Genetic Parameters For Milk Yield Research Articles

Estimação de parâmetros genéticos utilizando-se a produção de leite no dia do controle em primeiras lactações de vacas da raça Jersey

Registros da produção de leite de 3.531 controles de 620 primíparas da raça Jersey foram utilizados para a estimação dos componentes de covariância e dos parâmetros genéticos para a produção de leite por meio dos modelos de repetibilidade e de regressão aleatória. O modelo de repetibilidade (MR) incluiu os efeitos fixos de rebanho-ano-mês do controle, estação do parto e idade da vaca ao parto como covariável, com termos linear e quadrático, e os efeitos aleatórios de animal, de ambiente permanente e residual. O modelo de regressão aleatória incluiu os mesmos efeitos do MR, com o uso da função de Wilmink para a modelagem dos efeitos fixo (estação de parto) e aleatórios (genético de animal e de ambiente permanente). As estimativas de variância genética aditiva, de ambiente permanente, residual e fenotípica, e de herdabilidade e repetibilidade para a produção de leite usando-se o MR foram, respectivamente, 7,08; 1,88; 7,79 e 16,76 kg² e 0,42 e 0,50. Pelo modelo de regressão aleatória, os valores de herdabilidade para a produção de leite decresceram de 0,81 a 0,20 ao longo da lactação. As estimativas de variância genética aditiva mantiveram-se praticamente constantes durante a lactação, com maiores valores no início e final da lactação. As correlações genéticas foram próximas à unidade para as produções de leite da fase intermediária da lactação e diminuíram com o aumento do período entre os controles leiteiros. O modelo de repetibilidade não é a melhor alternativa para a modelagem das produções de leite no dia do controle da primeira lactação de vacas Jersey no Brasil.

Comparison of homogeneity and heterogeneity of residual variance using random regression test‐day models for first lactation Japanese Holstein cows

ABSTRACTUsing a large‐scale data set that included first lactation test day records from 1975 to 2000 for Japanese Holsteins, genetic parameters for milk yield were estimated by using random regression (RR) test‐day models (TDM) with heterogeneous and homogeneous residual variances. It is necessary for the RR‐TDM to include a function that explains the shape of the lactation curve. The RR‐TDM with the LW curve, which combined Wilmink's curve and a Legendre polynomial, was used for fitting the model for milk yield. In recent years, increases in residual variance have been noted for Japanese dairy cattle. Thus, three kinds of heterogeneous residual variance over the calving year were considered: H1, H2 and HG. Linear and quadratic exponential functions for the calving year were used in H1 and H2, respectively. Residual variance of HG was divided into five groups according to calving year. Homogeneous residual variance was HO. All heterogeneous residual variances increased with calving year in an almost linear fashion. Residual variance increased over the study period. However, there is no need to consider heterogeneous residual variances in genetic evaluations, because the heterogeneity of residual variance over the years did not affect the ranking of top sires and cows.

Genetic Parameters of Milk Yield and Milk Fat Percentage Test Day Records of Iranian Holstein Cows

Genetic parameters for first lactation milk production based on test day (TD) records of 56319 Iranian Holstein cows from 655 herds that first calved between 1991 and 2001 were estimated with restricted maximum likelihood method under an Animal model. Traits analyzed were milk yield and milk fat percentage. Heritability for TD records were highest in second half of the lactation, ranging from 0.11 to 0.19 for milk yield and 0.038 to 0.094 for milk fat percentage respectively. Estimates for lactation records for these traits were 0.24 and 0.26 respectively. Genetic correlations between individual TD records were high for consecutive TD records (>0.9) and decreased as the interval between tests increased. Estimates of genetic correlations of TD yield with corresponding lactation yield were highest (0.78 to 0.86) for mid-lactation (TD3 to TD8). Phenotypic correlations were lower than corresponding genetic correlations, but both followed the same pattern. For milk fat percentage no clear pattern was found. Results of this study suggested that TD yields especially in mid-lactation may be used for genetic evaluation instead of 305-day yield. (Asian-Aust. J. Anim. Sci. 2005. Vol 18, No. 9 : 1231-1236)

Parâmetros genéticos para a produção de leite de controles individuais de vacas da raça Gir estimados com modelos de repetibilidade e regressão aleatória

Registros individuais perfazendo 8.183 controles de produção de leite (PLC) de 1.273 primeiras lactações de vacas da raça Gir de rebanhos supervisionados pela ABCZ no período 1994/2000 foram utilizados para se estimar componentes de variância e parâmetros genéticos para PLC usando-se REML. Foram comparados um modelo de repetibilidade e modelos de regressão aleatória ajustados com as funções logarítmica (Ali & Schaeffer, 1987), exponencial (Wilmink, 1987) e polinômios ortogonais de Legendre (LP) de ordem 3 a 5, sob as pressuposições de homogeneidade e heterogeneidade de variância residual, definidas respectivamente por uma (ME=1) ou quatro classes de medidas de erro temporário (ME=4) ao longo do período de lactação. Também ajustou-se a produção de leite acumulada na lactação (P305) utilizando-se um modelo animal cuja estimativa de heritabilidade foi 0,22. As estimativas de heritabilidade e repetibilidade para a PLC foram 0,27 e 0,76, respectivamente. As estimativas de heritabilidade com a FAS e a FW alcançaram respectivamente 0,59 e 0,74 ao início da lactação e decresceram para valores próximos de 0,20 ao final do período. Exceto para o LP de quinta ordem com ME=1, as estimativas de heritabilidade diminuíram de 0,70 no início para 0,30 no final da lactação. Menores estimativas de VR foram obtidas para a FAS do que para a FW sob ambas as pressuposições de homogeneidade e heterogeneidade de variância. Em todos os estádios da lactação, as estimativas de VR diminuíram com o aumento da ordem do LP e dependeram da pressuposição sobre o ME. As estimativas das variâncias genética e de ambiente permanente não apresentaram nenhuma tendência com o aumento da ordem do LP e não se observaram diferenças significativas para tais estimativas sob a pressuposição de heterogeneidade de VR ao longo da lactação. Maiores valores de correlação genética entre as PLC foram obtidos com a FW, que também apresentou maior número de estimativas negativas entre as PLC do início e fim da lactação do que a FAS. Exceto para a FAS, observou-se redução das estimativas de correlação genética próximas à unidade entre as PLC adjacentes para valores negativos entre as PLC no início e no fim da lactação. Entre os polinômios de Legendre, o de quinta ordem apresentou um melhor o ajuste das PLC. Os resultados indicam o potencial de uso de regressão aleatória, com os modelos LP5 e a FAS apresentando-se como os mais adequados para a modelagem das variâncias genética e de efeito permanente das PLC da raça Gir.

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

Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.

Estimates of Genetic Parameters of Milk Yield in Brown Swiss and Holstein Friesian Cattle

Estimates of Genetic Parameters of Milk Yield in Brown Swiss and Holstein Friesian Cattle

Estimates of correction factors for lactation length and genetic parameters for milk yield in buffaloes

Correction factors for milk yield at 90, 240, 270 and 305 days of lactation of buffaloes and genetic and environmental parameters for milk yield of these lactation periods were estimated. The data used consisted of 3888 lactation records of 1630 buffaloes from 10 herds reared in the State of São Paulo. Genetic parameters were estimated by the derivative free restricted maximum likelihood method, fitting an animal repeatability model. Heritability estimates for milk yield corrected for 90, 240, 270 and 305 days of lactation were 0.17, 0.15, 0.14 and 0.14, respectively. In this same order, repeatability estimates were 0.40, 0.44, 0.41 and 0.41. The genetic correlation estimates between these corrected milk yields ranged from 0.96 to 1.00. The multiplicative correction factors for the different classes of lactation lengths were efficient for adjustment of milk yield at 90, 240, 270 and 305 days of lactation.

Heritability and Genetic Correlations of Test Day Milk Yield and Composition, Individual Laboratory Cheese Yield, and Somatic Cell Count for Dairy Ewes

Genetic parameters for milk yield, contents of fat, total protein, casein and serum protein, individual laboratory cheese yield, and somatic cell counts (SCC) were estimated from 7492 monthly test-day records of 1119 Churra ewes. Estimates were from multivariate REML using analytical gradients (AG-REML) procedures. Except for fat content, estimates for the other routinely recorded traits (milk yield, protein content, and SCC) agreed with those previously obtained in this and other dairy sheep populations. Protein content and composition had the highest heritabilities and repeatabilities. Heritabilities for protein and casein contents were very similar (0.23 and 0.21, respectively), and genetic correlation between the traits was close to unity (0.99). Accordingly, casein content is not advisable as an alternative to protein content as a selection criterion in dairy ewes; it does not have any compelling advantages and costs more to measure. Individual laboratory cheese yield (ILCY) obtained with Churra ewes had a low heritability (0.08), suggesting that potential for selection for this parameter would be possible but is not recommended. All correlations with ILCY were high and positive except for milk yield. A high SCC was accompanied by an increase in serum protein content and involved a loss in milk yield.

Genetic parameters for milk yield and some reproductive traits of Holstein cows using REML and Gibbs sampling

Genetic parameters for milk yield and some reproductive traits of Holstein cows using REML and Gibbs sampling

Genetic parameters for milk yield and faecal nematode egg count in Saanen does

Results of two herd tests per lactation (each comprising daily milk yield and yield of fat and protein (FP)) and faecal nematode egg counts (FEC) on Saanen does in Northland, New Zealand, were recorded during the lactations of 1991/92 to 1996/97. The data were used to estimate genetic parameters for milk yield and FP, and for FEC. A total of 4738 records from 1161 does, the daughters of 53 sires, were available. Restricted maximum likelihood procedures with an animal model were used for analyses. Overall, daily yields of milk and FP were 1.40 litres and 0.091 kg (average concentration 64.4 g/litre). Among the five age classes of doe, milk yield ranged from 0.93 to 1.80 litres, while FP ranged from 0.061 to 0.117 kg. Geometric mean FECs ranged from 974 to 1241 eggs/g faeces among does of different ages, and from 748 to 3093 eggs/g among years (lactations). There was a curvilinear relationship between all three traits and days in milk, with declining yields and FEC as lactation progressed. The heritabilities (h2) for milk yield and FP averaged 0.23 ± 0.04 and 0.27 ± 0.04, respectively, with corresponding repeatability (r) values of 0.26 + 0.03 and 0.27 ± 0.03. Estimates of h2 for loge(FEC+100) across years were 0.09 ± 0.05 (mid lactation) and 0.06 ± 0.04 (late lactation), with corresponding r values of 0.09 ± 0.06 and 0.15 ± 0.04. The genetic correlation between milk yield and FP was 0.87 ± 0.03, and those between FEC and milk yield or FP were ‐0.21 ± 0.26 and ‐0.17 ± 0.24, respectively. Phenotypic correlations between milk yield and FP, FEC and milk yield, and FEC and FP averaged 0.88 ± 0.01, ‐0.07 ± 0.03, and ‐0.07 ± 0.03, respectively.

Genetic parameters of milk yield and adjustment for age at calving in Nili-Ravi buffaloes

Genetic parameters of milk yield and adjustment for age at calving in Nili-Ravi buffaloes

Estimation of Genetic Parameters for Milk Yield and Fat and Protein Contents of Milk from Murciano-Granadina Goats

A total of 10,289 lactations, corresponding to 4967 does distributed in 35 herds, was used to estimate heritabilities, repeatabilities, and correlations among milk yield (kilograms), fat contents, and protein contents (grams/100g of milk) with single-trait and multiple-trait animal models using repeated records. Single-trait estimates were similar to those obtained with multiple-trait analysis. Heritabilities were 0.18, 0.16, and 0.25 with single-trait analysis and 0.17, 0.14, and 0.22 with multiple-trait analysis for milk yield, fat content, and protein content, respectively. Repeatabilities were 0.39, 0.36, and 0.47 with single-trait analysis and 0.36, 0.33, and 0.41 with multiple-trait analysis for milk yield, fat content, and protein content, respectively. Genetic correlations were –0.89 between milk yield and fat content, –0.65 between milk yield and protein content, and 0.93 between fat and protein contents. Phenotypic correlations were –0.48 between milk yield and fat content, –0.47 between milk yield and protein content, and 0.54 between fat and protein contents. Heritabilities and repeatabilities were lower, and correlations were higher, than those found in the literature. Some combination of both EBV of milk yield and protein content would be a good criterion for selection to improve milk yield while maintaining fat and protein contents.

Genetic Parameters for Milk Yield, Survival, Workability, and Type Traits for Australian Dairy Cattle

Genetic parameters, such as heritabilities and genetic correlations were estimated for milk yield, survival, workability, and type traits for Australian Holstein-Friesian and Jersey cattle. All analyses were performed using multivariate REML with a sire model. Heritabilities for lactation yield traits were moderate, ranging from .20 to .28, and heritabilities for mean test day deviations were approximately .40 higher. Heritabilities for survival (probability of surviving to the next lactation) were low, ranging from .02 to .08. Genetic correlations between survival scores were high, ranging from .37 to .98, in particular between adjacent survival scores (on average .91 and .97 for Holstein-Friesians and Jerseys). Heritabilities for stayabilities were larger, ranging from .03 to .22. On average, genetic correlations between stayabilities were very high ranging from .66 to .99. For milking speed, temperament, and likeability, heritability estimates ranged from .18 (for likeability in Holstein-Friesians) to .29 (for milking speed in Jerseys). Undesirable scores for milking speed and temperament had negative genetic correlations with stayabilities (correlations approximately –.20). Heritabilities for type traits were all moderate (.11 to .42), and genetic correlations among type traits and between type traits and production traits were large. Phenotypic correlations between type traits and stayabilities were low. Generally, genetic correlations between type traits and stayabilities were low although the standard errors of those estimates were large.

Genetic Parameters of Milk Yield and Composition and Their Relationships with Alternative Breeding Goals

Milk records on 32,077 Holstein cows in first lactation from 1116 herds on the Quebec Dairy Herd Analysis Service between 1973 and 1983 were used to estimate heritabilities of and genetic correlations between milk, fat, protein, and carrier (water, lactose, ash) yields; fat, protein, and carrier percentages; and ratios of protein to fat and protein plus fat to carrier. The cows were daughters of 451 sires; each sire was represented by five or more daughters. Heritabilities were from .20 to .31 for yields, .59 to .61 for percentages, and .58 to .61 for ratio measures. The heritability of protein yield was considerably lower than other yield traits (.20 vs. .28 to .31).The expected effects of multiple trait selection under 10 alternative breeding goals, using different sets of relative economic values, were considered using the genetic parameter estimates. Selection under the existing pricing system (milk yield plus fat percentage differential) had similar expected genetic gains for fat and protein yields as would be achieved under goals that either gave weight to milk yield and fat yield or to milk yield and the ratio of protein plus fat to carrier. Inclusion of information on protein percentage in an index gave relative little additional genetic progress in most traits, excpet some increases in protein yield and protein percentage were expected to be greater.

Genetic parameters for test-day milk yield in tropical Holstein Friesian cattle fitting a multiple-lactation random regression animal model

Accurate estimates of genetic parameters are essential for genetic improvement of milk yield in dairy cattle and for setting up breeding programmes. Estimates of genetic parameters from test-day models, particularly for Holstein Friesian cattle maintained in tropical environments, are scant in the literature. The objective of this study was therefore to estimate genetic parameters for milk yield by fitting a multiple-lactation random regression animal model (RRM) based on data from Ethiopian Holstein Friesian herds. Data were used from the first three lactations of cows that calved between 1997 and 2013. The data comprised 13 421 test-day milk yield records from 800 cows from two large dairy herds. Variance components were estimated using the average information restricted maximum likelihood method fitting an RRM. Heritability estimates for first, second, and third lactations ranged from 0.20 to 0.26, 0.15 to 0.27, and 0.17 to 0.28, respectively. Heritability estimates ranging from 0.15 to 0.28 indicate that effective genetic improvement should be accompanied by a corresponding improvement of the production environment. Across-lactation genetic correlations between first and second, second and third, and first and third lactations, expressed on a 305-day yield basis, were 0.88, 0.83, and 0.70, respectively. These genetic correlations, less than or equal to 0.88, indicate that different lactations are different traits. For an accurate evaluation of the genetic merit of animals for milk yield, lactations should be treated as different, but correlated traits in a multiple-lactation analysis.Keywords: Genetic correlation, heritability, Legendre polynomial, test-day model

Genetic and Environmental Parameters of Milk Constituents for Five Breeds. II. Some Genetic Parameters

Estimates were made of some genetic parameters of milk yield and its components and of the breeding values of sires for yields and constituent percentages. The data consisted of 1.449 cows of the Ayrshire, Guernsey, Holstein, Jersey, and Brown Swiss breeds located in 43 herds.Based on the average of five breeds, the herd effect as a percentage of the total variance in the unadjusted data ranged from 25 to 31% for yields and 7 to 16% for constituents. The repeatability of lactation records by intraclass correlation ranged from 0.31 to 0.48 for yields and 0.56 to 0.79 for constituents. The heritability estimates by paternal half-sibs on a breed average basis were: for yields of milk, 0.35; fat, 0.27; protein, 0.30; SNF, 0.34; TS, 0.31; and for percentages of fat, 0.42; protein, 0.40; SNF, 0.36; and TS, 0.45. The expected breeding values obtained by regressing the least-squares sire constant showed large genetic differences in the transmitting abilities of the sires for the traits studied. Because of the negative relationship between most of constituent percentages and milk yield, an index is needed in a selection program to secure the optimum yield with the desired composition of milk.