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Genetic variability and structure of the population were studied in 7949 registered Normande cattle in Colombia. The pedigree was deep with 18 traced generations, but there were some incomplete genealogical information for the cattle born in the more distant past. The average number of complete and equivalent complete generations was 2.42 and 5.21, respectively. The average pedigree completeness index for five generations was 0.62, which increased over time, and a significant difference between sexes was found (males: 0.82 ± 0.11; females: 0.62 ± 0.38). The average generation interval was 7.57 years. The number of founders, effective founders, ancestors, and founder genomes were 575, 115, 47, and 22.22, respectively, which suggests that an unequal use of founders and a random loss of alleles from founders occurred over time. The level of inbreeding was 0.019 and increased to 0.023, when the inbreeding coefficient was calculated by assigning inbreeding of contemporaries to founders. These levels of inbreeding lead to an effective population size of 138.5 and 117.9 and to a 0.36% and 0.42% rate of inbreeding, respectively. Out of 267 herds with more than five registered breeding animals, only one nucleus herd was present, whereas 117 and 119 were classified as multiplier and commercial herds, respectively. About 92% of calves were sired by French bulls; but the use of Colombian bulls for breeding is increasing. The Colombian Normande breed is at an acceptable level of genetic variability, although some losses of founder alleles have occurred. As the level of inbreeding has been increasing, inbreeding and mating strategies should be monitored in order to maintain the genetic diversity of the breed. [ABSTRACT FROM AUTHOR]

Simple Summary: Dairy cow welfare has become a significant topic in recent years. Lying (down) behavior is considered a useful indicator for dairy cow health, welfare, reproductive and productive status. The study evaluated the interaction of climatic conditions on the lying behavior of a group of dairy cows. The developed model seems helpful to identify and predict this important indicator of the welfare of the herd. The prediction model developed, with automatic monitoring of cow behavior, could be a valid early warning system to identify any deviation from the expected behavior, and could be also used to evaluate the goodness of management and to evaluate the heat stress mitigation strategy. Currently, lying behavior can be assessed using continuous observations from sensors (e.g., accelerometers). The analysis of digital data deriving from accelerometers is an effective tool for studying livestock behaviors. Despite the large interest in the lying behavior of dairy cows, no reference was found in literature regarding the prediction of lying behavior as a function of the interaction of environmental parameters. The present study aimed to evaluate the influence of climatic conditions (temperature-humidity index, solar radiation, air velocity and rainfalls) on the lying behavior of a group of primiparous dairy cows, using data from accelerometers, and develop a prediction model to identify and predict the lying behavior of dairy cows as a function of the effects of environmental conditions. Results from the. GLM Procedure (SAS) showed that the model was highly significant (p < 0.001) and the r2 was 0.84. All of the effects in the model resulted in being highly significant (p < 0.001). This model, if validated properly, could be a valid early warning system to identify any deviation from the expected behavior, and to assess the effectiveness of thermal stress mitigation strategies. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) produced by pathogens, host-pathogen interactions and biochemical pathways were explored in several study studies as biomarkers for their capacity of diagnosing pathologies in livestock and in humans. VOCs are present everywhere such as in blood, breath, faeces, sweat, skin, urine and vaginal fluids and their qualitative and quantitative composition is influenced by pathophysiological responses to infections, toxins or endogenous metabolic pathway perturbations. In poultry, VOCs analysis has been explored to evaluate air quality in sheds, but they have never been monitored to determine if birds were affected by enteric pathologies. These enteric disorders represent one of the most important groups of diseases they affect poultry and cause illness, mortality and economic losses. For this reason, monitoring the health status of broilers and an early detection of any health problem is of great importance in intensive farming, especially nowadays that antibiotics are banned. Nowadays, the antibiotic as a prophylaxis in intensive farming system, is still in use and this management practice may cause spreading of drugs in the environment, contributing to the phenomenon of antibiotic resistance. The prompt reaction to any change in health, welfare and productive status is the key for the reduction in drugs usage and for the improvement of animal wellbeing. Due to the high priority of this issue, it is of great importance the early detection of any health problem in intensive farming. Precision Livestock Farming (PLF), through the combination of cheap technologies and specific algorithms, can provide valuable information for farmers starting from the huge amount of data collected in real time at farm level. This study was aimed to the application of a PLF diagnostic tool, able to detect the variation of volatile organic compounds, to promptly recognize enteric problems in intensive farming, supporting veterinarians for selecting specific treatments in case of disease. [ABSTRACT FROM AUTHOR]