Epidemiology of Bovine Neosporosis in Relation to Socioeconomic, Demographic, and Transmissibility Factors in Dual-Purpose Production Systems in Colombia.

Introduction: Bovine neosporosis represents a significant threat to reproduction and production in livestock systems worldwide. This disease is caused by the protozoan , resulting in abortions of cows and neurological signs in newborn calves. This leads to significant economic losses, decreasing meat and milk production, especially in tropical regions.

Economic utility of Colombian Romosinuano cattle.

The objective of this study was to quantify the economic utility in Romosinuano production systems by developing a bioeconomic model assumed cow-calf, cow-calf plus stocker (CCPS), and complete cycle operations. Each system produced males for sale and females for replacement. Input parameters were established from breed data collected by AGROSAVIA.

Genealogical structure of the Colombian Romosinuano Creole cattle.

The Romosinuano cattle breed is one of the most important Creole genetic resources in Colombia, and interesting traits like adaptation or reproductive efficiency have promoted its use in different countries in America. To consolidate the genealogical historical records, the review of very first yield records in this population was used to reconstruct the genealogy of the breed since the first animals incorporated to the in vivo germplasm bank and estimate different demographic parameters. The complete genealogy comprises 17,136 animals with 5.

Genetic parameters and trends for growth traits in Blanco Orejinegro cattle.

Since 1940, efforts have been made to preserve the Blanco Orejinegro (BON) cattle breed by maintaining gene banks. Nine years ago, a BON genetic improvement program was implemented to increase genetic gain based on control of productivity and the use of performance tests, polygenic and genomic evaluations, and selection indices. The objective of this study was to estimate genetic parameters and trends for growth traits by using polygenic (PM) and genomic-polygenic (GPM) models.

Using near-infrared spectroscopy to determine intramuscular fat and fatty acids of beef applying different prediction approaches.

This study aimed to predict fat and fatty acids (FA) contents in beef using near-infrared spectroscopy and prediction models based on partial least squares (PLS) and support vector machine regression in radial kernel (R-SVR). Fat and FA were assessed in 200 longissimus thoracis samples, and spectra were collected in reflectance mode from ground meat. The analyses were performed for PLS and R-SVR with and without wavelength selection based on genetic algorithms (GAs).