Estimation of genetic parameters of the productive and reproductive traits in Ethiopian Holstein using multi-trait models.
This study estimated the genetic parameters for productive and reproductive traits.
The data included production and reproduction records of animals that have calved between 1979 and 2013. The genetic parameters were estimated using multivariate mixed models (DMU) package, fitting univariate and multivariate mixed models with average information restricted maximum likelihood algorithm.
The estimates of heritability for milk production traits from the first three lactation records were 0.03±0.03 for lactation length (LL), 0.17±0.04 for lactation milk yield (LMY), and 0.15±0.04 for 305 days milk yield (305-d MY). For reproductive traits the heritability estimates were, 0.09±0.03 for days open (DO), 0.11±0.04 for calving interval (CI), and 0.47±0.06 for age at first calving (AFC). The repeatability estimates for production traits were 0.12±0.02, for LL, 0.39±0.02 for LMY, and 0.25±0.02 for 305-d MY. For reproductive traits the estimates of repeatability were 0.19±0.02 for DO, and to 0.23±0.02 for CI. The phenotypic correlations between production and reproduction traits ranged from 0.08±0.04 for LL and AFC to 0.42±0.02 for LL and DO. The genetic correlation among production traits were generally high (>0.7) and between reproductive traits the estimates ranged from 0.06±0.13 for AFC and DO to 0.99±0.01 between CI and DO. Genetic correlations of productive traits with reproductive traits were ranged from -0.02 to 0.99.
The high heritability estimates observed for AFC indicated that reasonable genetic improvement for this trait might be possible through selection. The h2 and r estimates for reproductive traits were slightly different from single versus multi-trait analyses of reproductive traits with production traits. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended.
Ayalew W
,Aliy M
,Negussie E
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Estimation of genetic parameters for production and reproductive traits in Indian Karan-Fries cattle using multi-trait Bayesian approach.
Estimates of variance components are needed for implementing genetic selection. This study was conducted to genetic parameters for production and reproductive traits on Indian Karan-Fries cattle using multi-trait repeatability animal model. Data collected from ICAR-National Dairy Research Institute, Karnal, India (from 1988 to 2019) were used. Single-trait and multi-trait repeatability animal models were used for parameter estimation. The posterior mean of Heritability estimates for 305-day milk yield (305-DMY), lactation milk yield (LMY), lactation length (LL) were 0.20 ± 0.03, 0.19 ± 0.03 and 0.06 ± 0.02, respectively. For age at first calving (AFC), calving interval (CI), and days open (DO), the posterior mean of heritability estimates were 0.24 ± 0.08, 0.06 ± 0.01, and 0.07 ± 0.02, respectively. The repeatability estimates for 305-DMY, LMY, LL, CI, and DO were 0.37 ± 0.02, 0.34 ± 0.02, 0.15 ± 0.02, 0.09 ± 0.02, and 0.12 ± 0.02, respectively. Genetic correlation between milk production traits (305-DMY, LMY, and LL) was positive and strong (> 0.80). However, the genetic correlation between milk production trait and AFC ranges from - 0.31 to 0.12. Unfavorable strong genetic correlations were observed between production and reproductive traits (CI and DO) with values ranged from 0.5 to 0.7. Phenotypic correlations among 305-DMY, LMY, and LL were generally positive and high. The moderate heritability estimates and potential genetic variation for 305-DMY, TMY, and AFC suggested that genetic gain can be obtained for these traits through genetic selection. Low heritability estimates found for LL, CI and DO, indicating that the possibility of changing these traits through genetic selection is small. High genetic correlation observed between productive and fertility traits were unfavorable. The existed strong genetic and phenotypic correlation estimates between CI and DO indicates that recording only one of them would be sufficient in the herd. As the multi-trait model showed slight improvements in the h as well as r estimates for both productive and reproductive traits over univariate analysis, future selection with a multi-trait animal model applying Bayesian approach would be recommended.
Worku D
,Gowane GR
,Kumar R
,Joshi P
,Gupta ID
,Verma A
... -
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Genetic and phenotypic parameters and annual trends for milk production and fertility traits of the Sahiwal cattle in semi arid Kenya.
Data comprising 7211 lactation records of 2894 cows were used to estimate genetic and phenotypic parameters for milk production (lactation milk yield, LMY and lactation length, LL) and fertility (calving interval, CI; number of services per conception, NSC and age at first calving, AFC) traits. Genetic, environmental and phenotypic trends were also estimated. Variance components were estimated using univariate, bivariate and trivariate animal models on based restricted maximum likelihood procedures. Univariate models were used for each trait, while bivariate models were used to estimate genetic and phenotypic correlations between milk production and fertility traits and between LMY, LL, CI and NSC within each lactation. Trivariate models were used in the analysis of LMY, LL, CI and NSC in the first three lactations. Heritability estimates from the univariate model were 0.16, 0.07, 0.03, 0.04 and 0.01 for LMY, LL, CI, AFC and NSC, respectively. The heritability estimates from trivariate analysis were higher for milk production traits than those from univariate analyses. Genetic correlations were high and undesirable between milk production and fertility traits, while phenotypic correlations were correspondingly low. Genetic trends were close to zero for all traits, while environmental and phenotypic trends fluctuated over the study period.
Ilatsia ED
,Muasya TK
,Muhuyi WB
,Kahi AK
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《TROPICAL ANIMAL HEALTH AND PRODUCTION》
Genetic Parameters for First Lactation and Lifetime Traits of Nili-Ravi Buffaloes.
The data on first lactation and lifetime performance records of 501 Nili-Ravi were collected for a period from 1983 to 2017 (35 years) maintained at ICAR-Central Institute for Research on Buffaloes, Sub-Campus, Nabha, Punjab. The data were analyzed to calculate heritability, genetic and phenotypic correlation for first lactation traits, viz., Age at First Calving (AFC), First Lactation Total Milk Yield (FLTMY), First Lactation Standard (305 days or less) Milk Yield (FLSMY), First Peak Milk Yield (FPY), First Lactation Length (FLL), First Dry Period (FDP), First Service Period (FSP) and First Calving Interval (FCI), Herd Life (HL), Productive Life (PL), Productive Days (PD), Unproductive Days (UD), Breeding Efficiency (BE), Total Lifetime Milk Yield (Total LTMY), Standard Lifetime Milk Yield (Standard LTMY), Milk Yield Per Day of Productive Life (MY/PL), Milk Yield Per Day of Productive Days (MY/PD), and Milk Yield Per Day of Herd Life (MY/HL). For estimation of variance component and heritability separately for each trait, the uni-trait animal model was equipped, whereas to estimate genetic and phenotypic correlations between traits, bi-trait animal models were fitted. The estimates of heritability for production and reproduction traits of Nili-Ravi were medium, i.e., 0.365 ± 0.087, 0.353 ± 0.071, 0.318 ± 0.082, 0.354 ± 0.076, and 0.362 ± 0.086 for FLSMY, FDP, FSP, FCI, and AFC, respectively. The estimates of heritability were low, i.e., 0.062 ± 0.088, 0.123 ± 0.090, 0.158 ± 0.090, 0.155 ± 0.091, and 0.129 ± 0.091 for HL, PL, PD, Total LTMY, and Standard LTMY and high, i.e., 0.669 ± 0.096 for BE. Genetic correlation for FLTMY was high with FLL (0.710 ± 0.103), and genetic correlation of FLTMY was high and positive with HL, Total LTMY, MY/PL, and MY/PD while low and positive with PL. Genetic correlation of AFC was low and negative with PL, PD, UD, BE, Total LTMY, Standard LTMY, MY/PL, and MY/PD and negative with MY/HL. Significant positive phenotypic association of FPY was seen with FLTMY, FLSMY, FLL, AFC, HL, Total LTMY, and Standard LTMY. Higher heritability of first lactation traits especially FPY suggests sufficient additive genetic variability, which can be exploited under selection and breeding policy in order to improve overall performance of Nili-Ravi buffaloes.
Tamboli P
,Bharadwaj A
,Chaurasiya A
,Bangar YC
,Jerome A
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《Frontiers in Veterinary Science》
Genetic relationships between reproductive and production traits in Jersey crossbred cattle.
The study aimed to estimate the genetic parameters of different reproductive traits namely age at first calving (AFC), calving interval (CI), days open (DO) and number of service per conception (NSPC) and their associations with productive traits including 305-day milk yield (305DMY), total lactation milk yield (TLMY) and lactation length (LL) of Jersey crossbred cattle maintained at Kalyani, Nadia, West Bengal, India. Genetic parameters of reproductive traits and their correlations with productive traits were estimated by Restricted Maximum Likelihood method and Bayesian approach. Using both analytical approaches, the estimates of heritability for AFC, CI, DO and NSPC ranged from 0.12 -0.15, 0.05-0.08, 0.08-0.09 and 0.04-0.06, respectively. Low proportion of variances associated with permanent environmental effect of animals (c effect) were detected for CI (0.08-0.10), DO (0.09-0.11) and NSPC (0.05-0.06) in both the methods. Repeatability measures for all the reproductive traits considered in this study were low to moderate in nature, which ranged from 0.09 to 0.17. Genetic correlations between different reproductive traits were positive and low (0.05) to high (0.98) in magnitude except AFC-NSPC. Low and negative genetic correlations of AFC with 305DMY and TLMY were favourable and indicated animals with high milk yield had early age of maturity. Positive genetic correlations between CI, DO and NSPC with all production traits implied the antagonism relationships among these traits, therefore in any breeding program for improvement of production traits via selection, the reproductive traits should be taken into account as well.
Roy I
,Rahman M
,Karunakaran M
,Gayari I
,Baneh H
,Mandal A
... -
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