scholarly journals Evaluation of updated Feed Saved breeding values developed in Australian Holstein dairy cattle

2022 ◽  
Author(s):  
S. Bolormaa ◽  
I.M. MacLeod ◽  
M. Khansefid ◽  
L.C. Marett ◽  
W.J. Wales ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Breeding Values

scholarly journals Animal Model Versus Polynomial Legendre Test-Day In Dairy Cattle

2020 ◽  
Vol 23 (1) ◽  
pp. 5-12
Author(s):  
Mircea Cătălin Rotar ◽  
Horia Grosu ◽  
Mihail Alexandru Gras ◽  
Rodica Ştefania Pelmuş ◽  
Cristina Lazăr ◽  
...  
Keyword(s):  
Animal Model ◽  
Dairy Cattle ◽  
Fixed Effects ◽  
Rank Correlation ◽  
Pedigree Information ◽  
Lactation Period ◽  
Data Set ◽  
Breeding Values ◽  
Normal Limits ◽  
Model Versus

AbstractThe aim of the study was to compare the classical animal model (based on total milk for 305 days) with the Test-Day model (using monthly records of milk yield from Official Records of Performances). The data set derived from a total 175 animals (cows with records, parents of these animals and the descendants) from two Romanian breeds (Romanian Black Spotted and Montbeliarde), the phenotypic and the pedigree information arisen from National Research Development Institute for Animal Biology and Nutrition (IBNA-Balotesti). The selection criteria to be included in the analysis for each cow was to have at least 3 test-days and the days in milk between 200 and 330 for the Test-Day model and the total amount of the 305- day lactation yield for classical Animal Model respectively. Both models use B.L.U.P methodology and for that reason all the estimates were adjusted for fixed effects and all the breeding values and the solution for fixed effects were estimated simultaneous. For the animal model the fixed effects used was the breed and the year of performing and for the Test-Day model was an extra one, the test day effect. The correlation calculated between test days was very high (over 90%) for consecutive tests, and was getting lower when the days between tests was higher (under 40%). Also, in terms of heritability the values were in normal limits throughout lactation, except at the beginning and end of lactation period where these values were a little bit higher. The comparison of the ranking of breeding values with Spearman rank correlation shows that in 80% of the cases the ranking was similar for both models. As the ranking correlations shows, it is certain that the two models are very similar when they are used for genetic evaluation. But, in conclusion, we can say that for a better lactation curve estimation it is recommending to use test-day model for dairy cattle.

scholarly journals Associations between SNPs in the bovine GnRH receptor gene and breeding values for fertility traits in dairy cattle

2010 ◽  
Vol 1 (1) ◽  
pp. 214-214
Author(s):  
K Derecka ◽  
S Ahmad ◽  
TC Hodgman ◽  
N Hastings ◽  
MD Royal ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Receptor Gene ◽  
Gnrh Receptor ◽  
Breeding Values ◽  
Fertility Traits

Dairy cattle breeding.

2021 ◽  
pp. 234-291
Author(s):  
Geoff Simm ◽  
Geoff Pollott ◽  
Raphael Mrode ◽  
Ross Houston ◽  
Karen Marshall
Keyword(s):  
Genetic Analysis ◽  
Dairy Cattle ◽  
Selection Response ◽  
Animal Breeding ◽  
Technology Selection ◽  
Cattle Breeding ◽  
Breeding Values ◽  
Breeding Technology ◽  
Dairy Cattle Breeding

Abstract This chapter discussed the effects of applying the different principles in animal breeding such genetic analysis, predicting breeding values, use of tools and breeding technology, selection response within breeds, and strategies for genetic improvements in dairy cattle.

Genetic line × concentrate level interactions for milk production and feed efficiency in dairy cattle

1992 ◽  
Vol 72 (2) ◽  
pp. 227-236 ◽  
Author(s):  
S. Wang ◽  
G. L. Roy ◽  
A. J. Lee ◽  
A. J. McAllister ◽  
T. R. Batra ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Feed Efficiency ◽  
Production Efficiency ◽  
Breeding Value ◽  
Environment Interaction ◽  
Genetic Line ◽  
Breeding Values ◽  
Concentrate Level

Early first lactation data from 2230 cows of five research herds of Agriculture Canada were used to study the interactions of genetic line by concentrate level, and sire by concentrate level and to estimate breeding values of sires. The genetic lines were defined as Holstein (H), Ayrshire (A), and H × A or A × H (C). The interactions of sire by concentrate level were studied separately using progeny of five different mating groups: G1, H sires mated to H cows; G2, H sires mated to H, A and C cows; G3, A sires mated to A cows; G4, A sires mated to H, A and C cows; and G5, C sires mated to C cows. The interactions of genetic line by concentrate were significant (P < 0.05) for 56- to 112-d milk yield (MY112), corrected 56-to 112-d milk yield (CMY112) and feed efficiency (EFMY112 = MY112/TDN consumption). H and C cows produced more milk and were more efficient than A cows when fed high levels of concentrate. The H cattle possess a greater capacity to convert the concentrate into milk, while A cattle reach maximum milk production earlier than H cattle. The interactions of sire by concentrate were statistically significant for MY112, EFMY112 and CMY112 in G1 (P < 0.01), and G2 (P < 0.01). The breeding values of sires for MY112 were estimated using BLUP for all of the H line (BLUP-T), for half of the population consuming low amounts of concentrate (BLUP-L) and for the other half consuming high amounts (BLUP-H). A significant reranking of sires was found among the three groups. Key words: Genotype × environment interaction, milk production, efficiency, breeding value, dairy cattle

Top down preselection using marker assisted estimates of breeding values in dairy cattle

2004 ◽  
Vol 121 (5) ◽  
pp. 307-318 ◽  
Author(s):  
Jorn Bennewitz ◽  
Norbert Reinsch ◽  
Friedrich Reinhardt ◽  
Zengting Liu ◽  
Ernst Kalm
Keyword(s):  
Dairy Cattle ◽  
Top Down ◽  
Breeding Values

scholarly journals Designing dairy cattle breeding schemes under genomic selection: a review of international research

2012 ◽  
Vol 52 (3) ◽  
pp. 107 ◽  
Author(s):  
J. E. Pryce ◽  
H. D. Daetwyler
Keyword(s):  
Dairy Cattle ◽  
Genomic Selection ◽  
Genetic Gain ◽  
Reproductive Technologies ◽  
Progeny Testing ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Scheme Design ◽  
Dairy Cattle Breeding ◽  
Breeding Schemes

High rates of genetic gain can be achieved through (1) accurate predictions of breeding values (2) high intensities of selection and (3) shorter generation intervals. Reliabilities of ~60% are currently achievable using genomic selection in dairy cattle. This breakthrough means that selection of animals can happen at a very early age (i.e. as soon as a DNA sample is available) and has opened opportunities to radically redesign breeding schemes. Most research over the past decade has focussed on the feasibility of genomic selection, especially how to increase the accuracy of genomic breeding values. More recently, how to apply genomic technology to breeding schemes has generated a lot of interest. Some of this research remains the intellectual property of breeding companies, but there are examples in the public domain. Here we review published research into breeding scheme design using genomic selection and evaluate which designs appear to be promising (in terms of rates of genetic gain) and those that may have unfavourable side-effects (i.e. increasing the rate of inbreeding). The schemes range from fairly conservative designs where bulls are screened genomically to reduce numbers entering progeny testing, to schemes where very large numbers of bull calves are screened and used as sires as soon as they reach sexual maturity. More radical schemes that incorporate the use of reproductive technologies (in juveniles) and genomic selection in nucleus herds are also described. The models used are either deterministic and more recently tend to be stochastic, simulating populations of cattle. A key driver of the rate of genetic gain is the generation interval, which could range from being similar to that in conventional testing (~5 years), down to as little as 1.5 years. Generally, the rate of genetic gain is between 12% and 100% more than in conventional progeny testing, while the rate of inbreeding tends to be lower per generation than in progeny testing because Mendelian sampling terms can be estimated more accurately. However, short generation intervals can lead to higher rates of inbreeding per year in genomic breeding programs.

scholarly journals A method for implementing methane breeding values in Australian dairy cattle

2021 ◽  
Author(s):  
C. M. Richardson ◽  
B. Sunduimijid ◽  
P. Amer ◽  
I. van den Berg ◽  
J. E. Pryce
Keyword(s):  
Dairy Cattle ◽  
Breeding Values
Sign in / Sign up

Export Citation Format

Share Document