923 resultados para BEEF-CATTLE


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Animal science newsletter about Johne's Disease in cattle. Statistics, treatments, information about the disease itself and more.

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Animal science newsletter about Johne's Disease in cattle. Statistics, treatments, information about the disease itself and more.

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The Rangeland Journal – Climate Clever Beef special issue examines options for the beef industry in northern Australia to contribute to the reduction in global greenhouse gas (GHG) emissions and to engage in the carbon economy. Relative to its gross value (A$5 billion), the northern beef industry is responsible for a sizable proportion of national reportable GHG emissions (8–10%) through enteric methane, savanna burning, vegetation clearing and land degradation. The industry occupies large areas of land and has the potential to impact the carbon cycle by sequestering carbon or reducing carbon loss. Furthermore, much of the industry is currently not achieving its productivity potential, which suggests that there are opportunities to improve the emissions intensity of beef production. Improving the industry’s GHG emissions performance is important for its environmental reputation and may benefit individual businesses through improved production efficiency and revenue from the carbon economy. The Climate Clever Beef initiative collaborated with beef businesses in six regions across northern Australia to better understand the links between GHG emissions and carbon stocks, land condition, herd productivity and profitability. The current performance of businesses was measured and alternate management options were identified and evaluated. Opportunities to participate in the carbon economy through the Australian Government’s Emissions Reduction Fund (ERF) were also assessed. The initiative achieved significant producer engagement and collaboration resulting in practice change by 78 people from 35 businesses, managing more than 1 272 000 ha and 132 000 cattle. Carbon farming opportunities were identified that could improve both business performance and emissions intensity. However, these opportunities were not without significant risks, trade-offs and limitations particularly in relation to business scale, and uncertainty in carbon price and the response of soil and vegetation carbon sequestration to management. This paper discusses opportunities for reducing emissions, improving emission intensity and carbon sequestration, and outlines the approach taken to achieve beef business engagement and practice change. The paper concludes with some considerations for policy makers.

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Approximately 5% of Australian national greenhouse gas (GHG) emissions are derived from the northern beef industry. Improving the reproductive performance of cows has been identified as a key target for increasing profitability, and this higher efficiency is also likely to reduce the GHG emissions intensity of beef production. The effects of strategies to increase the fertility of breeding herds and earlier joining of heifers as yearlings were studied on two properties at Longreach and Boulia in western Queensland. The beef production, GHG emissions, emissions intensity and profitability were investigated and compared with typical management in the two regions. Overall weaning rates achieved on the two properties were 79% and 74% compared with typical herd weaning rates of 58% in both regions. Herds with high reproductive performance had GHG emissions intensities (t CO2-e t–1 liveweight sold) 28% and 22% lower than the typical herds at Longreach and Boulia, with most of the benefit from higher weaning rates. Farm gross margin analysis showed that it was more profitable, by $62 000 at Longreach and $38 000 at Boulia, to utilise higher reproductive performance to increase the amount of liveweight sold with the same number of adult equivalents compared with reducing the number of adult equivalents to maintain the same level of liveweight sold and claiming a carbon credit for lower farm emissions. These gains achieved at two case study properties which had different rainfall, country types, and property sizes suggest similar improvements can be made on-farm across the Mitchell Grass Downs bioregion of northern Australia.

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This paper explores the effect of using regional data for livestock attributes on estimation of greenhouse gas (GHG) emissions for the northern beef industry in Australia, compared with using state/territory-wide values, as currently used in Australia’s national GHG inventory report. Regional GHG emissions associated with beef production are reported for 21 defined agricultural statistical regions within state/territory jurisdictions. A management scenario for reduced emissions that could qualify as an Emissions Reduction Fund (ERF) project was used to illustrate the effect of regional level model parameters on estimated abatement levels. Using regional parameters, instead of state level parameters, for liveweight (LW), LW gain and proportion of cows lactating and an expanded number of livestock classes, gives a 5.2% reduction in estimated emissions (range +12% to –34% across regions). Estimated GHG emissions intensity (emissions per kilogram of LW sold) varied across the regions by up to 2.5-fold, ranging from 10.5 kg CO2-e kg–1 LW sold for Darling Downs, Queensland, through to 25.8 kg CO2-e kg–1 LW sold for the Pindan and North Kimberley, Western Australia. This range was driven by differences in production efficiency, reproduction rate, growth rate and survival. This suggests that some regions in northern Australia are likely to have substantial opportunities for GHG abatement and higher livestock income. However, this must be coupled with the availability of management activities that can be implemented to improve production efficiency; wet season phosphorus (P) supplementation being one such practice. An ERF case study comparison showed that P supplementation of a typical-sized herd produced an estimated reduction of 622 t CO2-e year–1, or 7%, compared with a non-P supplemented herd. However, the different model parameters used by the National Inventory Report and ERF project means that there was an anomaly between the herd emissions for project cattle excised from the national accounts (13 479 t CO2-e year–1) and the baseline herd emissions estimated for the ERF project (8 896 t CO2-e year–1) before P supplementation was implemented. Regionalising livestock model parameters in both ERF projects and the national accounts offers the attraction of being able to more easily and accurately reflect emissions savings from this type of emissions reduction project in Australia’s national GHG accounts.

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A bio-economic modelling framework (GRASP-ENTERPRISE) was used to assess the implications of retaining woody regrowth for carbon sequestration on a case study beef grazing property in northern Australia. Five carbon farming scenarios, ranging from 0% to 100% of the property regrowth retained for carbon sequestration, were simulated over a 20-year period (1993–2012). Dedicating regrowth on the property for carbon sequestration reduced pasture (up to 40%) and herd productivity (up to 20%), and resulted in financial losses (up to 24% reduction in total gross margin). A net carbon income (income after grazing management expenses are removed) of $2–4 per t CO2-e was required to offset economic losses of retaining regrowth on a moderately productive (~8 ha adult equivalent–1) property where income was from the sale of weaners. A higher opportunity cost ($ t–1 CO2-e) of retaining woody regrowth is likely for feeder steer or finishing operations, with improved cattle prices, and where the substantial transaction and reporting costs are included. Although uncertainty remains around the price received for carbon farming activities, this study demonstrated that a conservatively stocked breeding operation can achieve positive production, environmental and economic outcomes, including net carbon stock. This study was based on a beef enterprise in central Queensland’s grazing lands, however, the approach and learnings are expected to be applicable across northern Australia where regrowth is present.

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BACKGROUND Despite great effort and investment incurred over decades to control bovine tuberculosis (bTB), it is still one of the most important zoonotic diseases in many areas of the world. Test-and-slaughter strategies, the basis of most bTB eradication programs carried out worldwide, have demonstrated its usefulness in the control of the disease. However, in certain countries, eradication has not been achieved due in part to limitations of currently available diagnostic tests. In this study, results of in-vivo and post-mortem diagnostic tests performed on 3,614 animals from 152 bTB-infected cattle herds (beef, dairy, and bullfighting) detected in 2007-2010 in the region of Castilla y León, Spain, were analyzed to identify factors associated with positive bacteriological results in cattle that were non-reactors to the single intradermal tuberculin test, to the interferon-gamma (IFN-γ) assay, or to both tests applied in parallel (Test negative/Culture + animals, T-/C+). The association of individual factors (age, productive type, and number of herd-tests performed since the disclosure of the outbreak) with the bacteriology outcome (positive/negative) was analyzed using a mixed multivariate logistic regression model. RESULTS The proportion of non-reactors with a positive post-mortem result ranged from 24.3% in the case of the SIT test to 12.9% (IFN-γ with 0.05 threshold) and 11.9% (95% CI 9.9-11.4%) using both tests in parallel. Older (>4.5 years) and bullfighting cattle were associated with increased odds of confirmed bTB infection by bacteriology, whereas dairy cattle showed a significantly lower risk. Ancillary use of IFN-γ assay reduced the proportion of T-/C + animals in high risk groups. CONCLUSIONS These results demonstrate the likelihood of positive bacteriological results in non-reactor cattle is influenced by individual epidemiological factors of tested animals. Increased surveillance on non-reactors with an increased probability of being false negative could be helpful to avoid bTB persistence, particularly in chronically infected herds. These findings may aid in the development of effective strategies for eradication of bTB in Spain.

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Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina1 High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing 6.5% of the genome. Comparing our results with previous studies revealed an overlap in 1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.

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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.

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In Australia rural research and development corporations and companies expended over $AUS500 million on agricultural research and development. A substantial proportion of this is invested in R&D in the beef industry. The Australian beef industry exports almost $AUS5billionof product annually and invest heavily in new product development to improve the beef quality and improve production efficiency. Review points are critical for effective new product development, yet many research and development bodies, particularly publicly funded ones, appear to ignore the importance of assessing products prior to their release. Significant sums of money are invested in developing technological innovations that have low levels and rates of adoption. The adoption rates could be improved if the developers were more focused on technology uptake and less focused on proving their technologies can be applied in practice. Several approaches have been put forward in an effort to improve rates of adoption into operational settings. This paper presents a study of key technological innovations in the Australian beef industry to assess the use of multiple criteria in evaluating the potential uptake of new technologies. Findings indicate that using multiple criteria to evaluate innovations before commercializing a technology enables researchers to better understand the issues that may inhibit adoption.