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Clay, D.E
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Authors
Clay, D.E
Carlson, G
Tatge, J
Reese, C.L
Clay, D.E
Beck, D.L
Clay, S.A
Long, D.S
Shahinian, M
Erickson, B
Clay, D.E
Clay, S.A
Fausti, S
Morris, T
Tremblay, N
Kyveryga, P.M
Clay, D.E
Murrell, S
Ciampitti, I
Thompson, L
Mueller, D
Seger, J
Thies, S
Clay, D.E
Bruggeman, S
Joshi, D
Clay, S
Miller, J
Gardezi, M
Walsh, O
Joshi, D
Kumari, S
Clay, D.E
Rathore, J
Topics
Precision Carbon Management
Remote Sensing Applications in Precision Agriculture
Agricultural Education
Standards & Data Stewardship
Precision Agriculture and Global Food Security
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2010
2016
2018
2024
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Authors

Filter results6 paper(s) found.

1. Soil Organic Carbon Maintenance Requiremnets And Mineralizatyion Rate Constants: Site Specific Calcuations

  Over the past 100 years numerous studies have been conducted with the goal of quantifying the impact of management on carbon turnover. It is difficult to conduct a mechanistic evaluation of these studies because each study was conducted under unique soil, climatic, and management conditions.  Techniques for directly comparing data from unique studies are needed. This study discusses techniques for comparing data collected... D.E. Clay, G. Carlson, J. Tatge

2. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy Reflectance

  Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian

3. Knowledge, Skills and Abilities Needed in the Precision Ag Workforce: an Industry Survey

Precision agriculture encompasses a set of related technologies aimed at better utilization of crop inputs, increasing yield and quality, reducing risks, and enabling information flow throughout the crop supply and end-use chains.  The most widely adopted precision practices have been automated systems related to equipment steering and precise input application, such as autoguidance and section controllers.  Once installed, these systems are relatively easy for farmers and their supporting... B. Erickson, D.E. Clay, S.A. Clay, S. Fausti

4. Rationale for and Benefits of a Community for On-Farm Data Sharing

Most data sets for evaluating crop production practices have too few locations and years to create reliable probabilities from predictive analytical analyses for the success of the practices. Yield monitors on combines have the potential to enable networks of farmers in collaboration with scientists and farm advisors to collect sufficient data for calculation of more reliable guidelines for crop production showing the probabilities that new or existing practices will improve the efficiency of... T. Morris, N. Tremblay, P.M. Kyveryga, D.E. Clay, S. Murrell, I. Ciampitti, L. Thompson, D. Mueller, J. Seger

5. Precision Fall Urea Fertilizer Applications: Timing Impact on Carbon Dioxide, Ammonia Volatilization and Nitrous Oxide Emissions

To minimize ammonia (NH3) volatilization and nitrous oxide (N2O) emissions from fall applied fertilizer, it is generally recommended to not apply the fertilizer until the soil temperature decreases below 10 C. However, this recommendation is not based on detailed measurements of NH3and N2O emissions. The objective of this study was to determine the influence of fertilizer application timing on nitrous oxide, carbon dioxide, and ammonia volatilization emissions.  Nitrogen fertilizer was... S. Thies, D.E. Clay, S. Bruggeman, D. Joshi, S. Clay, J. Miller

6. Predicting Soybean Yield Using Remote Sensing and a Machine Learning Model

Soybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore