952 resultados para test-day milk yield


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Dados de 39.578 controles leiteiros de 3.766 primeiras lactações de vacas da raça Holandesa, ocorridas de 1994 a 2002, foram analisados com os objetivos de estimar parâmetros genéticos para as produções de leite no dia do controle (PLDC) e para a produção até 305 dias de lactação (P305) e comparar estes dois critérios de seleção. Os componentes de variância foram estimados pelo método da máxima verossimilhança restrita, sob modelo animal univariado ou bivariado. Para as PLDC, os modelos incluíram o efeito aleatório genético aditivo, o efeito fixo de grupo contemporâneo e, como covariáveis, a idade da vaca ao parto (efeitos linear e quadrático) e os dias em lactação (efeito linear). Para a P305, foi utilizado o mesmo modelo, substituindo dias em lactação por duração da lactação. Os grupos de contemporâneos foram formados por ano, mês do controle e rebanho (para as PLDC) e por ano, época do parto e rebanho (para a P305). As herdabilidades estimadas para a P305 foram de 0,27 e 0,25 para as análises univariadas e bivariadas, respectivamente. Para as PLDC, as herdabilidades variaram de 0,11 a 0,31. Para o modelo bivariado (pelo qual avaliaram-se simultaneamente P305 e as PLDC), as herdabilidades para os controles (PLDC) foram menores, variando de 0,08 a 0,25. As maiores estimativas ocorreram para as produções do 4º e 5º controles, correspondendo aos 2º e 3º meses de lactação. As correlações genéticas entre P305 e os controles individuais foram positivas e elevadas, variando de 0,83 a 1,00. Os resultados indicaram que a seleção direta para P305, como tradicionalmente realizada, implicaria maiores ganhos genéticos para a produção de leite (PL) na maioria dos controles quinzenais. Além disso, a seleção direta para as produções parciais poderia proporcionar ganhos correlacionados também para a P305, mas estes ganhos seriam menores que os obtidos via seleção direta.

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Relationships of several reproductve traits and milk yield were studied in 716 Gyr cows at Sant'Ana da Serra farm, Mococa, State of São Paulo, a humid tropical climate region. Mean age at first calving was 49.8 +/- 0.4 months, with a coeficient of cariation (C. V.) of 20.8%. Only year of parturition significantly affected age at first calving (P < 0.01). Heritability, estimated from paternal half-sib correlations, was 0.91 +/- 0.20, a value considered unrealistically high. Overall mean gestation length was 287.7 +/- 0.5 days (C. V. = 3.3%) for 419 observations, with month and year of parturition having significant effects. Heritability estimate was 0.30 +/- 0.14. Overall mean dry period for 1.276 observations was 238 +/- 3 days (C. V. = 48%); repeatability estimate was 0.19 +/- 0.06. Estimated annual genetic trend for dry period was -0.6 days, phenotypic trend was 11.5 days, and environmental trend, 12.1 days. Month and year of parturition and cow age had no significant effect on dry period. Highest milk yield was obtained at fourth lactation. The gross correlation between milk yield and gestation period was 0.11, and between previous dry period and subsequent milk yield, 0.16. Normal gestations of 285 to 290 days were associated with higher milk yields. Milk yield increased as dry period advanced from 30 to 390 days, and declined as dry period continued beyond 390 days. Delays in first mating and a more extensive dry period decreased reproductive efficiency in the herd studied.

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Genetic parameters for the relation between the traits of milk yield (MY), age at first calving (AFC) and interval between first and second calving (IBFSC) were estimated in milk buffaloes of the Murrah breed. In the study, data of 1578 buffaloes at first lactation, with calvings from 1974 to 2006 were analyzed. The MTDFREML system was used in the analyses with models for the MY, IBFSC traits which included the fixed effects of herd-year-season of calving, linear and quadratic terms of calving age as covariate and the random animal effects and error. The model for AFC consisted of the herd-year-season fixed effects of calving and the random effects of animal and error. Heritability estimates MY, AFC and IBFSC traits were 0.20, 0.07 and 0.14, respectively. Genetic and phenotypic correlations between the traits were: MY and AFC = -0.12 and -0.15, MY and IBFSC = 0.07 and 0.30, AFC and IBFSC = 0.35 and 0.37, respectively. Genetic correlation between MY and AFC traits showed desirable negative association, suggesting that the daughters of the bulls with high breeding value for MY could be physiological maturity to a precocious age. Genetic correlation between MY and IBFSC showed that the selection of the animals that increased milk yield is also those that tend to intervals of bigger calving.

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Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Milk yield, fat yield, and fat percentage during the first three lactations were studied using New York Holsteins that were milked twice daily over a 305-d, mature equivalent lactation. Those data were used to estimate variances from direct and maternal genetic effects, cytoplasmic effects, sire by herd interaction, and cow permanent environmental effects. Cytoplasmic line was traced to the last female ancestor using DHI records from 1950 through 1991. Records were 138,869 lactations of 68,063 cows calving from 1980 through 1991. Ten random samples were based on herd code. Samples averaged 4926 dams and 2026 cytoplasmic lines. Model also included herd-year-seasons as fixed effects and genetic covariance for direct-maternal effects. Mean estimates of the effects of maternal genetic variances and direct-maternal covariances, as fractions of phenotypic variances, were 0.008 and 0.007 for milk yield, 0.010 and 0.010 for fat yield, and 0.006 and 0.025 for fat percentage, respectively. Average fractions of variance from cytoplasmic line were 0.011, 0.008, and 0.009 for milk yield, fat yield, and fat percentage. Removal of maternal genetic effects and covariance for maternal direct effects from the model increased the fraction of direct genetic variance by 0.014, 0.021, and 0.046 for milk yield, fat yield, and fat percentage; little change in the fraction was due to cytoplasmic line. Exclusion of cytoplasmic effects from the model increased the ratio of additive direct genetic variance to phenotypic variance by less than 2%. Similarly, when sire by herd interaction was excluded, the ratio of direct genetic variance to phenotypic variance increased 1% or less.

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Heterogeneity of variances for milk yield (MY) was determined for Brazilian and Colombian herds. The herds were grouped as high or low variability within each country, using as criterion the phenotypic standard deviation (PSD) of MY in the contemporary groups of cows, from the first to the sixth calving. Brazilian and Colombian herds with PSD greater than 1,168 kg or 1,012 kg, respectively, were classified as high variability while the herd groups with values lower than those were classified as low variability. The genetic parameters for MY within each herd group were estimated using bivariate analysis in an animal model and the restricted maximum likelihood method with a derivative free algorithm, using 72,280 first lactations of cows, daughters of 1,880 sires. Heterogeneous variances were found, and Brazilian herds with high PSD had the greatest additive and residual genetic variances and heritability coefficients for MY. MY genetic correlation coefficients between herds of high and low variability within each country were 0.96 and 0.93 while between countries they varied from 0.72 to 0.81, suggesting that there was a reclassification of animals in the two countries and also heterogeneity of variances. This phenomenon leads to the questioning of the strategy of imported semen usage and the need to do genetic evaluations to identify sires with greater genetic potential for (sub) tropical environmental conditions.

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Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

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In the present study, data of 1,578 first lactation females, calving from 1985 to 2006 were analysed with the purpose of estimating genetic parameters for milk yield (MY), age at first calving (AFC) and interval between first and second calving (IBFSC) in dairy buffaloes of the Murrah breed in Brazil, Heritability estimates for MY, AFC and IBFSC traits were 0.20, 0.07 and 0.14, respectively. Genetic correlations between MY and AFC and IBFSC were -0.12 and 0.07, respectively, while the corresponding phenotypic correlations were -0.15 and 0.30, respectively. Genetic and phenotypic correlations between AFC and IBFSC were 0.35 and 0.37, respectively. Genetic correlation between MY and AFC showed desirable negative association, suggesting that daughters of the bulls with high breeding values for MY could reach physiological mature at a precocious age. Genetic correlation between MY and IBFSC, showed that the selection for milk production could result in the increase of calving intervals.

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Ghrelin is a gastrointestinal hormone that acts in releasing growth hormone and influences the body general metabolism. It has been proposed as a candidate gene for traits such as growth, carcass quality, and milk production of livestock because it influences feed intake. In this context, the aim of this study was to verify the existence of polymorphisms in the ghrelin gene and their associations with milk, fat and protein yield, and percentage in water buffaloes (Bubalus bubalis). A group of 240 animals was studied. Five primer pairs were used and 11 single nucleotide polymorphisms (SNP) were found in the ghrelin gene by sequencing. The animals were genotyped for 8 SNP by PCR-RFLP. The SNP g.960G>A and g.778C>T were associated with fat yield and the SNP g.905T>C was associated with fat yield and percentage and protein percentage. These SNP are located in intronic regions of DNA and may be in noncoding RNA sites or affect transcriptional efciency. The ghrelin gene in buffaloes influences milk fat and protein synthesis. The polymorphisms observed can be used as molecular markers to assist selection. © 2013 American Dairy Science Association.

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The major objective of this study was to estimate heritability and genetic correlations between milk yield (MY) and calving interval (CI) and lactation length (LL) in Murrah buffaloes using Bayesian inference. The database used belongs to the genetic improvement program of four buffalo herds from Brazil. To obtain the estimates of variance and covariance, bivariate analyses were performed with the Gibbs sampler, using the program MTGSAM. The heritability coefficient estimates were 0.28, 0.03 and 0.15 for MY, CI and LL, respectively. The genetic correlations between MY and LL was moderate (0.48). However, the genetic correlation between MY and CI showed large HPD regions (highest posterior density interval). Milk yield was the only trait with clear potential for genetic improvement by direct mass selection. The genetic correlation between MY and LL indicates that indirect selection using milk yield is a potentially beneficialstrategy.Theinterpretation of the estimated genetic correlation between MY and CI is difficult and could be spurious. ©2013 Sociedade Brasileira de Zootecnia.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The objective of the study was to estimate heritability and repeatability for milk yield (MY) and lactation length (LL) in buffaloes using Bayesian inference. The Brazilian genetic improvement program of buffalo provided the data that included 628 females, from four herds, born between 1980 and 2003. In order to obtain the estimates of variance, univariate analyses were performed with the Gibbs sampler, using the MTGSAM software. The model for MY and LL included direct genetic additive and permanent environment as random effects, and contemporary groups, milking frequency and calving number as fixed effects. The convergence diagnosis was performed with the Geweke method using an algorithm implemented in R software through the package Bayesian Output Analysis. Average for milk yield and lactation length was 1,546.1 +/- 483.8 kg and 252.3 +/- 42.5 days, respectively. The heritability coefficients were 0.31 (mode), 0.35 (mean) and 0.34 (median) for MY and 0.11 (mode), 0.10 (mean) and 0.10 (median) for LL. The repeatability coefficient (mode) were 0.50 and 0.15 for MY and LL, respectively. Milk yield is the only trait with clear potential for genetic improvement by direct genetic selection. The repeatability for MY indicates that selection based on the first lactation could contribute for an improvement in this trait.