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Srinivasa Rao, C
Dong, Y
Nowatzki, J
Kyveryga, P.M
Allphin, E
Albrigo, L.G
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Authors
Srinivasa Rao, C
Rao, K
Magen, H
Venkateswarlu, B
Subba Rao, A
Ashley, R
Nowatzki, J
Blackmer, T.M
Kyveryga, P.M
Kyveryga, P.M
Blackmer, T.M
Kyveryga, P.M
Blackmer, T.M
Reeg, P.R
Blackmer, T.M
Kyveryga, P.M
Kyveryga, P.M
Blackmer, T.M
Pearson , R
Blackmer, T.M
Kyveryga, P.M
Allphin, E
Kitchen, N.R
Suddeth, K.A
Thompson, A
Nowatzki, J
Brase, T
Lee, W
Kumar, A
Ehsani, R
Yang, C
Albrigo, L.G
Dong, Y
Wang, Y
Song, X
Gu, X
Reeg, P
Kyveryga, P.M
Mueller, T.A
Sivarajan, S
Bajwa, S
Nowatzki, J
Bajwa, S
Nowatzki, J
Harnisch, W
Schatz, B
Anderson, V
Thompson, A
Boardman, D.L
Kitchen, N
Allphin, E
Nowatzki, J
Bajwa, S
Sivarajan, S
Maharlooei, M
Kandel, H
Shirzadi, A
Maharlooei, M
hassanijalilian, O
Bajwa, S
Howatt, K
Sivarajan, S
Nowatzki, J
Kyveryga, P.M
Pritsolas, J
Connor, J
Pearson, R
Nowatzki, J
Bajwa, S
Roberts, D
Ossowski, M
Scheve, A
Johnson, A
Chaplin, Y
Kyveryga, P.M
Fey, S
Connor, J
Kiel, A
Muth, D
Maharlooei, M
Bajwa, S
Mireei, S.A
Shirzadi, A
Sivarajan, S
Berti, M
Nowatzki, J
Morris, T
Tremblay, N
Kyveryga, P.M
Clay, D.E
Murrell, S
Ciampitti, I
Thompson, L
Mueller, D
Seger, J
Rasmussen, P
Nowatzki, J
Topics
Precision Nutrient Management
Information Management and Traceability
Precision Crop Protection
Spatial Variability in Crop, Soil and Natural Resources
Precision A-Z for Practitioners
Spatial Variability in Crop, Soil and Natural Resources
eXtension: Precision Agriculture on the Internet
Precision Horticulture
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Precision Conservation Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Sensor Application in Managing In-season CropVariability
Remote Sensing Applications in Precision Agriculture
Unmanned Aerial Systems
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Standards & Data Stewardship
Education and Training in Precision Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
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Authors

Filter results24 paper(s) found.

1. Using Late-season Uncalibrated Digital Aerial Imagery For Predicting Corn Nitrogen Status Within Fields

Using uncalibrated digital aerial imagery (DAI) for diagnosing in-season nitrogen (N) deficiencies of corn (Zea mays L.) is challenging because of the dynamic nature of corn growth and the difficulty of obtaining timely imagery. Digital aerial imagery taken later during the growing season is more accurate in identifying areas deficient in N. Even so, the quantitative use of late-season DAI across many fields is still limited because the imagery is not truly calibrated. This study... P.M. Kyveryga, T.M. Blackmer, R. Pearson

2. A Systematic Approach For Using Precision Agriculture Tools For On-farm Evaluations In Iowa

 The competitive nature of modern agriculture requires constant refinements of many crop production management decisions. Precision agriculture tools (PAT) can allow growers to rapidly evaluate different management practices across large areas at a relatively low cost. But a systematic approach and a decision-making process describing how to utilize different PAT for on-farm evaluations have not been yet developed and adopted. This presentation will focus on how  approximately... T.M. Blackmer, P.M. Kyveryga

3. Nitrogen Loss In Corn Production Varies As A Function Of Topsoil Depth

  Understanding availability and loss potential of nitrogen for varying topsoil depths of poorly-drained claypan soil landscapes could help producers make improve decisions when managing crops for feed grain or bio-fuels.  While it has been well documented that topsoil depth on these soils plays an important role in storing water for crop growth, it is not well known how this same soil... E. Allphin, N.R. Kitchen, K.A. Suddeth, A. Thompson

4. Extension: Precision Ariculture On The Internet

This session will include an overall description of the new eXtension precision agriculture Web site. eXtension is an interactive learning environment delivering the best, most researched knowledge from land-grant university  across America. Session participants will learn about the Website, and how to participate in the continued site development. The precision agriculture eXtension Web site is a virtual platform for engagement... J. Nowatzki, T. Brase

5. Citrus Greening Disease Detection Using Airborne Multispectral And Hyperspectral Imaging

Citrus greening disease (Huanglongbing or HLB) has become a major catastrophic disease in Florida’s $9 billion citrus industry since 2005, and continued to be spread to other parts of the U.S. There is no known cure for this disease. As of October 2009, citrus trees in 2,702 different sections (square mile) in 34 counties were infected in Florida. A set of hyperspectral imageries were used to develop disease detection algorithms using image-derived spectral library, the mixture tuned... W. Lee, A. Kumar, R. Ehsani, C. Yang, L.G. Albrigo,

6. Categorization of Districts Based on Nonexchangeable Potassium: Generation GIS Maps and Implications in Efficient K Fertility Management in Indian Agriculture

Recommendations of K fertilizer are made based on available (exchangeable + water soluble) K status only  in India and other despite of  substantial contribution of nonexchangeable fraction of soil K to crop K uptake. Present paper examines the information generated in the last 30 years on the status of nonexchangeable K in Indian soils, categorization of Indian soils based on exchangeable and nonexchangeable K fractions and making K recommendations. Data for both K fractions of different... C. Srinivasa rao, K. Rao, H. Magen, B. Venkateswarlu, A. Subba rao

7. Using Electronic Technology to Remotely Monitor Conditions, Transfer the Data, and Display Data Real-time on the Internet

This session describes the use of electronic equipment to monitor soil temperature and moisture, air temperature, relative humidity, wind speed, solar radiation, leaf wetness, and rainfall. Presenter will explain how to use the equipment to monitor conditions, transfer the data, and display the information in real-time on the Internet.... R. Ashley, J. Nowatzki

8. Precision Tools to Evaluate Alternative Weed Management Systems in Soybean

... T.M. Blackmer, P.M. Kyveryga

9. Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure

... P.M. Kyveryga, T.M. Blackmer

10. Digital Aerial Imagery Guides a Statewide Nutrient Management Benchmarking Survey

... P.M. Kyveryga, T.M. Blackmer

11. Precision Tools to Evaluate Benefits of Tile Drainage in a Corn and Soybean Rotation in Iowa

... P.R. Reeg, T.M. Blackmer, P.M. Kyveryga

12. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial Information

Farmland quality represents various properties, including two parts of natural influencing factors and social influencing factors. The natural factors and social factors are interrelated and interaction, which determine the developing direction of farmland system. In order to overcome the limitation of subjective factors and fuzzy incompatible information, a more scientific evaluation method of farmland quality should be developed to reflect the essential characteristic of farmland.... Y. Dong, Y. Wang, X. Song, X. Gu

13. Evaluating Decision Systems For Using Variable Rates In Planting Soybean

Increased interest in managing seeding rates within soybean fields is being driven by the advances in technologies and the need to increase productivity and economic returns. A wealth of previous research was focused on studying how different seeding rates affect soybean yields at small-plot scales. However, little is known how different site-specific factors influence the responsiveness of soybean to higher or lower plant population densities at field levels, especially across geographic... P. Reeg, P.M. Kyveryga, T.A. Mueller

14. Soil Compaction: Impact Of Tractor And Equipment On Corn Growth, Development And Yield

This project looks at the impact of soil compaction on corn emergence, growth and development, and yield. This is a two-year study, begun in the in the spring of 2013, it will be completed after the 2014 growing season. Corn was produced in the field both years.   The project hypotheses are to: 1) Soil compaction does impact corn growth, development and yield; 2) Soil compacted in the fall season by farm equipment is measurable the following... S. Sivarajan, S. Bajwa, J. Nowatzki

15. Verify The Effectiveness Of UAS-Mounted Sensors In Field Crop And Livestock Production Management Issues

This research project is a “proof-of-concept” demonstrating specific UAS applications in production agriculture. Project personnel will use UAS-mounted sensors to collect data of ongoing crop and livestock research projects during the 2014 crop season at the North Dakota State University (NDSU) Carrington Research Extension Center (CREC). Project personnel will collaborate with NDSU research scientists conducting research at the CREC. During the first year of the project... S. Bajwa, J. Nowatzki, W. Harnisch, B. Schatz, V. Anderson

16. Water And Nitrogen Use Efficiency Of Corn And Switchgrass On Claypan Soil Landscapes

Claypan soils cover a significant portion of Missouri and Illinois crop land, approximately 4 million ha. Claypan soils, characterized with a pronounced argilic horizon at or below the soil surface, can restrict nutrient availability and uptake, plant water storage, and water infiltration. These soil characteristics affect plant growth, with increasing depth of the topsoil above the claypan horizon having a strong positive correlation to grain crop production. In the case of low... A. Thompson, D.L. Boardman, N. Kitchen, E. Allphin

17. Evaluation Of In-Field Sensors To Monitor Nitrogen Status In Soybean

In recent years, active optical crop sensors have been gaining importance to determine in-season nitrogen (N) fertilization requirements for on-the-go variable rate application.  Although most of these active in-field crop sensors have been evaluated in corn and wheat crops, they have not yet been evaluated in soybean production systems in North Dakota. Recent research from both South Dakota and North Dakota indicate that in-season N application in soybean can increase soybean yield... J. Nowatzki, S. Bajwa, S. Sivarajan, M. Maharlooei, H. Kandel

18. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy Temperature

Development of herbicide-resistant crops has resulted in significant positive changes to agronomic practices, while repeated and intensive use of herbicides with the same mechanisms of action has caused the development of herbicide-resistant weeds. As of 2015, 35 weed species are reported to be resistant to glyphosate worldwide. A greenhouse study was conducted to identify characteristics which can be helpful in field mapping of glyphosate resistant weeds by using UAV imagery. The experiment included... A. Shirzadi, M. Maharlooei, O. Hassanijalilian, S. Bajwa, K. Howatt, S. Sivarajan, J. Nowatzki

19. Challenges and Successes when Generating In-season Multi-temporal Calibrated Aerial Imagery

Digital aerial imagery (DAI) of the crop canopy collected by aircraft and unmanned aerial vehicles is the yardstick of precision agriculture.  However, the quantitative use of this imagery is often limited by its variable characteristics, low quality, and lack of radiometric calibration.  To increase the quality and utility of using DAI in crop management, it is important to evaluate and address these limitations of DAI.  Even though there have been improvements in spatial resolution... P.M. Kyveryga, J. Pritsolas, J. Connor, R. Pearson

20. Large-scale UAS Data Collection, Processing and Management for Field Crop Management

North Dakota State University research and Extension personnel are collaborating with Elbit Systems of America to compare the usefulness and economics of imagery collected from a large unmanned aircraft systems (UAS), small UAS and satellite imagery. Project personnel are using a large UAS powered with an internal combustion engine to collect high-resolution imagery over 100,000 acres twice each month during the crop growing season. Four-band multispectral Imagery is also being collected twice... J. Nowatzki, S. Bajwa, D. Roberts, M. Ossowski, A. Scheve, A. Johnson, Y. Chaplin

21. Within-field Profitability Assessment: Impact of Weather, Field Management and Soils

Profitability in crop production is largely driven by crop yield, production costs and commodity prices. The objective of this study was to quantify the often substantial yet somewhat illusive impact of weather, management, and soil spatial variability on within-field profitability in corn and soybean crop production using profitability indices for profit (net return) and return-on-investment (ROI) to produce estimates. We analyzed yield and cropping system data provided by 42 farmers within Central... P.M. Kyveryga, S. Fey, J. Connor, A. Kiel, D. Muth

22. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility Study

The fast and reliable quality determination of alfalfa crop is of interest for producers to make management decisions, the dealers to determine the price, and the dairy producers for livestock management. In this study, the crude protein (CP), one of the main quality indices of alfalfa, was estimated using the visible and near-infrared (Vis/NIR) spectroscopy. A total of 68 samples from various variety trials of alfalfa crop were collected under the irrigated and rainfed conditions. The diffuse... M. Maharlooei, S. Bajwa, S.A. Mireei, A. Shirzadi, S. Sivarajan, M. Berti, J. Nowatzki

23. 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

24. Map@Syst – Geospatial Solutions for Rural and Community Sustainability

Map@Syst is a part of the USDA Cooperative State Research, Education and Extension Service (CSREES) eXtension online Web information service. eXtension is an educational partnership of more than 70 universities to provide online access to objective, research-based information and educational opportunities. Map@Syst is a Wiki-based Web site assembled and maintained cooperatively by geospatial technology educational specialists and practitioners. Map@Syst is a primary source of geospatial information... P. Rasmussen, J. Nowatzki