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Research Article
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Prediction Breeding Value and Genetic Parameter in Iranian Holstein Bulls for Milk Production Traits |
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Mojtaba Hosseinpour Mashhadi,
Naser Emam Jomeh Kashan,
Mohammad Reza Nassiry
and
Rasol Vaez Torshizi
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ABSTRACT
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Data set included records of 43303 cows for first lactation. Records were collected from 2000 to 2006 in Animal Breeding Center of Iran Studied traits were yield of milk, fat, protein and percentage of fat and protein. Total number of animal was 197561 individual in pedigree. Genetic and phenotypic parameters were estimated with REML method under single trait Animal Model. Breeding values were predicted with BLUP procedure. The model for the analyses included the factors herd-year-season as fixed factor (1694 levels), animal as random effect and age at calving as co variable with minimum and maximum of 23 and 36 month. Respectively the estimated heritabilities were 0.35 (±0.02), 0.33 (±0.02), 0.31 (±0.017), 0.28 (±0.02), 0.27 (±0.016) for milk, fat, protein yield, percent of fat and protein. Mean of breeding values of sires were 180.2 (±28.2), 3.7 (±1.26), 2.3 (±1.06), -0.036 (±0.014) and -0.028 (±0.009) for milk, fat, protein yield, percent of fat and protein, respectively.
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INTRODUCTION
For improving genetic merit for milk production traits
in dairy cattle, Animal Breeding Center of Iran have started to recorded
the data from 1975. Now more than 1000 herds in the country are under
recording. The increase in results is because of concerted efforts by
Agriculture and Jihad ministry and Animal Breeding Center (Karaj) and
many private dairy cattle organization. They were screened Dairy cattle
herds and select best of male calve based on genetic criteria for using
in national progeny testing program. About 1620 sires have been tested
in this program from 1984 up to now. About 145 sires were proved based
on the highest breeding value for production traits.
Dairy cattle have a long generation interval and a low
reproductive rate. In addition, it is costly and time-consuming to carry
out dairy cattle selection on a large experimental scale (Togashi et
al., 2004). Methods to determine variance component have been greatly
improved over the last three decades. Maximum Likelihood based methods
have been introduced by Patterson and Thompson (1971) and making use of
mixed models equation by Henderson (1984). Animal models have some clearly
defined and useful genetic properties for prediction of genetic values
and estimation of genetic parameter in selected and inbred population.
This model incorporate all relatives with and without phenotypic observation.
Sire evaluation are almost exclusively based on field data, which are
highly affected by a large array of environment factors. Therefore, it
becomes very important to adjust for those environmental effects in order
to accurately estimate the genetic merits of sires and cows. Genetic evaluation
of dairy sires and cow has evolved greatly over the years. The Best Linear
Unbiased Prediction (BLUP) procedure under animal model has quickly become
the method of choice for genetic evaluation based on national field data
(Togashi et al., 2004).
Genetic parameter estimates from REML-AM analysis have
been reported by several authors. Swalve and Van Vleck (1987) and Albuquerque
et al. (1994) analyzed the milk yield in 1st, 2nd and 3rd lactation.Van
Vleck and Dong (1988), Dong et al. (1988) and Albuquerque et
al. (1995) performed a multivariate analysis of milk, fat and protein
yield in the first lactation. Visscher and Thompson (1992) reported results
from univariate and multivariate analyses for milk production traits in
1st, 2nd and 3rd lactation. Prediction of BLUP breeding values requires
known variance components.
BLUP solutions were also proven to vary with the data
quality (Winkelman and Schaeffer, 1988), the inclusion of all or part
of the data, the use of pedigree information (Van Der Werf and De Boer,
1990). A variety of factors may influence the estimation of co-variances
and consequently affect genetic evaluations. Continuous selection was
theoretically proven to reduce the genetic variance (Bulmer, 1971). Variance
component estimates were also shown to depend on the level of production
(Meyer, 1991; Misztal et al., 1992). The effects of heterogeneous
variances and selection on the BLUP breeding values were discussed by
Wiggans and Van Raden (1991).
The aim of the present study was to estimate genetic
parameters for milk, fat, protein yield, percent of fat and protein in
the first lactation of Holstein dairy cattle in Iran, based on REML method
under single traits animal model and prediction breeding value of proven
sires with BLUP procedure. MATERIALS AND METHODS
Data and pedigree information: Records of first lactation of Holstein
cows were used to estimate variance component. The data were recorded
in animal breeding center of Iran (Karaj) from 2000 to 2006. The pedigree
was traced back to cows born in 1993. Total number of animal in pedigree
were 197561. Traits analyzed were 305 day lactation milk (MY), fat (FY)
and protein yield (PY), percent of fat (FP) and percent of protein (PP).
All of traits were adjusted for 305 day and two times milking. Phenotypic
means, standard deviation, maximum and minimum of traits, levels of fixed
effect and the number of the individual data sets for each trait are given
in Table 1.
Age of cows at calving was considered as a co variable that minimum and
maximum were 23 to 36 month with average of 25 (±2.4) month. Number
of base animals was 70506 and animals with records were about 43303 individual.
Pedigree information of each trait is presented in Table
2.
Statistical analysis: The model equation for milk production traits
was:
Where, Y is the vector of observations ordered by traits
with in animals, b is the unknown vector of fixed effects, a is the unknown
vector of animal`s genetic effects and e is the vector of random residual
effects. X, Z, is known incidence matrices connecting the observations
to the respective fixed and random effects.
The structure of variance-covariance matrix is:
Table 1: |
Summary of the milk production traits |
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Table 2: |
Pedigree information for milk production
traits |
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The estimation method was REML (Patterson and Thompson,
1971) under single traits Animal Model. The software used was DFREML 3.1.000
(Meyer, 2000).
RESULTS AND DISCUSSION
For all traits residual variances were higher than the genetic variances.
The phenotypic coefficient of variation for traits was in range from 7
for percent of protein to 18.5 for fat yield (Table 3).
Estimated heritabilities and standard errors were 0.35 (±0.02),
0.33 (±0.02), 0.31 (±0.017), 0.28 (±0.02), 0.27 (±0.016)
for milk, fat, protein yield, percent of fat and protein, respectively.
Mean of breeding value were 180.2 (±28.2), 3.7 (±1.26),
2.3 (±1.06), -0.036 (±0.014) and -0.028 (±0.009)
for milk, fat, protein yield, percent of fat and protein, respectively
(Table 4).
Heritability of milk yield was higher than other traits.
These values for fat and protein yield compare with percent of fat and
protein were higher. Mean of breeding value for milk, fat and protein
yield were positive but for fat and protein percentage were negative.
The estimated heritabilities were in good agreement with
the results from the literature. Van Vleck and Dong (1988) using REML
methods with an animal model reported heritabilities of 0.36, 0.35 and
0.33 for milk, fat and protein yield in the first lactation. Similarity,
Albuquerque et al. (1994) reported heritability estimates of 0.34,
0.35 and 0.4 for milk, fat and protein yield in the first lactation. REML
sire model gave usually lower estimates than the animal model, as only
a part of relationships in included in the sire model (Dong et al.,
1988).Meyer (1984) reported heritabilities of 0.34, 0.35 and 0.28 for
milk yield, 0.32, 0.33, 0.23 for fat yield and 0.24, 0.29, 0.12 for protein
yield in 1st, 2nd and 3rd lactations, respectively. Also, Dedkova and
Wolf (2001) reported heritability of 0.30, 0.28 and 0.30 for milk yield,
0.24, 0.25 and 0.25 for fat yield and 0.25, 0.25 and 0.27 for protein
yield in 1st, 2nd and 3rd lactations, respectively. They used five subset
data of large dataset of Holstein. Ben Gara et al. (2006) used
BLUP procedure for prediction breeding value of sires they estimated heritabilities
lower than those commonly found in the literature probably because of
limited production levels and missing information on the current data.
Jamrozik et al. (2000) reported that reliabilities of predicting
breeding values of sires increased with the number of progenies per sires.
Heritabilities were estimated, using the complete data
set, for milk production traits ranged from 0.22 (±0.042) for milk
yield to 0.70 (±0.049) for milk fat concentration (Evans et
al., 2002; Atil et al., 2001).
Comparable heritability estimates were published for
other cattle. In Montbeliarde cattle, Beaumont (1989) reported heritability
estimates of 0.27, 0.24 and 0.27 for milk yield, 0.26, 0.20 and 0.24 for
fat yield and 0.18, 0.18 and 0.22 for protein yield in the 1st, 2nd and
3rd lactation, respectively from REML sire model. In Swedish Red and White,
Standberg and Danell (1989) received the following REML sire model estimates
of heritability: 0.29, 0.27 and 0.24 for milk yield and 0.24, 0.20 and
0.21 for fat yield in the first, second and third lactation, respectively.
For Dutch Red and White, Van Veldhuizen et al. (1991) estimated
heritabilities of 0.31, 0.37 and 0.34 for milk, fat and protein yield,
respectively in first lactation. Low values 0.23, 0.19 and 0.16 for first
lactation milk, fat and protein yield, respectively) were found by Liinamo
et al. (1999) for Finnish Ayrshire. Using Henderson`s method III,
Soliman et al. (1990) reported high value of heritabilities (0.40,
0.39 and 0.41) for the 1st lactation milk, fat and protein yield, respectively
for Pinzgauer cattle in Austria.
Kaya et al. (2003) estimated additive genetic,
residual and permanent environment variances, heritabilities and breeding
value for 305 day and test day milk yield by REML method using animal
models. The reported heritabilities were 0.25 and 0.11 for 305 day and
test day milk, respectively.
Table 3: |
Genetic and phenotypic parameter |
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Table 4: |
Heritabilities and breeding value |
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In the literature in agreement with the present findings,
slightly lower estimates were reported for heritabilities of fat and protein
yield compared with heritabilities of milk yield (Jakobsen et al.,
2000).
CONCLUSION Present
result showed that estimated heritabilities of milk compare to these values
for fat and protein were higher. heritabilities of fat and protein percentage
were lower than fat and protein yield that probably reason were for structure
of data and record of these traits.
Mean of breeding value of sires for milk, fat and protein
yield were positive. These results imply that for genetic improvement
of production traits on Iranian Holstein population, selection of sires
could be based on highest breeding value for using them in mating system
on different herd on the country.
ACKNOWLEDGMENTS
Authors are thankful to Animal Breeding Center of Iran
(Karaj) for allowing access to their database. Authors also wish to thank
Mr. M.B. Sayadnezhad for cooperating to using dataset.
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