Non-agreement between 2 serologic techniques for detecting antibody to Brucella ovis in naturally infected sheep.

Brucella ovis is the causative agent of ovine brucellosis, which is an important infectious disease in sheep farming worldwide and is responsible for economic losses because of its negative effect on the reproductive system of rams and ewes. Serologic tests are the main tools for detection of infection; however, these tests commonly yield a high frequency of false-negative results. We compared 2 serologic tests, agar gel immunodiffusion (AGID) and ELISA, for the detection of anti-B. ovis antibodies in naturally infected sheep. Of the 728 serum samples analyzed, 0.3% were positive by AGID and 9.2% by ELISA. Positive results were obtained for different animals and flocks. There was no statistical difference between the detection frequency of the 2 methods (p = 0.674), and the kappa test indicated low concordance (κ = 0.005). The lack of agreement between results obtained using AGID and ELISA, associated with the absence of clinical signs, makes it difficult to detect ovine brucellosis efficiently, and demonstrates the need for effective tests for the definitive detection of B. ovis infection.

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion.