997 resultados para ANGUS CATTLE


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In order to provide information that may help researchers to understand the main cause(s) of differences in bull fertility frequently observed in field trials, this study aimed to investigate conception rates as well as several in vitro sperm characteristics of different sires of unknown fertility utilized in a Timed-AI (TAI) program. Suckled Nelore cows submitted to the same TAI protocol were allocated into eight breeding groups of approximately 120 animals each. Frozen semen doses from three Angus bulls and three different batches from each bull were utilized. Approximately 100 doses from each batch were used in TAI. Sires, batches and AI technicians were equally distributed across breeding groups. Cows were examined for pregnancy diagnosis 40 d after TAI. For in vitro sperm analyses, the same thawing procedure was repeated in the laboratory to mimic field conditions. The following in vitro sperm characteristics were assessed: computerized motility, thermal resistance, plasma and acrosomal membrane integrity, lipid peroxidation, morphology, morphometry and chromatin structure. No effect of breeding group, body condition score, AI technician and sire was observed. However, some significant differences among bulls were detected in laboratory analyses. Semen from sire presenting numerically lower (P > 0.05) pregnancy/AI also presented lower (P < 0.05) values in all sperm characteristics analyzed in thermal resistance test at 4 h (Total Motility, Progressive Motility, Average Path Velocity, Straight-Line Velocity, Curvilinear Velocity, Amplitude of Lateral Head Displacement, Beat Cross Frequency, Straightness, Linearity, and Percentage of Rapidly Moving Cells), higher (P < 0.05) Major and Total Defects in sperm morphological test, lower (P < 0.05) Length, Ellipticity and Fourier parameter (Fourier 0) in sperm morphometric analysis as well as higher (P < 0.05) chromatin heterogeneity. It was concluded that, although no bull effect was observed in the field experiment, the sire that presented numerically lower pregnancy/AI also presented lower semen quality according to the laboratory analyses performed. (C) 2012 Elsevier B.V. All rights reserved.

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White corn was compared with yellow corn in a 180-day finishing trial with 600 lb. Angus steers fed 90% concentrate diets. Steers fed yellow corn consumed 3.3% less feed and were 3.8% more efficient in feed utilization. Rate of gain and carcass characteristics were similar for steers fed white or yellow corn. The color of subcutaneous fat over the ribs was significantly whiter from carcasses of steers fed white corn compared with those fed yellow corn. The results of this study indicate that white corn may be used instead of barley to produce whiter fat in beef carcasses.

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Six steers (3/4 Charolaisx1/4 Brahman) (mean body weight 314 +/- 27 kg) and six spayed heifers (3/5 Shorthornx2/5 Red Angus) (mean body weight 478 +/- 30 kg) were used to determine the effects of climatic conditions and hormone growth promotants (HGP) on respiration rate (RR; breaths/min), pulse rate (beats/min), rectal temperature (RT; degrees C), and heat production (HP; kJ). Cattle were exposed to the following climatic conditions prior to implantation with a HGP and then again 12 days after implantation: 2 days of thermoneutral conditions (TNL) [21.9 +/- 0.9 degrees C ambient temperature (T-A) and 61.7 +/- 22.1% relative humidity (RH)] then 2 days of hot conditions [HOT; 29.2 +/- 4 degrees C (T-A) and 78.3 +/- 13.2% (RH)], then TNL for 3 days and then 2 days of cold conditions [COLD; 17.6 +/- 0.9 degrees C (T-A) and 63.4 +/- 1.8% (RH); cattle were wet during this treatment]. The HGP implants used were: estrogenic implant (E), trenbolone acetate implant (TBA), or both (ET). Both prior to and following administration of HGP, RRs were lower (P < 0.05) on cold days and greater (P < 0.05) on hot days compared to TNL. On hot days, RTs, were 0.62 degrees C higher after compared to before implanting. Across all conditions, RTs were > 0.5 degrees C greater (P < 0.05) for E cattle than for TBA or ET cattle. On cold days, RTs of steers were > 0.8 degrees C higher than for the heifers, while under TNL and HOT, RTs of steers were 0.2-0.35 degrees C higher than those of heifers. Prior to implantation, HP per hour and per unit of metabolic body weight was higher (P < 0.05) for cattle exposed to hot conditions, when compared to HP on cold days. After implantation, HP was greater (P < 0.05) on hot days than on cold days. Under TNL, ET cattle had the lowest HP and greatest feed intake. On hot days, E cattle had the lowest HP, and the highest RT; therefore, if the potential exists for cattle death from heat episodes, the use of either TBA or ET may be preferred. Under cold conditions HP was similar among implant groups.

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Eighteen Angus steers exposed to high heat load conditions were used to assess the effectiveness of four spray cooling systems, on reducing the effects of heat load, the impact on microclimate and water usage. The steers were housed in groups of nine in a fully enclosed shed and were exposed to high heat load conditions for four days. The cooling systems used were water applied via a hose, via overhead sprinklers, via sprinklers at leg height and via misters. The water used was approximately 31 oC and contained 3% NaCl. Fans were used to ensure adequate air movement over the cattle. The animal parameters measured were feed intake, respiration rate, panting score and behaviour. Climatic factors were ambient temperature and wet bulb temperature. Ammonia levels were also measured. The hose, overhead sprinklers and misting were successful in reducing heat load on the cattle. The leg wetting system did not work because the dominant cattle blocked access to the sprinklers. The misting system used the most water (5483 L) and the hose the least (845 L). The application of water had minor impacts on wet bulb temperature, but resulted in significant reductions in dry bulb temperatures.

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Beef constitutes a main component of the American diet and still represent the principal source of protein in many parts of the world. Currently, the meat market is experiencing an important transformation; consumers are increasingly switching from consuming traditional beef to grass-fed beef. People recognized products obtained from grass-fed animals as more natural and healthy. However, the true variations between these two production systems regarding various aspects remain unclear. This dissertation provides information from closely genetically related animals, in order to decrease confounding factors, to explain several confused divergences between grain-fed and grass-fed beef. First, we examined the growth curve, important economic traits and quality carcass characteristics over four consecutive years in grain-fed and grass-fed animals, generating valuable information for management decisions and economic evaluation for grass-fed cattle operations. Second, we performed the first integrated transcriptomic and metabolomic analysis in grass-fed beef, detecting alterations in glucose metabolism, divergences in free fatty acids and carnitine conjugated lipid levels, and altered β-oxidation. Results suggest that grass finished beef could possibly benefit consumer health from having lower total fat content and better lipid profile than grain-fed beef. Regarding animal welfare, grass-fed animals may experience less stress than grain-fed individuals as well. Finally, we contrasted the genome-wide DNA methylation of grass-fed beef against grain-fed beef using the methyl-CpG binding domain sequencing (MBD-Seq) method, identifying 60 differentially methylated regions (DMRs). Most of DMRs were located inside or upstream of genes and displayed increased levels of methylation in grass-fed individuals, implying a global DNA methylation increment in this group. Interestingly, chromosome 14, which has been associated with large effects on ADG, marbling, back fat, ribeye area and hot carcass weight in beef cattle, allocated the largest number of DMRs (12/60). The pathway analysis identified skeletal and muscular system as the preeminent physiological system and function, and recognized carbohydrates metabolism, lipid metabolism and tissue morphology among the highest ranked networks. Therefore, although we recognize some limitations and assume that additional examination is still required, this project provides the first integrative genomic, epigenetic and metabolomics characterization of beef produced under grass-fed regimen.

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The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

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Managing livestock movement in extensive systems has environmental and production benefits. Currently permanent wire fencing is used to control cattle; this is both expensive and inflexible. Cattle are known to respond to auditory and visual cues and we investigated whether these can be used to manipulate their behaviour. Twenty-five Belmont Red steers with a mean live weight of 270kg were each randomly assigned to one of five treatments. Treatments consisted of a combination of cues (audio, tactile and visual stimuli) and consequence (electrical stimulation). The treatments were electrical stimulation alone, audio plus electrical stimulation, vibration plus electrical stimulation, light plus electrical stimulation and electrified electric fence (6kV) plus electrical stimulation. Cue stimuli were administered for 3s followed immediately by electrical stimulation (consequence) of 1kV for 1s. The experiment tested the operational efficacy of an on-animal control or virtual fencing system. A collar-halter device was designed to carry the electronics, batteries and equipment providing the stimuli, including audio, vibration, light and electrical of a prototype virtual fencing device. Cattle were allowed to travel along a 40m alley to a group of peers and feed while their rate of travel and response to the stimuli were recorded. The prototype virtual fencing system was successful in modifying the behaviour of the cattle. The rate of travel of cattle along the alley demonstrated the large variability in behavioural response associated with tactile, visual and audible cues. The experiment demonstrated virtual fencing has potential for controlling cattle in extensive grazing systems. However, larger numbers of cattle need to be tested to derive a better understanding of the behavioural variance. Further controlled experimental work is also necessary to quantify the interaction between cues, consequences and cattle learning.

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We consider the problem of monitoring and controlling the position of herd animals, and view animals as networked agents with natural mobility but not strictly controllable. By exploiting knowledge of individual and herd behavior we would like to apply a vast body of theory in robotics and motion planning to achieving the constrained motion of a herd. In this paper we describe the concept of a virtual fence which applies a stimulus to an animal as a function of its pose with respect to the fenceline. Multiple fence lines can define a region, and the fences can be static or dynamic. The fence algorithm is implemented by a small position-aware computer device worn by the animal, which we refer to as a Smart Collar.We describe a herd-animal simulator, the Smart Collar hardware and algorithms for tracking and controlling animals as well as the results of on-farm experiments with up to ten Smart Collars.

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Virtual fencing has the potential to control grazing livestock. Understanding and refi ning the cues that can alter behaviour is an integral part of autonomous animal control. A series of tests have been completed to explore the relationship between temperament and control. Prior to exposure to virtual fencing control the animals were scored for temperament using fl ight speed and a sociability index using contact logging devices. The behavioural response of 30, Belmont Red steers were observed for behavioural changes when presented with cues prior to receiving an electrical stimulation. A control and four treatments designed to interrupt the animal’s movement down an alley were tested. The treatments consisted of sound plus electrical stimulation, vibration plus electrical stimulation, a visual cue plus electrical stimulation and electrical stimulation by itself. The treatments were randomly applied to each animal over fi ve consecutive trials. A control treatment in which no cues were applied was used to establish a basal behavioural pattern. A trial was considered completed after each animal had been retained behind the cue barrier for at least 60 sec. All cues and electrical stimulation were manually applied from a laptop located on a portable 3.5 m tower located immediately outside the alley. The electric stimulation consisted of 1.0 Kv of electricity. Electric stimulation, sound and vibration along with the Global Position System (GPS) hardware to autonomously record the animal’s path within the alley were recorded every second.

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ElectricCOW is a network, animal behaviour and agent simulator designed to allow detailed simulation of an ad-hoc model network built from small mote-like devices called flecks. Detailed radio communications, cattle behaviour and sensor and actuator network modelling allows a closed-loop environment, where the network can influence the behaviour of its mobile platforms.