that gave rise to the domestic breed of the present time. Initially the selection of breeders was carried out empirically. In the eighteenth century R. Bakewell pioneered the use of records of performance of animals and progeny testing. At the end of this century herdbooks of various breeds began to be established. In the 19th century, the scientific advances made by Darwin and Mendel are fundamental for the, in the first half of the 20th century, development of most animal breeding theory with the contribution of several researchers (R. Fisher, S. Wright, J. Haldane). Jay Lush became known as the father of modern animal breeding. He argued that instead of subjective appearance, animal breeding should be bas 


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