Proceedings
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| Filter results10 paper(s) found. |
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1. Validation of Variable Rate Spray Decision Rules in Intricate Micro-Metrological ConditionsThis study evaluated validity of modified spray decision rules formed to operate axial fan airblast sprayer retrofitted for use in citrus production. The sprayer was field tested in a spraying... L.R. Khot, R. Ehsani, G. Albrigo, J. Campoy, C. Wellington, W. Swen, J. Camergo Neto |
2. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial InformationFarmland 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 |
3. Soil Compaction: Impact Of Tractor And Equipment On Corn Growth, Development And YieldThis 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 |
4. Verify The Effectiveness Of UAS-Mounted Sensors In Field Crop And Livestock Production Management IssuesThis 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 |
5. Evaluation Of In-Field Sensors To Monitor Nitrogen Status In SoybeanIn 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 |
6. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy TemperatureDevelopment 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 |
7. Large-scale UAS Data Collection, Processing and Management for Field Crop ManagementNorth 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 |
8. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility StudyThe 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 |
9. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter WheatNitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng |
10. Mapping Leaf Area Index of Maize in Tasseling Stage Based on Beer-Lambert Law and Landsat-8 ImageLeaf area index (LAI) is one of the important structural parameters of crop population, which could be used to monitor the variety of crop canopy structure and analyze photosynthesis rate. Mapping leaf area index of maize in a large scale by using remote sensing technology is very important for management of fertilizer and water, monitoring growth change and predicting yield. The Beer-Lambert law has been preliminarily applied to develop inversion model of crop LAI, and has achieved good application... X. Gu, S. Wang, G. Yang, X. Xu |