222 resultados para Caprine milk


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

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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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In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

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The objective was to evaluate the effect of unsaturated fatty acid sources supplementation on nutrients balances and milk fatty acid profile of mid lactation dairy cows. Twelve Brazilian Holstein cows in the mid lactation (mean of 128 days) and (580 ± 20kg of weight; mean ± SD) with milk yield of 25kg/d were assigned randomly into three 4 × 4 Latin square, fed the following diets: control (C); refined soybean oil; (SO); whole soybean raw (WS) and; calcium salts of unsaturated fatty acids (CSFA). Milk yield was 26.6; 26.4; 24.1 and 25.7 to the diets CO, SO, WS and CSFA respectively. Cows fed the WS treatment produced less milk (1.95kg/d of milk), fat and lactose than did cows fed the SO and CSFA. Cows fed the CSFA treatment showed less blood, urine (g/d) concentrations of N more energetic efficiency and intake of energy than did cows fed the SO treatment. Cows fed the unsaturated fatty acids sources showed more C18:2 cis-9, trans-11 CLA and trans-C18:1 FA concentration in milk than did cows fed the CO treatment. Diets with whole soybeans and soybeans oil provide more efficient digestive processes, and increase milk composition of unsaturated fatty acids.

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The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.

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Mastitis is an important disease for the dairy industry worldwide, causing economic losses and reducing milk quality and production. Staphylococcus aureus is a worldwide agent of this intramammary infection, which also causes foodborne diseases. The objective of this study was to determine the frequency of methicillin-susceptible Staphylococcus aureus (MSSA) isolates in milk of mastitis cows in Brazil and to analyze the genetic lineages and the content of antimicrobial resistance genes and virulence factors among these isolates. Fifty-six MSSA isolates were recovered from 1,484 milk samples (positive for the California mastitis test) of 518 cows from 11 different farms in Brazil (representing 51% of total Staph. aureus obtained), and they were further characterized. Methicillin-susceptible Staphylococcus aureus were isolated from 3.7% of California mastitis test-positive tested milk samples and from 6.2% of tested mastitic cows. Methicillin-susceptible Staphylococcus aureus isolates were characterized by spa typing, agr typing, and multilocus sequence typing, and resistance and virulence traits were investigated by PCR. Seven spa types were identified among MSSA (% of isolates): t127 (44.6), t605 (37.5), t002, t1784, t2066 (1.8), and 2 new ones: t10856 (10.7) and t10852 (1.8). Five distinct sequence types (ST) were detected (% of isolates): ST1 (46.4), ST126 (37.5), ST133 (10.7), ST5 (3.6), and a novel ST registered as ST2493 (1.8). Resistances were detected for streptomycin, chloramphenicol, and tetracycline. One strain contained the chloramphenicol resistance gene (fexA; included within transposon Tn558) and 3 strains contained the tetracycline resistance gene [tet(K)]. Methicillin-susceptible Staphylococcus aureus strains were susceptible to most of the antibiotics studied and lacked the virulence genes of Panton-Valentine leukocidin (lukF/S-PV), toxic shock syndrome toxin 1 (tst), exfoliative toxin A (eta), and exfoliative toxin B (etb), as well as the genes of the immune evasion cluster. Methicillin-susceptible Staphylococcus aureus isolates were detected in a relatively low proportion of cows with mastitis (6.2%) and recovered isolates presented high diversity of genetic lineages, with CC1 and CC126 the predominant clonal complexes, and CC133 also being detected. Larger epidemiological studies with molecular characterization of isolates are required to deepen the knowledge on the circulating genetic lineages among the cow population with mastitis. © 2013 American Dairy Science Association.

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We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

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

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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.

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The objective of this study was to estimate genetic parameters for milk yield at 244 days and lactation length in graded buffalo cows at the El Cangre Cattle Genetic Enterprise. Data were gathered from 2575 lactations, 1377 buffalo cows, 37 milking units and between 2002-2009 calving years. It was employed the Restricted Maximum Likelihood method (REML) for estimating (co) variance components with multi trait model. Average of milk yield at 244 days and lactation length were 864 kg and 240 days, respectively. Heritability was 0.15 for milk yield and 0.13 for lactation length. Genetic correlation between these traits was 0.63. It was concluded that it is necessary to intensify selection and to increase control of the information of the genetic herds to obtain high precision in the estimates and therefore, obtain bigger genetic progress in of this species in our country.

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Knowing the genetic parameters of productive and reproductive traits in milking buffaloes is essential for planning and implementing of a program genetic selection. In Brazil, this information is still scarce. The objective of this study was to verify the existence of genetic variability in milk yield of buffaloes and their constituents, and reproductive traits for the possibility of application of the selection. A total of 9,318 lactations records from 3,061 cows were used to estimate heritabilities for milk yield (MY), fat percentage (%F), protein percentage (%P), length of lactation (LL), age of first calving (AFC) and calving interval (CI) and the genetic correlations among traits MY, %F and %P. The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year and calving season), number of milking (2 levels), and age of cow at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. Estimated heritability values for MY, % F, % P, LL, AFC and CI were 0.24, 0.34, 0.40, 0.09, 0.16 and 0.05, respectively. The genetic correlation estimates among MY and % F, MY and % P and % F and % P were -0.29, -0.18 and 0.25, respectively. The production of milk and its constituents showed enough genetic variation to respond to a selection program. Negative estimates of genetic correlations between milk production and its components suggest that selection entails a reduction in the other.