Determining the gestational age of crioulo mares based on a fetal ocular measure

The practice of covering in herds is often used in Crioulo breeding farms, thus not allowing the determination of ovulation dates and the early detection of pregnancies. This fact complicates the estimation of gestational age after 70 days of conception. This study aimed to evaluate the diameter of the fetal orbits of Crioulo mares to develop a formula to estimate a gestational date. Measurements of 164 fetal ocular orbits were performed in 124 Crioulo mares with gestational ages ranging between 119 and 341 days. The current study observed a linear growth pattern of Crioulo fetal orbits up to 341 days of gestation. Thus, obtaining a suitable linear regression model to determine the gestational age of Crioulo mares based on fetal ocular orbit diameter measure is possible. The obtained model was y = 8.3756x + 11.90, where y represents the gestational age in days, and x represents the diameter of the fetal ocular orbit in millimeters. This formula had anr2 of 0.985 (P < .001). We conclude that this model allows researchers and veterinarians to accurately estimate the gestational age of Crioulo mares between 4 and 11months of pregnancy. © 2013 Elsevier Inc.

Report on the activities of the working groups created at the Third Meeting of the Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Includes bibliography

Report on the activities of the working groups created at the Third Meeting of the Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Includes bibliography

Documentos presentados a la Tercera Reunión de la Conferencia Estadística de las Américas de la Comisión Económica para América Latina y el Caribe = Documents presented at the Third Meeting of the Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Incluye Bibliografía

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.

Third Meeting of the Expert Group on Poverty Statistics (Rio Group)

Includes bibliography

Age declaration, mortality and selected socioeconomic characteristics of the elderly

Includes bibliography