Proceedings

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Sawyer, J
Stanley, J
Scanlan, C
Silveira, R.R
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Authors
Cosby, A.M
Falzon, G
Trotter, M
Stanley, J
Powell, K
Schneider, D
Lamb, D
Ransom, C.J
Bean, M
Kitchen, N
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Evans, F.H
Andrew, J
Scanlan, C
Cook, S
Kitchen, N.R
Yost, M.A
Ransom, C.J
Bean, G
Camberato, J
Carter, P
Ferguson, R
Fernandez, F
Franzen, D
Laboski, C
Nafziger, E
Sawyer, J
de Azevedo, K.K
de Figueiredo, D.M
de Sousa, M.G
Dallago, G.M
Silveira, R.R
da Silva, L.D
Santos, R.A
de Azevedo, K.K
Figueiredo, D.M
de Sousa, M.G
Dallago, G.M
Silveira, R.R
da Silva, L.D
Rennó, L.N
Santos, R.A
de Azevedo, K.K
Figueiredo, D.M
Dallago, G.M
Vieira, J.A
Silveira, R.R
da Silva, L.D
Santos, R.A
Rennó, L.N
Pacheco, G.B
Topics
Precision Crop Protection
Sensor Application in Managing In-season Crop Variability
Site-Specific Nutrient, Lime and Seed Management
In-Season Nitrogen Management
Farm Animals Health and Welfare Monitoring
Type
Poster
Oral
Year
2014
2016
2018
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Authors

Filter results7 paper(s) found.

1. Using A Decision Tree To Predict The Population Density Of Redheaded Cockchafer (Adoryphorus Couloni) In Dairy Fields

A native soil dwelling insect pest, the redheaded cockchafer (Adoryphorus couloni) (Burmeister) (RHC) is an important pest in the higher rainfall regions of south-eastern Australia. Due to the majority of its lifecycle spent underground feeding on the roots and soil organic matter the redheaded cockchafer is difficult to detect and control. The ability to predict the level of infestation and location of redheaded cockchafers in a field may give producers the option to use an endophyte containing... A. Cosby, G. Falzon, M. Trotter, J. Stanley, K. Powell, D. Schneider, D. Lamb

2. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor Algorithm

Nitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

3. Modifying Agro-Economic Models to Predict Effects of Spatially Varying Nitrogen on Wheat Yields for a Farm in Western Australia

Agricultural research in broadacre farming in Western Australia has a strong history, resulting in a significant public resource of knowledge about biophysical processes affecting crop performance. However, translation of this knowledge into improved on-farm decision making remains a challenge to the industry. Online and mobile decision support tools to assist tactical farm management decisions are not widely adopted, for reasons including: (1) they take too much time and training to learn; and... F.H. Evans, J. Andrew, C. Scanlan, S. Cook

4. Evaluation of Nutrient Intake in Sheep Fed with Increasing Levels of Crambe Meal (Crambe Abyssinica Hoscht)

The objective of this study was to evaluate the effects of increasing levels of crude protein (CP) substitution of the concentrate by CP of crambe meal (CM) (0, 25, 50 and 75% dry matter basis) on consumption of nutrients. Four rumen fistulated and castrated sheep (18 months old on average and initial body weight of 50 kg) were used distributed in a 4 x 4 Latin square design with 4 treatments and 4 experimental periods (repetitions). Diets were balanced to meet requirements for minimum gains of... K.K. De azevedo, D.M. De figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, R.A. Santos

5. Levels of Inclusion of Crambe Meal (Crambe Abyssinica Hochst) in Sheep Diet on the Balance of Nitrogen and Ureic Nitrogen in the Blood Serum

Crambe meal, which is a co-product of biodiesel production, is a potential substitute for conventional protein sources in ruminant diets. The objective of this study was to evaluate the effect of the substitution of crude protein of the concentrate by crude protein of crambe meal with increasing levels (0, 25, 50, and 75%) on nitrogen balance and blood plasma urea nitrogen concentration in sheep. Four male sheep, rumen fistulated, were placed in metabolic crates and distributed in a 4 x 4 Latin... K.K. De azevedo, D.M. Figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, L.N. Rennó, R.A. Santos

6. Efficiency of Microbial Synthesis and the Flow of Nitrogen Compounds in Sheep Receiving Crambe Meal (Crambe Abyssinica Hochst) Replacing the Concentrade Crude Protein

The objective of this study was to evaluate the effect of increasing levels (0, 25, 50, 75%) of crude protein substitution of the concentrate by crude protein of crambe meal on microbial protein synthesis and the flow of microbial nitrogen compounds in sheep. Four rumen fistulated sheep (18 months and initial average body weight of 50 kg) were distributed in a 4 x 4 Latin square design. Diets were balanced to meet the requirements for minimum gains, containing approximately 14% crude protein and... K.K. De azevedo, D.M. Figueiredo, G.M. Dallago, J.A. Vieira, R.R. Silveira, L.D. Da silva, R.A. Santos, L.N. Rennó, G.B. Pacheco

7. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer Response

Improving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer