scholarly journals Estimation of genetic parameters and trends for energy-corrected 305-d milk yield in Iranian Holsteins

2012 ◽  
Vol 55 (5) ◽  
pp. 420-426
Author(s):  
N. G. Hossein-Zadeh
Keyword(s):  
Animal Models ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Physiological Mechanism ◽  
Animal Breeding ◽  
Dairy Herds ◽  
Breeding Values ◽  
Estimation Of Genetic Parameters ◽  
Genetic Trends

Abstract. Calving records from the Animal Breeding Centre of Iran collected from January 1995 to December 2007 and comprising 217973 calving events of Holsteins from 704 dairy herds were analysed using univariate and bivariate linear animal models to estimate heritabilities and genetic correlations for energy-corrected 305-d milk yield (ECM) in the first three lactations of Holstein cows. Genetic trends were obtained by regressing yearly mean estimates of breeding values on calving year. Average ECM increased from parity 1 through parity 3. Estimates of heritabilities were from 0.14 to 0.21 for ECM and decreased over the parities. The greatest genetic correlations were between ECM2 and ECM3 (0.96), and the greatest phenotypic correlations were between ECM1 and ECM2 (0.57) and ECM2 and ECM3 (0.57). The high and positive genetic correlations between ECM traits at different lactations are evidence for common genetic and physiological mechanism controlling these traits. There were positive and increasing phenotypic and genetic trends for ECM over the years (P<0.001). Higher heritability of the ECM in the first parity along with the high genetic correlations between first-lactation ECM with these traits in other lactations shows that higher potential exists for selecting animals for ECM based on their first parity records.

scholarly journals Genetic Parameters of Bovine Milk Fatty Acid Profile, Yield, Composition, Total and Differential Somatic Cell Count

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2406
Author(s):  
Tania Bobbo ◽  
Mauro Penasa ◽  
Martino Cassandro
Keyword(s):  
Animal Models ◽  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Milk Fat ◽  
Fixed Effects ◽  
Somatic Cell Count ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Bovine Milk

The growing interest of consumers for milk and dairy products of high nutritional value has pushed researchers to evaluate the feasibility of including fatty acids (FA) in selection programs to modify milk fat profile and improve its nutritional quality. Therefore, the aim of this study was to estimate genetic parameters of FA profile predicted by mid-infrared spectroscopy, milk yield, composition, and total and differential somatic cell count. Edited data included 35,331 test-day records of 25,407 Italian Holstein cows from 652 herds. Variance components and heritability were estimated using single-trait repeatability animal models, whereas bivariate repeatability animal models were used to estimate genetic and phenotypic correlations between traits, including the fixed effects of stage of lactation, parity, and herd-test-date, and the random effects of additive genetic animal, cow permanent environment and the residual. Heritabilities and genetic correlations obtained in the present study reflected both the origins of FA (extracted from the blood or synthesized de novo by the mammary gland) and their grouping according to saturation or chain length. In addition, correlations among FA groups were in line with correlation among individual FA. Moderate negative genetic correlations between FA and milk yield and moderate to strong positive correlations with fat, protein, and casein percentages suggest that actual selection programs are currently affecting all FA groups, not only the desired ones (e.g., polyunsaturated FA). The absence of association with differential somatic cell count and the weak association with somatic cell score indicate that selection on FA profile would not affect selection on resistance to mastitis and vice versa. In conclusion, our findings suggest that genetic selection on FA content is feasible, as FA are variable and moderately heritable. Nevertheless, in the light of correlations with other milk traits estimated in this study, a clear breeding goal should first be established.

scholarly journals Schätzung genetischer Parameter an einem Datenmaterial der Sächsischen Rinderpopulation

2001 ◽  
Vol 44 (6) ◽  
pp. 589-598
Author(s):  
A. Michaiolowskaja ◽  
N. Mielenz ◽  
L. Schüler ◽  
U. Bergfeld ◽  
U. Müller
Keyword(s):  
Dairy Cattle ◽  
Protein Content ◽  
Population Genetic ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Fat Content ◽  
Cattle Population ◽  
Population Genetic Parameters ◽  
Estimation Of Genetic Parameters ◽  
Genetic Trends

Abstract. Title of the paper: Estimation of genetic parameters in the dairy cattle population of Saxonia Population-genetic parameters of the dairy cattle population of Saxonia have been examined. The estimated heritabilities for milk quantity range between 0.35 and 0.42, for fat content between 0.48 and 0.55 and for protein content between 0.52 and 0.57. Higher heritabilities were found for 1st than for subsequent lactations. The genetic correlations between milk quantity and the fat and protein contents were significantly negative for all lactations, likewise between protein content and the protein quantity. The correlation between fat content and fat quantity has been slightly positive (rg=0.08). The analysis of genetic trends revealed a substantial increase in quantity traits, whereas a negative trend has been observed for the milk content merits.

Estimation of genetic parameters for lambing ease, birthweight and gestation length in Australian sheep

2016 ◽  
Vol 56 (5) ◽  
pp. 934 ◽  
Author(s):  
L. Li ◽  
D. J. Brown
Keyword(s):  
Animal Models ◽  
Environmental Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Gestation Length ◽  
Phenotypic Variance ◽  
Full Dataset ◽  
Australian Sheep ◽  
Using Data ◽  
Estimation Of Genetic Parameters

This study presents estimates of genetic parameters for lambing ease (LE), birthweight (BW) and gestation length (GL) in Australian terminal sire sheep breeds using data from the Sheep Genetics LAMBPLAN database. LE was scored on lambs on a 1–5 scale, with 1 being no assistance and 5 being other such as special veterinary assistance. The full dataset consisted of 43 448 records on LE and its two subsets (the single and twin subsets) based on the birth type of the litter were analysed. Four models with different combinations of random effects consisting of direct genetic, maternal genetic and maternal permanent environmental effects were compared. All traits were analysed using linear animal models and linear sire models with LE further analysed by threshold sire models for all datasets to evaluate the influence of datasets and models on the estimation of genetic parameters. The results showed that multiple-born lambs had shorter GL, less BW and less lambing difficulty than single-born lambs. Lambing difficulty decreased with the increase of dam age from 1.5 to 4.5 years, and then increased afterwards. Genetic parameters using linear animal models were similar to those using linear sire models for all traits. Phenotypic variance and direct heritability were higher for single-born lambs compared with twin-born lambs. No significant maternal permanent environmental effect was detected for LE. Based on results using linear animal models with the full dataset, the direct heritabilities were 0.06 ± 0.01, 0.15 ± 0.01 and 0.52 ± 0.02, the maternal heritabilities were 0.03 ± 0.01, 0.15 ± 0.01 and 0.13 ± 0.02 for LE, BW and GL, respectively. The proportions of maternal permanent environmental effects to the total variances were 0.13 ± 0.01 for BW. Low to moderate direct genetic correlations of 0.31 ± 0.09 (LE and BW), 0.24 ± 0.11 (LE and GL) and 0.08 ± 0.08 (BW and GL) were estimated using tri-variate analysis from the full dataset, indicating the trend that lambs with greater BW and longer GL would result in more lambing difficulty.

scholarly journals Does the Acknowledgement of αS1-Casein Genotype Affect the Estimation of Genetic Parameters and Prediction of Breeding Values for Milk Yield and Composition Quality-Related Traits in Murciano-Granadina?

Animals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 679 ◽  
Author(s):  
María Gabriela Pizarro Inostroza ◽  
Vincenzo Landi ◽  
Francisco Javier Navas González ◽  
Jose Manuel León Jurado ◽  
Amparo Martínez Martínez ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Dry Matter ◽  
Production Efficiency ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Increase Production Efficiency ◽  
Breeding Programs ◽  
Breeding Values ◽  
Males And Females

A total of 2090 lactation records for 710 Murciano-Granadina goats were collected during the years 2005–2016 and analyzed to investigate the influence of the αS1-CN genotype on milk yield and components (protein, fat, and dry matter). Goats were genetically evaluated, including and excluding the αS1-CN genotype, in order to assess its repercussion on the efficiency of breeding models. Despite no significant differences being found for milk yield, fat and dry matter heritabilities, protein production heritability considerably increased after aS1-CN genotype was included in the breeding model (+0.23). Standard errors suggest that the consideration of genotype may improve the model’s efficiency, translating into more accurate genetic parameters and breeding values (PBV). Genetic correlations ranged from −0.15 to −0.01 between protein/dry matter and milk yield/protein and fat content, while phenotypic correlations were −0.02 for milk/protein and −0.01 for milk/fat or protein content. For males, the broadest range for reliability (RAP) (0.45–0.71) was similar to that of females (0.37–0.86) when the genotype was included. PBV ranges broadened while the maximum remained similar (0.61–0.77) for males and females (0.62–0.81) when the genotype was excluded, respectively. Including the αS1-CN genotype can increase production efficiency, milk profitability, milk yield, fat, protein and dry matter contents in Murciano-Granadina dairy breeding programs.

scholarly journals Genetic parameters and trends for lactation length in the first three lactations of Holstein cows

2012 ◽  
Vol 55 (6) ◽  
pp. 533-539
Author(s):  
N. G. Hossein-Zadeh
Keyword(s):  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Holstein Cows ◽  
Dairy Herds ◽  
Production Environment ◽  
Genetic Trend ◽  
Lactation Length ◽  
Breeding Center ◽  
Genetic Trends

Abstract. Calving records from the Animal Breeding Center of Iran collected from January 1986 to December 2007 and comprising 492424 calving events of Holsteins from 1413 dairy herds were analysed using linear animal models to estimate genetic parameters for lactation lengths in the first three lactations of Holstein cows. Genetic trends were obtained by regressing yearly mean estimates of breeding values on calving year. Heritability estimates for lactation lengths varied from 0.03 to 0.04 across the parities. Estimates of genetic correlations between lactation lengths in different parities ranged from 0.35 to 0.53. There was decreasing genetic trend for lactation length at parity 3 and there were increasing genetic trends for lactation lengths at parities 1 and 2 over the years (P<0.05). The low estimates of heritabilities obtained in this study imply that much of the improvement in lactation lengths could be attained by improvement of production environment rather than genetic selection.

scholarly journals Estimation of Genetic Parameters and Breeding Values of Milk Yield Using Test Day Model with Cubic Splines and Legendre Polynomials in Chinese Holstein Cattle

2021 ◽  
Vol 25 (02) ◽  
pp. 354-360
Author(s):  
Wan Lv
Keyword(s):  
Milk Yield ◽  
Legendre Polynomials ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Information Criterion ◽  
Additive Genetic Effect ◽  
Optimal Model ◽  
Breeding Values ◽  
Estimation Of Genetic Parameters

This study aimed to estimate the genetic parameters and breeding values of milk yield traits of Holstein cows in Shandong Province using the best model identified by a comparison between a numbers of alternative random regression test day models (RRMs). The data included 585,702 test day records of milk yield in the first lactation of 88,215 Holstein cows, covering 219 cattle farms in Shandong Province during the period from 2005 to 2016. Different models were investigated, which differed in the number of knots of Spline functions to improve the fitting of population lactation curve and in orders (2, 3, or 4) of Legendre polynomials to fit additive genetic effect and permanent environmental effect. The optimal test day model was screened out by Akaike information criterion (AIC) and Bayesian information criterion (BIC) criteria. Detailed analysis of genetic parameters and accuracy of estimation of breeding values were performed using the optimal model. In the results, the optimal model (Sp15-La4-Lp3) for analyzing the milk yield data was the one with 15 knots of Splines, 4 orders of Legendre polynomials for additive genetic effect and 3 orders of Legendre polynomials for permanent environmental effect. Using the optimal model, estimates of additive genetic variances of milk yield at different days in milk (DIM) during the whole lactation ranged from 8.54 to 15.39, the permanent environmental variance ranged from 17.65 to 31.42. Correspondingly, the heritability ranged from 0.20 to 0.30, and repeatability ranged from 0.43 to 0.54. Rank correlations between EBV of bull with different number of daughters and the bull’s parent average ranged from 0.79 to 0.94, and the correlations between EBV of bulls and the sire-maternal grandsire index ranged from 0.48 to 0.86. In conclusion, Sp15-La4-Lp3 could be the optimal model for estimation of genetic parameters and prediction of breeding values of milk in Shandong Holstein population. The amount of progeny information is critical to the conventional genetic evaluation of bulls. © 2021 Friends Science Publishers

scholarly journals Genetic parameters for milk yield in imported Jersey and Jersey-Friesian cows using daily milk records in Sri Lanka

2020 ◽  
Vol 33 (11) ◽  
pp. 1741-1754
Author(s):  
Amali Malshani Samaraweera ◽  
Vinzent Boerner ◽  
Hewa Waduge Cyril ◽  
Julius van der Werf ◽  
Susanne Hermesch
Keyword(s):  
Sri Lanka ◽  
Animal Models ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Random Regression ◽  
Breeding Values ◽  
Daily Milk Yield ◽  
Jersey Cows ◽  
Daily Milk ◽  
Friesian Cows

Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka.Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model.Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and –0.35 in Jersey-Friesian cows.Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.

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