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.

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 Genetic relationship between milk dry matter and other milk traits in extended lactations of Polish Holstein cows

2010 ◽  
Vol 55 (No. 3) ◽  
pp. 91-104 ◽  
Author(s):  
K. Yazgan ◽  
J. Makulska ◽  
A. Węglarz ◽  
E. Ptak ◽  
M. Gierdziewicz
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Fixed Effects ◽  
Dry Matter ◽  
Genetic Correlations ◽  
Random Regression ◽  
Holstein Cows ◽  
Milk Traits ◽  
Data Set ◽  
The Third

The objective of this research was to examine heritabilities and genetic, phenotypic and permanent environmental relationships between milk dry matter (DM) and milk traits such as milk, fat, protein and lactose yields, milk urea nitrogen (MUN) and somatic cell score (SCS) in extended (to 395 days) lactations of Holstein cows from a big farm in Poland. The data set consisted of 78 059 test day records from the first, second and third lactations of 3 792 cows, daughters of 210 sires and 1 677 dams. Single- or two-trait random regression models were used with fixed effects of calving year, calving month, dry period and calving interval and random additive genetic and permanent environmental effects. The last two fixed effects were not included in the analysis of first lactation data. The highest values of heritabilities for all traits, except DM, were observed in the second lactation. First lactation heritabilities for all traits – except milk yield and SCS – were smaller than those in the third lactation. Lactose yield was highly heritable, with average h<SUP>2</SUP> equal to 0.25, 0.29 and 0.28 in lactations 1, 2 and 3, respectively. Heritability for DM was slightly lower than that for lactose (0.22, 0.26 and 0.28 for lactations 1, 2 and 3, respectively). In all lactations heritabilities for SCS were below 0.1. Genetic correlations between DM and milk yield (0.64–0.74) were lower than those between MUN and milk yield (0.67–0.79) as well as between lactose and milk yield (0.72–0.82). In general, DM was much more closely correlated with fat or protein yield (0.55–0.79) than with MUN or lactose (0.38–0.76). Only in the third lactation the correlation between DM and protein (0.72) was lower than between lactose and protein (0.76). For all lactations there were very high genetic correlations between DM and lactose (0.96–0.98) and high correlations between DM and MUN (0.63–0.83) and between lactose and MUN (0.70–0.85). The results suggest that further research is needed, focused on DM and its relationship with other traits in larger populations. &nbsp;

scholarly journals Estimation the Genetic Parameters for Milk Yield in Romanian Spotted, Simmental Type Cattle Breed

2021 ◽  
Vol 24 (2) ◽  
pp. 105-121
Author(s):  
Rodica Stefania Pelmuș ◽  
Mircea Cătălin Rotar ◽  
Cristina Lazăr ◽  
Răzvan Alexandru Uță
Keyword(s):  
Animal Model ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Cattle Breed ◽  
Random Regression ◽  
Breeding Value ◽  
Regression Test ◽  
Fat Yield ◽  
Heritability Estimates

Abstract The aim of this study was to estimate the genetic parameters for test-day traits milk yield and the breeding value in Romanian Spotted, Simmental type cattle. Random regression test-day animal model was used to estimate the genetic parameters. The number of records were 2062 test-day from 302 cows. The data were obtained from Romanian Breeding Association Romanian Spotted, Simmental type. The heritability estimates values for milk yield ranged between 0.377 and 0.417. The heritability for fat test-day yield in our study was low the values ranged between 0.117 and 0.236 and for protein test-day yield was medium, the values ranged between 0.308 and 0.372. The breeding value for the best ten cows for milk yield ranged from 1946.57 to 3250.38 kg, for fat yield were between 64.92 and 98.86 kg and for protein ranged from 67.26 to 102.21 kg. The correlations between test-day milk yields ranging from 0.28 to 1. Genetic correlations between test day fat and protein yields were high.

scholarly journals Genetic Analysis of Persistency for Milk Fat Yield in Iranian Buffaloes (Bubalus bubalis)

2021 ◽  
Vol 12 ◽  
Author(s):  
Mohammad Ali Nazari ◽  
Navid Ghavi Hossein-Zadeh ◽  
Abdol Ahad Shadparvar ◽  
Davood Kianzad
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Genetic Correlations ◽  
Bubalus Bubalis ◽  
Random Regression ◽  
Animal Products ◽  
Improvement Programs ◽  
Fat Yield ◽  
The Difference ◽  
Genetic Trends

This study aimed to estimate heritabilities and genetic trends for different persistency measures for milk fat yield and their genetic correlations with 270-day milk yield in Iranian buffaloes. The records of test-day milk fat yield belonging to the first three lactations of buffaloes within 523 herds consisting of 43,818 records were got from the Animal Breeding Center and Promotion of Animal Products of Iran from 1996 to 2012. To fit the lactation curves based on a random regression test-day model, different orders of Legendre polynomial (LP) functions were selected. Three persistency measures were altered according to the specific condition of the lactation curve in buffaloes: (1) The average of estimated breeding values (EBVs) for test day fat yield from day 226 to day 270 as a deviation from the average of EBVs from day 44 to day 62 (PM1), (2) A summation of contribution for each day from day 53 to day 247 as a deviation from day 248 (PM2), and (3) The difference between EBVs for day 257 and day 80 (PM3). The estimates of heritability for PM1, PM2, and PM3 ranged from 0.20 to 0.48, from 0.36 to 0.47, and from 0.19 to 0.35 over the first three lactations, respectively. The estimate of genetic trends for different persistency measures of milk fat yield was not significant over the lactations (P &gt; 0.05). Genetic correlation estimates between various measures of persistency were generally high over the first three lactations. Also, genetic correlations estimates between persistency measures and 270-day milk yield were mostly low and varied from 0.00 to 0.24 (between PM1 and 270-day milk yield), from −0.19 to 0.13 (between PM2 and 270-day milk yield), and from −0.02 to 0.00 (between PM1 and 270-day milk yield) over the first three lactations, respectively. Persistency measures that showed low genetic correlations with milk fat yield were considered the most suitable measures in selection schemes. Besides, medium to high heritability estimates for different persistency measures for milk fat yield indicated that relevant genetic variations detected for these characters could be regarded in outlining later genetic improvement programs of Iranian buffaloes.

scholarly journals Milk yield genetic parameters estimated using random regression model in Teleorman Black Head Sheep

2021 ◽  
Vol 24 (1) ◽  
pp. 44-52
Author(s):  
Florin Popa ◽  
Horia Grosu ◽  
Mircea-Cătălin Rotar ◽  
Rodica Ștefania Pelmuș ◽  
Cristina Lazăr ◽  
...  
Keyword(s):  
Milk Yield ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Breeding Value ◽  
First Year ◽  
Sheep Population ◽  
Random Regression Model ◽  
Regression Test ◽  
Black Head

Abstract Genetic parameters are important in breeding program of sheep. For the genetic evaluation of sheep was used the random regression test-day animal model. This model was better economic that another models because reduces generation interval and reduces the costs with test-days records. Data consisted of 1050 test-day of 403 ewes in first year (2017), 752 test-day of 374 ewes in second year (2018) and 1164 test-day of 319 ewes in third year (2019). The main goal to achieve the objectives of this research were the estimation of the genetic parameters important in obtaining the breeding value by calculation heritability for test-day milk yields and the correlations between test-days milk yields, for Teleorman Black Head Sheep population from Teleorman county in three different years. The heritability for test-day milk yield ranged from 0.150 to 0.237 in 2017, from 0.212 to 0.600 in 2018 and in 2019 from 0.186 to 0.403. Genetic correlations between sheep test-days milk yield in 2017 were positive and high.

scholarly journals Linking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows

2019 ◽  
Vol 62 (1) ◽  
pp. 153-160 ◽  
Author(s):  
Marwa Grayaa ◽  
Sylvie Vanderick ◽  
Boulbaba Rekik ◽  
Abderrahman Ben Gara ◽  
Christian Hanzen ◽  
...  
Keyword(s):  
Milk Yield ◽  
Genetic Correlations ◽  
Interaction Effects ◽  
Genetic Effects ◽  
Random Regression ◽  
Production Traits ◽  
Environment Effects ◽  
Random Regression Model ◽  
Calving Season ◽  
Additive Genetic Effects

Abstract. Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using information from 25 981 primiparous Tunisian Holsteins. For each trait, shape curves (i.e. peak lactation, persistency), level of production adjusted to 305 days in milk (DIMs) for total milk yield (TMY), and average fat (TF %) and protein (TP %) percentages were defined. Variance components were estimated with a linear random regression model under three bivariate animal models. Production traits were modelled by fixed herd × test-day (TD) interaction effects, fixed classes of 25 DIMs × age of calving × season of calving interaction effects, fixed classes of pregnancy, random environment effects and random additive genetic effects. Survival was modelled by fixed herd × year of calving interaction effects and age of calving × season of calving interaction effects, random permanent environment effects, and random additive genetic effects. Heritability (h2) estimates were 0.03 (±0.01) for survival and 0.23 (±0.01), 0.31 (±0.01) and 0.31 (±0.01) for TMY, TF % and TP %, respectively. Genetic correlations between survival and TMY, TF % and TP % were 0.26 (±0.08), −0.24 (±0.06) and −0.13 (±0.06), respectively. Genetic correlations between survival and persistency for fat and protein percentages were −0.35 (±0.09) and −0.19 (±0.09), respectively. Cows that had higher persistencies for fat and protein percentages were more likely not to survive.

scholarly journals Genetic parameters for test-day model with random regressions for production traits of Czech Holstein cattle

2011 ◽  
Vol 50 (No. 4) ◽  
pp. 142-154 ◽  
Author(s):  
L. Zavadilová ◽  
J. Jamrozik ◽  
Schaeffer LR
Keyword(s):  
Milk Fat ◽  
Sampling Method ◽  
Random Regression ◽  
Model Parameters ◽  
Residual Variance ◽  
Posterior Distributions ◽  
Production Traits ◽  
Multiple Trait ◽  
Holstein Breed ◽  
Random Regression Model

Multiple-lactation random regression model was applied to test-day records of milk, fat and protein yields in the first three lactations of the Czech Holstein breed. Data included 9&nbsp;583 cows, 89&nbsp;584, 44&nbsp;207 and 11&nbsp;266 test-day records in the first, second and third lactation, respectively. Milk, fat and protein in the first three lactations were analysed separately and in a multiple-trait analysis. Linear model included herd-test date, fixed regressions within age-season class and two random effects: animal genetic and permanent environment modelled by regressions. Gibbs sampling method was used to generate samples from marginal posterior distributions of the model parameters. The single- and multiple-trait models provided similar results. Genetic and permanent environmental variances and heritability for particular days in milk were high at the beginning and at the end of lactation. The residual variance decreased throughout the lactation. The resulting heritability ranged from 0.13 to 0.52 and increased with parity. &nbsp;

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.

Effect of milk fat to protein ratio on genetic variance for milk yield in Thai tropical Holstein cattle

2016 ◽  
Vol 96 (3) ◽  
pp. 410-415 ◽  
Author(s):  
S. Puangdee ◽  
M. Duangjinda ◽  
W. Boonkum ◽  
S. Buaban ◽  
S. Katawatin
Keyword(s):  
Milk Fat ◽  
Variance Components ◽  
Legendre Polynomials ◽  
Bayesian Method ◽  
Genetic Variance ◽  
Genetic Correlations ◽  
Random Regression ◽  
Third Order ◽  
Protein Ratio ◽  
Regression Test

The objective of this research was to investigate the optimum fat to protein ratio (FPR) in Thai tropical Holstein dairy cattle. First parity data consisting of 20 492 milk yields (MY) records for 24 891 cows for the period 2001 and 2011, were used in the analysis. The analysis used a random regression test-day animal model of third-order Legendre polynomials through the creation of a covariance function based on different FPRs. Variance components were estimated using the Bayesian method via the Gibbs sampling. The estimated heritability of MY in relation to FPR ranged from 0.19 to 0.27 with the pattern being similar to the genetic variances. Genetic correlations of MY at different FPRs were high at consecutive FPRs and then declined to negative in response to greater differences in FPR. Based on the results, it is concluded that the optimum FPR is in the range of 0.9 to 1.9, corresponding to the genetically controlled energy balance for MY in tropical Holsteins.

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.

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