The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...

The aim of this study was using Bayesian approach via Gibbs sampling (GS) for estimating genetic parameters of production, reproduction and health traits in Iranian Holstein cows. Data consisted of 320666 first- lactation records of Holstein cows from 7696 sires and 260302 dams collected by the animal breeding center of Iran from year 1991 to 2010. (Co) variance components were estimated using ...

The purpose of this study was to find out whether abilities to win races of different distances are different traits. Data included information on 14 665 starts of 1 646 Thoroughbreds, aged 2 to 9 years and on 10 862 starts of 1 145 Arab horses, aged 3 to 10 years. The data comprised seven racing distances for Thoroughbred horses, i.e. 1 000, 1 200, 1 300, 1 400, 1 600, 1 800, >1 800 m, and fiv...

The genetic analysis of characters that are best considered as functions of some independent and continuous variable, such as age, can be a complicated matter, and a simple and efficient procedure is desirable. Three methods are common in the literature: random regression, orthogonal polynomial approximation, and character process models. The goals of this article are (i) to clarify the relatio...

Data from the centralised performance tests for young beef bulls in South Africa were used to determine the minimum test duration required to obtain an accurate measure of feed intake, growth rate and two measures of feed efficiency: feed conversion ratio and residual feed intake. Five breeds from four different biological types were used to investigate whether different duration tests are requ...

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression a...

Obtaining accurate estimates of the genetic covariance matrix Sigma(G) for multivariate data is a fundamental task in quantitative genetics and important for both evolutionary biologists and plant or animal breeders. Classical methods for estimating Sigma(G) are well known to suffer from substantial sampling errors; importantly, its leading eigenvalues are systematically overestimated. This art...

Total litter weight weaned at 120 d postpartum per ewe lambing is often believed to be a measure of range ewe productivity. Genetic correlations for litter weight weaned at 120 d with prolificacy, growth, and wool traits for Columbia, Polypay, Rambouillet, and Targhee sheep were estimated using REML with animal models. Observations per breed ranged from 5,140 to 7,083 for litter weight weaned, ...

Estimates of covariance components and genetic parameters were obtained for birth, weaning, 200-d, and 400-d weight for a herd of Polled Herefords and a herd of a multibreed synthetics, the so-called Wokalups. Data originated from an experiment in Western Australia selecting for preweaning growth rate. Analyses were carried out by REML fitting an animal model including genetic and permanent env...