Impact of the Ethanol Boom on Livestock and Dairy Industries: What Are They Going to Eat?

Increased demand for corn for ethanol production has helped push grain prices to record levels. This has increased livestock production costs, and producers have responded with changes to production systems. This paper explores the degree to which costs can be mitigated with alternative feeds, the effect this might have on physical performance, and the impact of alternative feeds on the competitive position of different species.cattle feeding, corn, cost of production, ethanol, Agribusiness, Farm Management, Livestock Production/Industries, Production Economics, Research and Development/Tech Change/Emerging Technologies, Q12, Q13,

Depth Characterization of Shallow Aquifers with Seismic Reflection, Part II—Prestack Depth Migration and Field Examples

It is common in shallow seismic studies for the compressional-wave velocity in unconsolidated sediments to increase by a factor of four or more at the transition from dry or partial water saturation to full saturation. Under these conditions, conventional NMO velocity analysis fails and leads to large depth and layer thickness estimates if the Dix equation is assumed valid. Prestack depth migration (PSDM) is a means of improving image accuracy. A comparison of PSDM with conventional NMO processing for three field examples from differing hydrogeologic environments illustrates that PSDM can significantly improve image quality and accuracy

Evaluation of the Illinois Soil Nitrogen Test in the North Central Region

Data from 96 locations across the North Central Region was complied to evaluate the usefulness of the Illinois soil nitrogen test (ISNT) in identifying fields where corn will not respond to additional N fertilizer and predicting the yield optimizing N rate (YONR) for each field. The ISNT could not accurately predict non-responsive sites, nor could it predict YONR. Sub-setting the data based on soil drainage class and previous crop did not improve the predictive capability of the ISNT. The ISNT was related to soil organic matter and was measuring a constant fraction of total soil N. The ISNT is not a meaningful tool upon which N rate decisions should be based

Phosphorus indexing for cropland: Overview and basic concepts of the Iowa phosphorus index

Excessive phosphorus (P) loss from soils impairs surface water resources. An assessment tool or index has been proposed to identify fields with high potential risk of P delivery. The P index integrates P source and transport factors into a decision making process that may lead to changes in current P management and soil conservation practices. The index recognizes that a single soil P threshold alone is not an appropriate evaluation factor because of the varying conditions across fields. Although most indices being developed in the United States include similar factors, source and transport characteristics are considered in various ways to best address the variable conditions across regions. The Iowa P index reflects conditions that predominate under grain-crop production systems, considers source factors in a multiplicative manner within three main transport mechanisms, and approximates loads of P likely to enter and become available to aquatic ecosystems. An erosional component considers sheet and rill erosion, P enrichment, total soil P, buffers, sediment delivery, distance to a stream, and the long term biotic availability of particulate P in lake ecosystems. A runoff component considers water runoff based on a modification of the runoff curve number (RCN), soil-test P (STP), rate, time, and method of P application. An internal drainage component considers the presence of tiles, water flow to tile lines, subsurface recharge from subsurface flow, and soil-test P. When the erosion risk is high, the index weighs particulate P loss heavily compared with dissolved P loss, and emphasizes long-term processes comparatively more than short-term processes. This P assessment tool helps identify alternative P and soil conservation management options for reducing total P delivery from fields to surface water resources

Statistical and machine learning methods evaluated for incorporating soil and weather into corn nitrogen recommendations

Nitrogen (N) fertilizer recommendation tools could be improved for estimating corn (Zea mays L.) N needs by incorporating site-specific soil and weather information. However, an evaluation of analytical methods is needed to determine the success of incorporating this information. The objectives of this research were to evaluate statistical and machine learning (ML) algorithms for utilizing soil and weather information for improving corn N recommendation tools. Eight algorithms [stepwise, ridge regression, least absolute shrinkage and selection operator (Lasso), elastic net regression, principal component regression (PCR), partial least squares regression (PLSR), decision tree, and random forest] were evaluated using a dataset containing measured soil and weather variables from a regional database. The performance was evaluated based on how well these algorithms predicted corn economically optimal N rates (EONR) from 49 sites in the U.S. Midwest. Multiple algorithm modeling scenarios were examined with and without adjustment for multicollinearity and inclusion of two-way interaction terms to identify the soil and weather variables that could improve three dissimilar N recommendation tools. Results showed the out-of-sample root-mean-square error (RMSE) for the decision tree and some random forest modeling scenarios were better than the stepwise or ridge regression, but not significantly different than any other algorithm. The best ML algorithm for adjusting N recommendation tools was the random forest approach (r2 increased between 0.72 and 0.84 and the RMSE decreased between 41 and 94 kg N ha−1). However, the ML algorithm that best adjusted tools while using a minimal amount of variables was the decision tree. This method was simple, needing only one or two variables (regardless of modeling scenario) and provided moderate improvement as r2 values increased between 0.15 and 0.51 and RMSE decreased between 16 and 66 kg N ha−1. Using ML algorithms to adjust N recommendation tools with soil and weather information shows promising results for better N management in the U.S. Midwest

A Framework to Manage the Complex Organisation of Collaborating: Its Application to Autonomous Systems

In this paper we present an analysis of the complexities of large group collaboration and its application to develop detailed requirements for collaboration schema for Autonomous Systems (AS). These requirements flow from our development of a framework for collaboration that provides a basis for designing, supporting and managing complex collaborative systems that can be applied and tested in various real world settings. We present the concepts of "collaborative flow" and "working as one" as descriptive expressions of what good collaborative teamwork can be in such scenarios. The paper considers the application of the framework within different scenarios and discuses the utility of the framework in modelling and supporting collaboration in complex organisational structures

Flight Team Development in Support of LCROSS - A Class D Mission

The LCROSS (Lunar Crater Observation and Sensing Satellite) project presented a number of challenges to the preparation for mission operations. A class D mission under NASA s risk tolerance scale, LCROSS was governed by a $79 million cost cap and a 29 month schedule from "authority to proceed" to flight readiness. LCROSS was NASA Ames Research Center s flagship mission in its return to spacecraft flight operations after many years of pursuing other strategic goals. As such, ARC needed to restore and update its mission support infrastructure, and in parallel, the LCROSS project had to newly define operational practices and to select and train a flight team combining experienced operators and staff from other arenas of ARC research. This paper describes the LCROSS flight team development process, which deeply involved team members in spacecraft and ground system design, implementation and test; leveraged collaborations with strategic partners; and conducted extensive testing and rehearsals that scaled in realism and complexity in coordination with ground system and spacecraft development. As a testament to the approach, LCROSS successfully met its full mission objectives, despite many in-flight challenges, with its impact on the lunar south pole on October 9, 2009

Dynamics of Hyporheic Flow and Heat Transport Across a Bed-to-Bank Continuum in a Large Regulated River

The lower Colorado River (LCR) near Austin, Texas is heavily regulated for hydropower generation. Daily water releases from a dam located 23 km upstream of our study site in the LCR caused the stage to fluctuate by more than 1.5 m about a mean depth of 1.3 m. As a result, the river switches from gaining to losing over a dam storage-release cycle, driving exchange between river water and groundwater. We assessed the hydrologic impacts of this by simultaneous temperature and head monitoring across a bed-to-bank transect. River-groundwater exchange flux is largest close to the bank and decreases away from the bank. Correspondingly, both the depth of the hyporheic zone and the exchange time are largest close to the bank. Adjacent to the bank, the streambed head response is hysteretic, with the hysteresis disappearing with distance from the bank, indicating that transient bank storage affects the magnitude and direction of vertical exchange close to the bank. Pronounced changes in streambed temperature are observed down to a meter. When the river stage is high, which coincides with when the river is coldest, downward advection of heat from a previous cycles\u27 warm-water pulse warms the streambed. When the river is at its lowest stage but warmest temperature, upwelling groundwater cools the streambed. Future research should consider and focus on a more thorough understanding of the impacts of dam regulation on the hydrologic, thermal, biogeochemical, and ecologic dynamics of rivers and their hyporheic and riparian zones

Design of high affinity cyclic pentapeptide ligands for Κ-opioid receptors

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73319/1/j.1399-3011.2005.00295.x.pd