Effect of concentrate feeding level in winter and turnout date to pasture in spring on biological and economical performance of weanling cattle in suckler beef production systems

peer-reviewedThree experiments were carried out to determine the effects of supplementary concentrate feeding level (Low, LC; High, HC) to grass silage and/or turnout date to pasture in spring (Early, ET; Late, LT) for a second grazing season on performance to slaughter of spring-born, weaned beef calves (n = 188). Experiment 1 comprised of two concentrate levels (0.5 and 1.5 kg/day). Experiment 2 comprised of two turnout dates (19 March, 9 April). Experiment 3 comprised of two concentrate levels (0.5 kg and 2.0 kg/day) and two turnout dates (22 March, 12 April). In Experiment 1, live-weight gain during the indoor winter period was 25 kg higher (P 0.05) total live-weight gain for both treatments. In Experiment 2, live weight at turnout to pasture was 11 kg lower (P 0.05), subsequently. In Experiments 1 and 2, live-weight gain during the finishing period and carcass weight, conformation and fat scores did not differ (P > 0.05) between the treatments. In Experiment 3, at turnout to pasture, HC were 35 kg heavier (P < 0.001) than LC, and ET were 12 kg lighter (P < 0.05) than LT, whereas 8 days after late turnout, ET were 13 kg heavier (P < 0.05) than LT. There was a concentrate level × turnout date interaction (P < 0.05) for live weight at the end of the grazing season, whereby the LC, LT treatment were lighter than the other treatments, which did not differ. Live weight at slaughter and carcass weight did not differ (P > 0.05) between the concentrate levels, whereas they were higher (P < 0.05) for ET than LT. Economic and stochastic analysis of Experiment 3 indicated that, in the context of whole-farm systems, (i) feeding HC was dependent on date of sale such that only where progeny were sold at the start of the second grazing season, net farm margin (NFM) was increased, (ii) ET only increased NFM where progeny were retained through to finish and, (iii) taking progeny through to finish was more profitable than selling earlier in the animals’ lifetime. In conclusion, subsequent compensatory growth at pasture diminishes the growth and economic advantage from concentrate supplementation or early turnout to pasture, of young late-maturing cattle

How Can Medicare Lead Delivery System Reform?

Explores options and design issues for reforming the fee-for-service payment system to encourage better, more efficient health care through greater accountability for specific populations and totality of care. Proposes a Medicare demonstration program

Delivery System Reform Tracking: A Framework for Understanding Change

Proposes a framework for tracking progress on delivery system reforms such as patient-centered medical homes and accountable care organizations by assessing structures, capabilities, incentives, and outcomes. Outlines challenges for data collection

Global optimization of data quality checks on 2‐D and 3‐D networks of GPR cross‐well tomographic data for automatic correction of unknown well deviations

Significant errors related to poor time zero estimation, well deviation or mislocation of the transmitter (TX) and receiver (RX) stations can render even the most sophisticated modeling and inversion routine useless. Previous examples of methods for the analysis and correction of data errors in geophysical tomography include the works of Maurer and Green (1997), Squires et al. (1992) and Peterson (2001). Here we follow the analysis and techniques of Peterson (2001) for data quality control and error correction. Through our data acquisition and quality control procedures we have very accurate control on the surface locations of wells, the travel distance of both the transmitter and receiver within the boreholes, and the change in apparent zero time. However, we often have poor control on well deviations, either because of economic constraints or the nature of the borehole itself prevented the acquisition of well deviation logs. Also, well deviation logs can sometimes have significant errors. Problems with borehole deviations can be diagnosed prior to inversion of travel-time tomography data sets by plotting the apparent velocity of a straight ray connecting a transmitter (TX) to a receiver (RX) against the take-off angle of the ray. Issues with the time-zero pick or distances between wells appear as symmetric smiles or frown in these QC plots. Well deviation or dipping-strong anisotropy will result in an asymmetric correlation between apparent velocity and take-off angle (Figure 1-B). In addition, when a network of interconnected GPR tomography data is available, one has the additional quality constraint of insuring that there is continuity in velocity between immediately adjacent tomograms. A sudden shift in the mean velocity indicates that either position deviations are present or there is a shift in the pick times. Small errors in well geometry may be effectively treated during inversion by including weighting, or relaxation, parameters into the inversion (e.g. Bautu et al., 2006). In the technique of algebraic reconstruction tomography (ART), which is used herein for the travel time inversion (Peterson et al., 1985), a small relaxation parameter will smooth imaging artifacts caused by data errors at the expense of resolution and contrast (Figure 2). However, large data errors such as unaccounted well deviations cannot be adequately suppressed through inversion weighting schemes. Previously, problems with tomograms were treated manually. However, in large data sets and/or networks of data sets, trial and error changes to well geometries become increasingly difficult and ineffective. Mislocation of the transmitter and receiver stations of GPR cross-well tomography data sets can lead to serious imaging artifacts if not accounted for prior to inversion. Previously, problems with tomograms have been treated manually prior to inversion. In large data sets and/or networks of tomographic data sets, trial and error changes to well geometries become increasingly difficult and ineffective. Our approach is to use cross-well data quality checks and a simplified model of borehole deviation with particle swarm optimization (PSO) to automatically correct for source and receiver locations prior to tomographic inversion. We present a simple model of well deviation, which is designed to minimize potential corruption of actual data trends. We also provide quantitative quality control measures based on minimizing correlations between take-off angle and apparent velocity, and a quality check on the continuity of velocity between adjacent wells. This methodology is shown to be accurate and robust for simple 2-D synthetic test cases. Plus, we demonstrate the method on actual field data where it is compared to deviation logs. This study shows the promise for automatic correction of well deviations in GPR tomographic data. Analysis of synthetic data shows that very precise estimates of well deviation can be made for small deviations, even in the presence of static data errors. However, the analysis of the synthetic data and the application of the method to a large network of field data show that the technique is sensitive to data errors varying between neighboring tomograms

Coordinated field study for CaPE: Analysis of energy and water budgets

The objectives of this hydrologic cycle study are to understand and model (1) surface energy and land-atmosphere water transfer processes, and (2) interactions between convective storms and surface energy fluxes. A surface energy budget measurement campaign was carried out by an interdisciplinary science team during the period July 8 - August 19, 1991 as part of the Convection and Precipitation/Electrification Experiment (CaPE) in the vicinity of Cape Canaveral, FL. Among the research themes associated with CaPE is the remote estimation of rainfall. Thus, in addition to surface radiation and energy budget measurements, surface mesonet, special radiosonde, precipitation, high-resolution satellite (SPOT) data, geosynchronous (GOES) and polar orbiting (DMSP SSM/I, OLS; NOAA AVHRR) satellite data, and high altitude airplane data (AMPR, MAMS, HIS) were collected. Initial quality control of the seven surface flux station data sets has begun. Ancillary data sets are being collected and assembled for analysis. Browsing of GOES and radar data has begun to classify days as disturbed/undisturbed to identify the larger scale forcing of the pre-convective environment, convection storms and precipitation. The science analysis plan has been finalized and tasks assigned to various investigators