scholarly journals Estimation of genetic parameters and comparison of random regression animal and sire models of production traits in the first three lactations of Iranian Holsteins

2014 ◽  
Vol 30 (2) ◽  
pp. 261-279 ◽  
Author(s):  
A. Mohammadi ◽  
S. Alijani
Keyword(s):  
Milk Fat ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Random Regression ◽  
Lactation Period ◽  
Production Traits ◽  
Environmental Variance ◽  
In The Beginning ◽  
Residual Variances

This study was conducted to compare of random regression (RR) animal and sire models for estimation of the genetic parameters for production traits of Iranian Holstein dairy cows. For this purpose, the test day records were used belonged to first three lactations of cows and for, milk, fat and protein yields traits where, collected from 2003 to 2010, by the national breeding center of Iran. The genetic parameters were estimated using restricted maximum likelihood algorithm. To compare the model, different criterion -2logL value, AIC, BIC and RV were used for considered traits. Residual variances were considered homogeneous over the lactation period. Obtained results showed that additive genetic variance was highest in the beginning and end lactation and permanent environmental variance was highest in beginning of lactation than other lactation period. Heritabilities estimate for milk, fat and protein yields by RR animal and sire models were found to be lowest during early lactation (0.05, 0.04 and 0.07; 0.05, 0.19 and 0.13; 0.14, 0.19 and 0.15, for milk, fat and protein yields and in first, second and third lactation respectively). However, estimated heritabilities during lactation did not vary among different order Legendre polynomials, and also between RR animal and sire models. The variation in genetic correlations estimate in the RR animal and sire models was larger in the first lactation than in the second and third lactations. Thus, based on the results obtained, it can be inferred that the RR animal model is better for modeling yield traits in Iranian Holsteins.

scholarly journals Genetic parameters for production traits in primiparous Holstein cows estimated by random regression models

2011 ◽  
Vol 40 (1) ◽  
pp. 85-94 ◽  
Author(s):  
Igor de Oliveira Biassus ◽  
Jaime Araújo Cobuci ◽  
Claudio Napolis Costa ◽  
Paulo Roberto Nogara Rorato ◽  
José Braccini Neto ◽  
...  
Keyword(s):  
Milk Fat ◽  
Legendre Polynomials ◽  
Regression Models ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Holstein Cows ◽  
Lactation Period ◽  
Production Traits ◽  
Residual Variances

The objective of this study was to estimate genetic parameters for milk, fat and protein yields of Holstein cows using 56,508; 35,091 and 8,326 test-day milk records from 7,015, 4,476 and 1,114 cows, calves of 359, 246 and 90 bulls, respectively. The additive genetic and permanent environmental effects were estimated using REML. Random regression models with Legendre polynomials from order 3 to 6 were used. Residual variances were considered homogeneous over the lactation period. The estimates of variance components showed similar trends, with an increase of the polynomial order for each trait. The heritability estimates ranged from 0.14 to 0.31; 0.03 to 0.21 and 0.09 to 0.33 for milk, fat and protein yield, respectively. Genetic correlations among milk, fat and protein yields ranged from 0.02 to 1.00; 0.34 to 1.00 and 0.42 to 1.00, respectively. Models with higher order Legendre polynomials are the best suited to adjust test-day data for the three production traits studied.

scholarly journals Random regression models to estimate genetic parameters for test-day milk yield and composition in Iranian buffaloes

2013 ◽  
Vol 56 (1) ◽  
pp. 276-284 ◽  
Author(s):  
M. Madad ◽  
N. Ghavi Hossein-Zadeh ◽  
A. A. Shadparvar ◽  
D. Kianzad
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Milk Protein ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Production Traits ◽  
Environmental Correlations ◽  
Protein Percentage ◽  
Heritability Estimates

Abstract. The objective of this study was to estimate genetic parameters for milk yield and milk percentages of fat and protein in Iranian buffaloes. A total of 9,278 test-day production records obtained from 1,501 first lactation buffaloes on 414 herds in Iran between 1993 and 2009 were used for the analysis. Genetic parameters for productive traits were estimated using random regression test-day models. Regression curves were modeled using Legendre polynomials (LPs). Heritability estimates were low to moderate for milk production traits and ranged from 0.09 to 0.33 for milk yield, 0.01 to 0.27 for milk protein percentage and 0.03 to 0.24 for milk fat percentage, respectively. Genetic correlations ranged from −0.24 to 1 for milk yield between different days in milk over the lactation. Genetic correlations of milk yield at different days in milk were often higher than permanent environmental correlations. Genetic correlations for milk protein percentage ranged from −0.89 to 1 between different days in milk. Also, genetic correlations for milk percentage of fat ranged from −0.60 to 1 between different days in milk. The highest estimates of genetic and permanent environmental correlations for milk traits were observed at adjacent test-days. Ignoring heritability estimates for milk yield and milk protein percentage in the first and final days of lactation, these estimates were higher in the 120 days of lactation. Test-day milk yield heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in Iranian milking buffaloes.

scholarly journals Estimation of genetic parameters for daily milk yields of primiparous Iranian Holstein cows

2013 ◽  
Vol 56 (1) ◽  
pp. 455-466
Author(s):  
K. Kheirabadi ◽  
S. Alijani ◽  
L. Zavadilová ◽  
S. A. Rafat ◽  
G. Moghaddam
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
National Level ◽  
Genetic Correlations ◽  
Protein Yield ◽  
Random Regression ◽  
Production Traits ◽  
Multiple Traits ◽  
Multiple Trait

Abstract. Applying a multiple trait random regression (MT-RR) in national level and for whole test day records of a country is a great advance in animal breeding context. Having reliable (co) variance components is a critical step in applying multiple traits genetic evaluation especially in developing countries. Genetic parameters of milk, fat and protein yields were estimated for Iranian Holstein dairy cows. Data included 276 692 test day (TD) production traits records collected of 30 705 primiparous cows belonging to 619 sires. An animal multi-trait random regression model was employed in the analyses using the restricted maximum likelihood (REML) method. The model included herd-test-date, age-season of calving (by applying a fixed regression for each subclass of this effect) and year of calving as fixed effects and random regression (RR) coefficients for additive genetic (AG) and permanent environmental (PE) effects. Obtained results showed that daily heritabilities ranged from 0.10 to 0.21 for milk, from 0.05 to 0.08 for fat and from 0.08 to 0.18 for protein yield. Estimated heritability for 305-d milk, fat and protein yields were 0.25, 0.20 and 0.25, respectively. Correlations between individual test day records within traits were high for adjacent tests (nearly 1) and decreased as the interval between tests increased. Correlations between yields of milk, fat and protein on a given test day are also high and greater during late lactation than during early or mid-lactation. Genetic correlations between 305-d yield traits ranged from 0.75 to 0.92. The largest genetic correlation, as well as permanent environmental correlation, was observed between milk and protein yield.

scholarly journals Estimation of variance components of milk, fat, and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods

2016 ◽  
Vol 59 (2) ◽  
pp. 243-248 ◽  
Author(s):  
Hafedh Ben Zaabza ◽  
Abderrahmen Ben Gara ◽  
Hedi Hammami ◽  
Mohamed Amine Ferchichi ◽  
Boulbaba Rekik
Keyword(s):  
Dairy Cattle ◽  
Bayesian Methods ◽  
Milk Fat ◽  
Variance Components ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Bayesian Procedure ◽  
Milk Traits ◽  
Residual Variances ◽  
Estimation Of Variance

Abstract. A multi-trait repeatability animal model under restricted maximum likelihood (REML) and Bayesian methods was used to estimate genetic parameters of milk, fat, and protein yields in Tunisian Holstein cows. The estimates of heritability for milk, fat, and protein yields from the REML procedure were 0.21 ± 0.05, 0.159 ± 0.04, and 0.158 ± 0.04, respectively. The corresponding results from the Bayesian procedure were 0.273 ± 0.02, 0.198 ± 0.01, and 0.187 ± 0.01. Heritability estimates tended to be larger via the Bayesian than those obtained by the REML method. Genetic and permanent environmental variances estimated by REML were smaller than those obtained by the Bayesian analysis. Inversely, REML estimates of the residual variances were larger than Bayesian estimates. Genetic and permanent correlation estimates were on the other hand comparable by both REML and Bayesian methods with permanent environmental being larger than genetic correlations. Results from this study confirm previous reports on genetic parameters for milk traits in Tunisian Holsteins and suggest that a multi-trait approach can be an alternative for implementing a routine genetic evaluation of the Tunisian dairy cattle population.

scholarly journals Genetic parameters for test day milk yield of first lactation Holstein cows estimated by random regression using Legendre polynomials

2008 ◽  
Vol 37 (4) ◽  
pp. 602-608 ◽  
Author(s):  
Claudio Napolis Costa ◽  
Claudio Manoel Rodrigues de Melo ◽  
Irineu Umberto Packer ◽  
Ary Ferreira de Freitas ◽  
Nilson Milagres Teixeira ◽  
...  
Keyword(s):  
Variance Components ◽  
Legendre Polynomials ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Holstein Cows ◽  
Residual Variance ◽  
Environmental Variance ◽  
Environmental Correlations ◽  
Lp Estimates

Data comprising 263,390 test-day (TD) records of 32,448 first parity cows calving in 467 herds between 1991 and 2001 from the Brazilian Holstein Association were used to estimate genetic and permanent environmental variance components in a random regression animal model using Legendre polynomials (LP) of order three to five by REML. Residual variance was assumed to be constant in all or in some classes of lactation periods for each LP. Estimates of genetic and permanent environmental variances did not show any trend due to the increase in the LP order. Residual variance decreased as the order of LP increased when it was assumed constant, and it was highest at the beginning of lactation and relatively constant in mid lactation when assumed to vary between classes. The range for the estimates of heritability (0.27 - 0.42) was similar for all models and was higher in mid lactation. There were only slight differences between the models in both genetic and permanent environmental correlations. Genetic correlations decreased for near unity between adjacent days to values as low as 0.24 between early and late lactation. A five parameter LP to model both genetic and permanent environmental effects and assuming a homogeneous residual variance would be a parsimonious option to fit TD yields of Holstein cows in Brazil.

scholarly journals Genetic parameters for milk production and persistency in the Iranian Holstein population by the multitrait random regression model

2014 ◽  
Vol 57 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Khabat Kheirabadi ◽  
Sadegh Alijani
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Genetic Correlations ◽  
Random Regression ◽  
Genetic Dissection ◽  
Production Traits ◽  
Data Set ◽  
Random Regression Model ◽  
Regression Test ◽  
Fat Yield

Abstract. For genetic dissection of milk, fat, and protein production traits in the Iranian primiparous Holstein dairy cattle, records of these traits were analysed using a multitrait random regression test-day model. Data set included 763 505 test-day records from 88 204 cows calving since 1993. The (co)variance components were estimated by Bayesian method. The obtained results indicated that as in case of genetic correlations within traits, genetic correlations between traits decrease as days in milk (DIM) got further apart. The strength of the correlations decreased with increasing DIM, especially between milk and fat. Heritability estimates for 305-d milk, fat, and protein yields were 0.31, 0.29, and 0.29, respectively. Heritabilities of test-day milk, fat, and protein yields for selected DIM were higher in the end than at the beginning or the middle of lactation. Heritabilities for persistency ranged from 0.02 to 0.24 and were generally highest for protein yield (0.05 to 0.24) and lowest for fat yield (0.02 to 0.17), with milk yield having intermediate values (0.06 to 0.22). Genetic correlations between persistency measures and 305-d production were higher for protein and milk yield than for fat yield. The genetic correlation of the same persistency measures between milk and fat yields averaged 0.76, and between milk and protein yields averaged 0.82.

Genetic parameters of milk cholesterol content in Holstein cattle

2018 ◽  
Vol 98 (4) ◽  
pp. 714-722 ◽  
Author(s):  
Duy N. Do ◽  
Allison Fleming ◽  
Flavio S. Schenkel ◽  
Filippo Miglior ◽  
Xin Zhao ◽  
...  
Keyword(s):  
Milk Fat ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Cholesterol Content ◽  
Production Traits ◽  
Fat Percentage ◽  
Bivariate Models ◽  
Estimate Heritability ◽  
Fat Yield ◽  
Using Data

This study aimed to estimate heritability for milk cholesterol (CHL) and genetic correlations between milk CHL and other production traits (test-day milk, fat, and protein yields, fat and protein percentages, and somatic cell score). Milk CHL content was determined by gas chromatography and expressed as mg of CHL in 100 g of fat (CHL_fat) or in 100 mg of milk (CHL_milk). Univariate models were used to estimate variances and heritability, whereas bivariate models were used to compute correlations using data from 1793 cows. The average concentrations (standard deviation) of CHL_fat and CHL_milk were 275.63 (75) mg and 11.16 (3.63) mg, respectively. Milk CHL content was significantly affected by days in milk and herd (P < 0.05), but not by parity, regardless of the scale of expression. Heritability estimates for CHL_fat and CHL_milk were 0.06 ± 0.04 and 0.17 ± 0.06, respectively. Phenotypic and genetic correlations between CHL_fat and CHL_milk were 0.82 and 0.44 ± 0.24, respectively. CHL_fat had nonsignificant genetic correlations with all production traits, whereas CHL_milk had significant (P < 0.05) genetic correlations with milk yield (−0.47), fat yield (0.51), protein percentage (0.56), and fat percentage (0.88). This is the first study to estimate genetic parameters for milk CHL content. Further studies are required to assess the possibility of genetically selecting cows with lower milk CHL content.

Corrigendum - Response to selection in Australian Merino sheep. II. Estimates of phenotypic and genetic parameters for some production traits in Merino ewes and an analysis of the possible effects of selection on them

1968 ◽  
Vol 19 (2) ◽  
pp. 303
Author(s):  
GH Brown ◽  
HN Turner
Keyword(s):  
Genetic Parameters ◽  
Genetic Variance ◽  
Statistical Significance ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Production Traits ◽  
Average Value ◽  
Selection History ◽  
Order Of Magnitude ◽  
Selection For

Estimates of heritabilities and of phenotypic and genetic correlations are given, based on extensive measurements on medium Peppin Merino ewes at 15–16 months of age. In general these substantiate results obtained by other workers and, in particular, confirm the high heritabilities of the traits measured. An effort has been made to try to detect possible changes in additive genetic variance for the trait under selection (clean wool weight). Estimates are obtained for data from animals at different stages of selection: (A) either unselected, or with little selection history, and (B and C) with varying amounts of selection. For stage A data the average estimated additive genetic variance was 0.31. There are problems involved in estimating from stage (B+C) data but an upper limit average value of 0.22 was obtained. Thus, although a decrease in additive genetic variance has occurred, its statistical significance is unknown and conclusions about the decrease must necessarily be tentative. In practically all cases the estimates of phenotypic and genetic correlations are of the same order of magnitude, and for the genetic correlations may be summarized as: See PDFAll other combinations of traits have negligible genetic correlations (in the range –0.20 to + 0.2).

Genetic correlation estimates between milk production traits, mastitis and different measures of somatic cells in Holstein cows

2019 ◽  
Vol 59 (6) ◽  
pp. 1031 ◽  
Author(s):  
Arash Chegini ◽  
Navid Ghavi Hossein-Zadeh ◽  
Seyed Hossein Hosseini-Moghadam ◽  
Abdol Ahad Shadparvar
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Linear Models ◽  
Genetic Correlations ◽  
Holstein Cows ◽  
Threshold Models ◽  
Production Traits ◽  
Environmental Variance ◽  
Udder Health ◽  
Cell Counts

The objective of this study was to estimate genetic parameters including repeatability, heritability as well as genetic and environmental relationships between 305-day milk yield, milk fat and protein yield (Fat and Pro), milk fat and protein percentages (Fat% and Pro%), mastitis (Mast), number of mastitis occurrence and different measurements of somatic cell counts using linear and threshold animal as well as linear and threshold sire models in Holstein cows of Iran. Records of 33851 first lactation Holstein cows from five large dairy herds with calving dates from March 2002 to September 2014 were analysed, using Gibbs sampling methodology. Heritabilities of production traits estimated by linear animal model ranged from 0.14 (Fat%) to 0.29 (Pro%). Generally, udder health traits had low heritability (ranged from 0.005 to 0.10). Estimates of heritability for Mast using linear models were higher than those obtained with threshold models. However, in general estimates of heritabilities using threshold models were higher than those from linear models. There were unfavourable genetic correlations between production traits and Mast, which implies that breeding programs with emphasis on 305-day milk yield will experience deterioration in udder health. Despite low heritability of udder health traits, genetic variability exists for these traits that allow selecting superior animals and increasing resistance to Mast and animal welfare. Considering relatively high ratio of permanent environmental variance for Mast, culling decisions can be made with higher accuracy in order to reduce Mast incidence phenotypically over time.

Genetic and phenotypic relationships between conformation and production traits in Ayrshire heifers

1994 ◽  
Vol 58 (3) ◽  
pp. 335-338 ◽  
Author(s):  
R. A. Mrode ◽  
G. J. T. Swanson
Keyword(s):  
Maximum Likelihood ◽  
Genetic Correlation ◽  
Milk Fat ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Production Traits ◽  
Linear Type ◽  
Maximum Likelihood Procedure ◽  
Type Traits ◽  
The Relationship

AbstractFirst lactation records for production traits (milk, fat and protein yields) and 17 linear type traits for 7169 Ayrshire heifers were analysed to estimate genetic parameters for type traits and to examine the relationship between type and production traits. A multivariate restricted maximum likelihood procedure fitting a sire model with sire relationships included was used for all analyses.Heritabilities for production traits were approximately 0·3 and genetic correlations among them were high (>0·84). The estimates of heritabilities for type traits were mainly low to moderate ranging from 0·04 to 0·42. Angularity (0·80), beef shape (0·49), foot angle (0·53) and stature (0·46) had higher heritabilities. Generally phenotypic correlations among type traits were lower than the genetic correlations. The highest negative genetic correlation was between rear legs side and rear legs rear (-0·95) and the highest positive correlation between chest width and beef shape (0·93).Genetic correlations between type and production were low to moderate and were similar for milk, fat and protein yields. The genetic correlations between the production traits and chest width, udder depth and beef shape were negative but were positive between production and angularity, rear udder width and teat placement side.

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