Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

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.

Milk fatty acid characterization and genetic parameter estimates for milk conjugated linoleic acid in buffaloes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Density and rheological parameters of goat milk

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

FLOW PROPERTIES and TUBE FRICTION FACTOR of MILK CREAM: INFLUENCE of TEMPERATURE and FAT CONTENT

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

Estudo de efeitos ambientais que influem na forma da curva de lactação de cabras mestiças no estado da Paraíba

Conselho Nacional do Desenvolvimento Científico e Tecnológico (CNPq)

Use of a new milk-clotting protease from Thermomucor indicae-seudaticae N31 as coagulant and changes during ripening of Prato cheese

Prato cheeses were manufactured using coagulant from Thermomucor indicae-seudaticae N31 or a commercial coagulant. Cheeses were characterised using the following analysis: yield; fat; acidity; moisture; ash; salt; pH; total nitrogen; total protein; NS-pH 4.6/NT100; NS-TCA 12%/NT100; casein electrophoresis; and RP-HPLC. The results were statistically analysed and revealed that the proteolytic indices were not significantly different throughout the 60 days of ripening of cheeses made with either coagulant. Even though there were some quantitative differences in the peptide profile of cheeses, the enzyme from T. indicae-seudaticae N31 was used in the production of good quality Prato cheese without having to change the established technological parameters of the process. © 2011 Elsevier Ltd. All rights reserved.

Yield, changes in proteolysis, and sensory quality of Prato cheese produced with different coagulants

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Production, composition and processing of milk from ewes fed soybean seeds

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