EVALUATION OF DAIRY CATTLE FOR FINAL CLASS USING ANIMAL MODELS

1988 ◽  
Vol 68 (3) ◽  
pp. 639-645 ◽  
Author(s):  
J. JAMROZIK ◽  
L. R. SCHAEFFER
Keyword(s):  
Animal Models ◽  
Dairy Cattle ◽  
Fixed Effects ◽  
Genetic Relationships ◽  
Residual Effects ◽  
Breeding Values ◽  
Stage Of Lactation ◽  
Key Words Animal ◽  
Estimated Breeding Values ◽  
Genetic Evaluations

Estimated breeding values for final class of 364 868 Canadian Holstein Friesian cows and 10 186 bulls from three different animal models were compared. FIRST lactation, first classifications were described by a model with fixed effects of herd-round-classifier, linear and quadratic effects of age at calving and stage of lactation at classification, and random effects of additive genetic effects of cows, and residual effects. All additive genetic relationships among animals were included. A second model used the LATEST classification on each cow rather than the first and these observations were pre-adjusted for age and stage. The third model used ALL classifications on each cow, and these were also pre-adjusted for age and stage effects. Correlations among estimated breeding values between methods ranged from 0.92 to 0.95. Estimated breeding values from LATEST were most highly correlated to sire proofs from the currently official sire model which also used the latest classification of each cow. Correlations of estimated breeding values between sires and their sons showed that results from LATEST were more accurate than results from the other two models. A model similar to that for LATEST is proposed for official genetic evaluations for conformation in the Canadian Holstein population. Key words: Animal model, conformation, dairy cattle

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.

Practical aspects of a genetic evaluation system using parentage assigned from genetic markers

2005 ◽  
Vol 45 (8) ◽  
pp. 935 ◽  
Author(s):  
K. G. Dodds ◽  
J. A. Sise ◽  
M. L. Tate
Keyword(s):  
Genetic Markers ◽  
Evaluation System ◽  
Fixed Effects ◽  
Genetic Evaluation ◽  
Diagnostic Systems ◽  
Breeding Values ◽  
Mating Group ◽  
Animal Management ◽  
The Mean ◽  
Estimated Breeding Values

Animal breeding values can be calculated when genetic markers have been used to help determine the parentage of some of the animals, but their parentage has been incompletely determined. The pedigree sampling method is 1 computing strategy for calculating these breeding values. This paper describes and discusses methods for dealing with a number of practical issues that arise when implementing such a system for industry use. In particular, diagnostic systems for detecting inadequacies or possible errors in the genotyping systems and the recording of animal management are developed. Also, characteristics of the best assigned pedigrees are calculated according to mating group and used to check for sires missing from these groups. The correlation between breeding values estimated from a single sampled pedigree (using parentage probabilities) and those estimated as the mean from many sampled pedigrees gives a diagnostic to indicate which estimated breeding values are more influenced by uncertainties in relationships. For the analysis of survival traits, a method to enumerate and assign likely parentage to dead offspring which have not been DNA sampled and genotyped is described. When embryo transfer technology is used, the genetic dam needs to be included as a possible dam when considering parentage. If some fixed effects which depend on the parent are missing, these can be sampled similarly to parentage, and this may improve the evaluation if certain assumptions are met. A method to provide a likely list of parents, the ‘fitted pedigree’, which is based on the most likely parents, but modified to reduce the occurrence of unlikely family sets (e.g. very large litters) is also presented. The use of these methods will enhance the practical application of DNA parenting when used in conjunction with genetic evaluation.

scholarly journals Inclusion of bioclimatic variables in genetic evaluations of dairy cattle

2021 ◽  
Vol 34 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Renata Negri ◽  
Ignacio Aguilar ◽  
Giovani Luis Feltes ◽  
Juliana Dementshuk Machado ◽  
José Braccini Neto ◽  
...  
Keyword(s):  
Heat Stress ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Fixed Effects ◽  
Information Criterion ◽  
Least Square ◽  
Random Regression ◽  
Yield Losses ◽  
Bioclimatic Variables ◽  
Genetic Evaluations

Objective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models.Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models.Results: The THI and DTV thresholds for milk yield losses was THI = 74 (–0.106 kg/d/THI) and DTV = 13 (–0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (–2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model.Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability.

scholarly journals Reliability of breeding values between random regression and 305-day lactation models

2016 ◽  
Vol 51 (11) ◽  
pp. 1848-1856
Author(s):  
Alessandro Haiduck Padilha ◽  
◽  
Jaime Araujo Cobuci ◽  
Darlene dos Santos Daltro ◽  
José Braccini Neto
Keyword(s):  
Legendre Polynomials ◽  
Regression Models ◽  
Protein Yield ◽  
Random Regression ◽  
Holstein Cattle ◽  
Average Increase ◽  
Data Set ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Genetic Evaluations

Abstract The objective of this work was to verify the gain in reliability of estimated breeding values (EBVs), when random regression models are applied instead of conventional 305-day lactation models, using fat and protein yield records of Brazilian Holstein cattle for future genetic evaluations. Data set contained 262,426 test-day fat and protein yield records, and 30,228 fat and protein lactation records at 305 days from first lactation. Single trait random regression models using Legendre polynomials and single trait lactation models were applied. Heritability for 305-day yield from lactation models was 0.24 (fat) and 0.17 (protein), and from random regression models was 0.20 (fat) and 0.21 (protein). Spearman correlations of EBVs, between lactation models and random regression models, for 305-day yield, ranged from 0.86 to 0.97 and 0.86 to 0.98 (bulls), and from 0.80 to 0.89 and 0.81 to 0.86 (cows), for fat and protein, respectively. Average increase in reliability of EBVs for 305-day yield of bulls ranged from 2 to 16% (fat) and from 4 to 26% (protein), and average reliability of cows ranged from 24 to 38% (fat and protein), which is higher than in the lactation models. Random regression models using Legendre polynomials will improve genetic evaluations of Brazilian Holstein cattle due to the reliability increase of EBVs, in comparison with 305-day lactation models.

Effect of controlling future rate of inbreeding on expected genetic gain and genetic variability in small livestock populations

2020 ◽  
Vol 60 (14) ◽  
pp. 1681
Author(s):  
S. I. Mwangi ◽  
T. K. Muasya ◽  
E. D. Ilatsia ◽  
A. K. Kahi
Keyword(s):  
Genetic Variability ◽  
Milk Yield ◽  
Genetic Gain ◽  
Genetic Relationships ◽  
Breeding Population ◽  
Breeding Values ◽  
Sahiwal Cows ◽  
Improvement Programs ◽  
Small Livestock ◽  
Estimated Breeding Values

Context In the present study we assessed the use of average relationship as a means to control future rates of inbreeding in small cattle closed nucleus and its effect on genetic gain for milk yield as a means of managing genetic variability in livestock improvement programs. Aim The aim was to strike an ideal balance between genetic gain and loss of genetic variability for Sahiwal population. Methods A total of 8452 milk yield records of Sahiwal cows from National Sahiwal Stud, Kenya, were used to estimate breeding values and 19315 records used to estimate average relatedness of all individuals. The estimated breeding values and genetic relationships were then used to optimise individual genetic contributions between the best two males and the top 210 females in 2000–2008-year group, as well as between the best four, six and eight males and top, 420, 630 and 840 females based on estimated breeding values for lactation milk yield. Weights on genetic merit and average relationship considered in this study were (1, 0), (1, −300), (1, −500), (1, −1000) and (0, −1). Key results When the best sires were selected and used for mating disregarding average relationship with their mates i.e. (0, –1), genetic gain of up to 213 kg was realised accompanied by a rate of inbreeding per generation of 4%. Restricting average relationship alone i.e. (0, –1), resulted in a future rate of inbreeding of 1.6% and average merit of 154 when top two sires were used for breeding. At the same restriction level but using eight top sires, the rate of inbreeding per generation was 0.9% accompanied by an average merit of 128.2 kg. Controlling average relationship between mates resulted in increased genetic variability i.e. lower rate of inbreeding though average merit declined. Conclusion A rate of inbreeding per generation of <1% is required for a population to maintain its long-term viability. For this level to be attained, the size of the breeding population should be increased from the current two sires vs 210 dams to eight sires vs 840 dams. Implications Practical implications for closed nucleus programs such as the Sahiwal program in Kenya should include expanding the nucleus to comprise other institutional and privately-owned herds.

scholarly journals Changes in genomic predictions when new information is added

2021 ◽  
Vol 99 (2) ◽  
Author(s):  
Jorge Hidalgo ◽  
Daniela Lourenco ◽  
Shogo Tsuruta ◽  
Yutaka Masuda ◽  
Stephen Miller ◽  
...  
Keyword(s):  
Single Step ◽  
Pedigree Information ◽  
Weaning Weight ◽  
Breeding Values ◽  
Core Group ◽  
Absolute Change ◽  
Angus Cattle ◽  
Average Maximum ◽  
Estimated Breeding Values ◽  
Genetic Evaluations

Abstract The stability of genomic evaluations depends on the amount of data and population parameters. When the dataset is large enough to estimate the value of nearly all independent chromosome segments (~10K in American Angus cattle), the accuracy and persistency of breeding values will be high. The objective of this study was to investigate changes in estimated breeding values (EBV) and genomic EBV (GEBV) across monthly evaluations for 1 yr in a large genotyped population of beef cattle. The American Angus data used included 8.2 million records for birth weight, 8.9 for weaning weight, and 4.4 for postweaning gain. A total of 10.1 million animals born until December 2017 had pedigree information, and 484,074 were genotyped. A truncated dataset included animals born until December 2016. To mimic a scenario with monthly evaluations, 2017 data were added 1 mo at a time to estimate EBV using best linear unbiased prediction (BLUP) and GEBV using single-step genomic BLUP with the algorithm for proven and young (APY) with core group fixed for 1 yr or updated monthly. Predictions from monthly evaluations in 2017 were contrasted with the predictions of the evaluation in December 2016 or the previous month for all genotyped animals born until December 2016 with or without their own phenotypes or progeny phenotypes. Changes in EBV and GEBV were similar across traits, and only results for weaning weight are presented. Correlations between evaluations from December 2016 and the 12 consecutive evaluations were ≥0.97 for EBV and ≥0.99 for GEBV. Average absolute changes for EBV were about two times smaller than for GEBV, except for animals with new progeny phenotypes (≤0.12 and ≤0.11 additive genetic SD [SDa] for EBV and GEBV). The maximum absolute changes for EBV (≤2.95 SDa) were greater than for GEBV (≤1.59 SDa). The average(maximum) absolute GEBV changes for young animals from December 2016 to January and December 2017 ranged from 0.05(0.25) to 0.10(0.53) SDa. Corresponding ranges for animals with new progeny phenotypes were from 0.05(0.88) to 0.11(1.59) SDa for GEBV changes. The average absolute change in EBV(GEBV) from December 2016 to December 2017 for sires with ≤50 progeny phenotypes was 0.26(0.14) and for sires with >50 progeny phenotypes was 0.25(0.16) SDa. Updating the core group in APY without adding data created an average absolute change of 0.07 SDa in GEBV. Genomic evaluations in large genotyped populations are as stable and persistent as the traditional genetic evaluations, with less extreme changes.

scholarly journals Estimation of the breeding value of sport horses in the Czech Republic

2004 ◽  
Vol 52 (1) ◽  
pp. 145-152
Author(s):  
Iva Jiskrová
Keyword(s):  
Czech Republic ◽  
Random Effects ◽  
Fixed Effects ◽  
Prediction Method ◽  
Sport Performance ◽  
Breeding Value ◽  
Progeny Testing ◽  
The Czech Republic ◽  
Breeding Values ◽  
Estimated Breeding Values

The performance of 10671 horses in 10911 sport competitions was used to estimate the breeding value of the population of the Czech warm-blooded horses using the Best Linear Unibased Prediction method. The sport performance was estimated on the basis of the number of bad points (penalties) in jumping competitions. We analysed 252781 sporting results in the period 1991 – 2002. The estimations encompassed the fixed effects of sex, age, level of the competition and random effects of the breeder, rider, competition and the permanent environment. We compared the original and innovated calculations of the estimate of the breeding value of sport horses in the Czech Republic. We then compiled a list of estimated breeding values for stallions having 30 or more offspring and we compared the estimated breeding values with the results of the official system of progeny testing for performance in the Czech Republic.

A comprehensive comparison between single- and two-step GBLUP methods in a simulated beef cattle population

2018 ◽  
Vol 98 (3) ◽  
pp. 565-575 ◽  
Author(s):  
Mario L. Piccoli ◽  
Luiz F. Brito ◽  
José Braccini ◽  
Fernanda V. Brito ◽  
Fernando F. Cardoso ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Production Systems ◽  
Simulated Data ◽  
Single Step ◽  
Breeding Values ◽  
True Breeding ◽  
Blending Method ◽  
Estimated Breeding Values ◽  
Genetic Evaluations ◽  
Genomic Predictions

The statistical methods used in the genetic evaluations are a key component of the process and can be best compared by using simulated data. The latter is especially true in grazing beef cattle production systems, where the number of proven bulls with highly reliable estimated breeding values is limited to allow for a trustworthy validation of genomic predictions. Therefore, we simulated data for 4980 beef cattle aiming to compare single-step genomic best linear unbiased prediction (ssGBLUP), which simultaneously incorporates pedigree, phenotypic, and genomic data into genomic evaluations, and two-step GBLUP (tsGBLUP) procedures and genomic estimated breeding values (GEBVs) blending methods. The greatest increases in GEBV accuracies compared with the parents’ average estimated breeding values (EBVPA) were 0.364 and 0.341 for ssGBLUP and tsGBLUP, respectively. Direct genomic value and GEBV accuracies when using ssGBLUP and tsGBLUP procedures were similar, except for the GEBV accuracies using Hayes’ blending method in tsGBLUP. There was no significant or slight bias in genomic predictions from ssGBLUP or tsGBLUP (using VanRaden’s blending method), indicating that these predictions are on the same scale compared with the true breeding values. Overall, genetic evaluations including genomic information resulted in gains in accuracy >100% compared with the EBVPA. In addition, there were no significant differences between the selected animals (10% males and 50% females) by using ssGBLUP or tsGBLUP.

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