Genetic trends and genetic correlations between 305-day milk yield, persistency and somatic cell score of Holstein cows in Brazil using random regression model

2019 ◽  
Vol 59 (2) ◽  
pp. 207 ◽  
Author(s):  
A. Haiduck Padilha ◽  
E. P. M. Alfonzo ◽  
D. S. Daltro ◽  
H. A. L. Torres ◽  
J. Braccini Neto ◽  
...  
Keyword(s):  
Regression Model ◽  
Somatic Cell ◽  
Genetic Correlation ◽  
Milk Yield ◽  
Genetic Correlations ◽  
Somatic Cell Score ◽  
Random Regression ◽  
Random Regression Model ◽  
The Difference ◽  
Estimated Breeding Values

The objective was to estimate genetic correlations for persistency, milk yield and somatic cell score (SCS) in Holstein cattle in Brazil. A dataset with 190389 records of test-day milk and of test-day SCS from 21824 cows was used. Two-trait random regression model with a fourth order Legendre polynomial was used. Persistency (PS) was defined as the difference between estimated breeding values (EBV) along different days in milk using two formulae: and PS2=(EBV290–EBV90). Larger values for PS2 or lower ones for PS1 indicate higher persistency. Heritability was 0.24 for 305-day milk yield, 0.14 for SCS up to 305 days, 0.15 for PS1 and 0.14 for PS2. Genetic correlation between 305-day milk yield and SCS up to 305 days was –0.47. Genetic correlation of 305-day milk yield with PS1 and PS2 was –0.32 and 0.30, respectively. Genetic correlation of SCS up to 305 days was 0.25 with PS1 and –0.20 with PS2. The additive genetic correlations between milk yield, SCS and persistency showed that selection for higher persistency or for low somatic cell score will increase 305-day milk yield.

scholarly journals Genetic parameters for somatic cell score in the first three lactations of Czech Holstein and Fleckvieh breeds using a random regression model

2011 ◽  
Vol 56 (No. 6) ◽  
pp. 251-260 ◽  
Author(s):  
L. Zavadilová ◽  
J. Wolf ◽  
M. Štípková ◽  
E. Němcová ◽  
J. Jamrozik
Keyword(s):  
Regression Model ◽  
Somatic Cell ◽  
Genetic Correlations ◽  
Middle Part ◽  
Somatic Cell Score ◽  
Random Regression ◽  
Model Parameters ◽  
Environmental Correlations ◽  
Random Regression Model ◽  
Residual Variances

A multiple-lactation random regression model was applied to test-day somatic cell score (SCS) records from the first three lactations of Czech Holstein and Fleckvieh cows. For Holstein, the data included 26 314 cows, with 244 953, 76 188 and 26 153 test-day records in the first, second and third lactation, respectively. For Fleckvieh, the data included 24 061 cows, with 223 421, 93 358 and 31 305 test-day records in the first, second and third lactation, respectively. The linear model for SCS included the following factors (for the given parity): fixed herd-test date effect, fixed regressions on days in milk within the age-season class, random regressions for the animal genetic and random regressions for the permanent environmental effect of the cow. Third-degree Legendre polynomials were used for all regressions. Gibbs sampling was used to generate samples from the marginal posterior distributions of the model parameters. The resulting daily heritability ranged from 0.08 to 0.11 in the middle part of lactation and it increased only slightly with parity. Extremely high values (0.25, 0.21) observed especially at the beginning and end of the third lactation for Holstein might be caused by the "end-of-range" problem. The average daily heritabilities computed for the part of lactation between 45 and 255 days in milk (DIM) were in the range from 0.10 to 0.14. Daily permanent environmental variances were higher than the genetic variances and daily residual variances decreased with DIM. The residual variances in early lactation increased with lactation number. For both breeds, the highest genetic correlations computed for the part of lactation between DIM 45 and DIM 255 were obtained between the second and third lactation (0.95). The lowest daily genetic correlations of SCS in the same DIM between different lactations occurred at the beginning of lactation, especially between the first and third lactation. The permanent environmental correlations for selected DIM were lower than the respective genetic correlations.

scholarly journals The use of dijkstra mechanistic model for genetic analysis of the lactation curve characteristics and their relationships with age at first calving and somatic cell score of Iranian dairy cows

2020 ◽  
Vol 42 ◽  
pp. e50181
Author(s):  
Mahdi Elahi Torshizi ◽  
Homayoun Farhangfar
Keyword(s):  
Somatic Cell ◽  
Genetic Correlation ◽  
Milk Yield ◽  
Mechanistic Model ◽  
Genetic Correlations ◽  
Somatic Cell Score ◽  
Specific Rate ◽  
Lactation Period ◽  
Age At First Calving ◽  
Lactation Curve

The objective of this study was to estimate lactation curve parameters with Dijkstra mechanistic model and to evaluate genetic and phenotypic relationships between the parameters and the average somatic cell count in primiparous cows. The finding indicated that heritability estimates for partial milk yield (PMY1, PMY2 and PMY3), total 305-day milk yield (TMY305), decay parameter (λ2), age at first calving (AFC) and peak yield (PY) were moderate while the heritability of persistency (PS%), average somatic cell score (AVGSCS), time to peak yield (TP), initial milk production (λ0), specific rate of cell proliferation at parturition (λ1), and specific rate of cell death (λ3) were quite low. Genetic correlations between both AFC and PS% traits with average somatic cell scores was negative (-0.047 and -0.060) but low positive genetic correlation were between partial milk yields (PMY1 and PMY3) while negative genetic correlation (-0.06) was obtained between TMY305 and AVGSCS. Differences between TMY305 of cows with less than 100000 cells mL-1 and cows with >1,500,000 cells mL-1 was approximately 708 Kg and is equivalent to 8% loss of milk yield/cow during lactation period and also loss of persistency (11.1 %( was shown for the extreme classes of SCC in this study.

Genetic perspective of milk yield persistency in the first three lactations of Iranian buffaloes (Bubalus bubalis)

2017 ◽  
Vol 84 (4) ◽  
pp. 434-439 ◽  
Author(s):  
Navid Ghavi Hossein-Zadeh ◽  
Mohammad Ali Nazari ◽  
Abdol Ahad Shadparvar
Keyword(s):  
Milk Yield ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Bubalus Bubalis ◽  
Random Regression ◽  
Genetic Trend ◽  
Breeding Center ◽  
Regression Test ◽  
The Difference ◽  
Estimated Breeding Values

The objectives of this study were to estimate the genetic parameters and genetic trends for different measures of persistency (PM) for milk yield in Iranian buffaloes using a random regression test day model. Test day records of the first three lactations of buffaloes within 715 herds comprising 43 014, 38 941 and 33 937 records, respectively, were obtained from the Animal Breeding Center of Iran during 1992 to 2012. Legendre polynomial functions were chosen to fit the lactation curves in the framework of a random regression test day model for estimating (co)variance components. Three measures of persistency were modified based on the lactation curve conditions of buffaloes: (1) The average of estimated breeding values (EBVs) for test day milk yields 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), (3) The difference between EBVs for day 257 and day 80 (PM3). The highest heritability estimates were observed for PM2over the first three lactations (0·29, 0·80 and 0·42, respectively). Estimates of genetic correlations between persistency measures and milk yield varied from −0·48 to 0·29 (first lactation), from −0·12 to 0·48 (second lactation), and from −0·62 to 0·63 (third lactation). Estimate of genetic trend for first lactation PM2was negative (−0·0088 ± 0·0043;P< 0·05). It is essential to include milk yield persistency in the breeding goal of Iranian buffaloes along with other important traits such as milk yield or reproductive traits.

scholarly journals Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model

2021 ◽  
Vol 73 (1) ◽  
pp. 18-24
Author(s):  
E.P.B. Santos ◽  
G.L. Feltes ◽  
R. Negri ◽  
J.A. Cobuci ◽  
M.V.G.B. Silva
Keyword(s):  
Regression Model ◽  
Milk Yield ◽  
Legendre Polynomials ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Third Order ◽  
Good Tool ◽  
Components Of Variance ◽  
Random Regression Model

ABSTRACT The objective of this study was to estimate the components of variance and genetic parameters of test-day milk yield in first lactation Girolando cows, using a random regression model. A total of 126,892 test-day milk yield (TDMY) records of 15,351 first-parity Holstein, Gyr, and Girolando breed cows were used, obtained from the Associação Brasileira dos Criadores de Girolando. To estimate the components of (co) variance, the additive genetic functions and permanent environmental covariance were estimated by random regression in three functions: Wilmink, Legendre Polynomials (third order) and Linear spline Polynomials (three knots). The Legendre polynomial function showed better fit quality. The genetic and permanent environment variances for TDMY ranged from 2.67 to 5.14 and from 9.31 to 12.04, respectively. Heritability estimates gradually increased from the beginning (0.13) to mid-lactation (0.19). The genetic correlations between the days of the control ranged from 0.37 to 1.00. The correlations of permanent environment followed the same trend as genetic correlations. The use of Legendre polynomials via random regression model can be considered as a good tool for estimating genetic parameters for test-day milk yield records.

Genetic evaluation of Holstein Friesian sires for daughter condition-score changes using a random regression model

1999 ◽  
Vol 68 (3) ◽  
pp. 467-475 ◽  
Author(s):  
H. E. Jonest ◽  
I. M. S. White ◽  
S. Brotherstone
Keyword(s):  
Genetic Analysis ◽  
Regression Model ◽  
Genetic Correlations ◽  
Random Regression ◽  
Stage Of Lactation ◽  
Random Regression Model ◽  
Holstein Friesian ◽  
Condition Score ◽  
Estimated Breeding Values ◽  
Stage 1

AbstractIn dairy cattle type classification schemes, heifers are condition scored (CS) only once during their first lactation. Although genetic analysis of condition-score changes is not possible using an animal model, the data can be analysed as repeated observations on the sire.CS records for 100 078 Holstein Friesian heifers, the progeny of 797 sires, were available. Sires differed in the shape of the regression of mean daughter CS on stage of lactation at both the phenotypic and genetic level. Genetic analysis was carried out using a random regression model (RRM) which can account for differences between sires in the shape of the CS curves. CS curves for individual sires were modelled using a cubic polynomial.Heritability estimates for CS at each stage of lactation generally increased through the lactation from 0·20 in stage 2 (days in milk 31 to 60) to 0·28 in later lactation stages. Genetic correlations between CS at different stages were generally high (0·80), with the exception of correlations with stage 1 (days in milk 1 to 30) which decreased to 0·63 with stages 6 and 7, suggesting that CS at stage 1 is under different biological control from CS at other stages of the lactation. Using RRM, sire estimated breeding values (EBVs) for CS at each stage of the lactation were estimated. Sire rankings on EBV at each stage were seen to change through early, mid and later lactation stages.

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