Authors
| Filter results6 paper(s) found. |
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1. Sensor Algorithms 101This presentation will break down the algorithms used for Optical Sensor Based Nitrogen rate recommendations. The group will walk through the mechanics and agronomics behind the most commonly used equations, in order to turn the black boxes into slightly muddied waters. ... B. Arnall |
2. Weather Impacts on UAV Flight Availability for Agricultural Purposes in OklahomaThis research project analyzed 21 years of historical weather data from the Oklahoma Mesonet system. The data examined the practicality of flying unmanned aircraft for various agricultural purposes in Oklahoma. Fixed-wing and rotary wing (quad copter, octocopter) flight parameters were determined and their performance envelope was verified as a function of weather conditions. The project explored Oklahoma’s Mesonet data in order to find days that are acceptable for flying... P. Weckler, C. Morris, B. Arnall, P. Alderman, J. Kidd, A. Sutherland |
3. Comparative Analysis of Different On-the-go Soil Sensor SystemsThis study is part of the field of precision agriculture. This management mode is one of the great revolutions in the agriculture field, and it means better management of farm inputs such as fertilizers, herbicides, and seeds by applying the right amount at the right place and at the right time. To succeed in this, we should dispose of a tool that allows a precise assessment of the soil’s physical state. Thus, on-the-go soil sensors can be used as a creative tool to gain better... H. Moulay, B. Arnall, S. Phillips |
4. The Evaluation of NDVI Response Index Consistency Using Proximal Sensors, UAV and SatellitesThe Response Index NDVI (RINDVI) is described as the response of crops to additional nitrogen (N) fertilizer. It is calculated by dividing the NDVI of the high-N plot (N-rich strip) by the NDVI of the zero-N plot or farmer's practice where less pre-plant N was applied (Arnall and al., 2016). RI values are used to predict yield and monitor top dress N fertilization. Many research has been carried out to determine the difference... S. Phillips, B. Arnall, M. Maatougui |
5. The Evaluation of Spatial Response to Potassium in SoybeansIn agriculture, the nutrients that are in the largest demand are nitrogen (N), phosphorus (P), and potassium (K), as product demand increases so does demand for fertilizers. In the case of potassium, most soils can provide potassium in amounts that exceed crop demand; however the potassium within the soil is not always readily available to the crop, this leads to producers apply potassium to their crops even though soil tests suggests otherwise. One such crop where potassium is in demand... S. Akin, B. Arnall |
6. Influence of Potassium Variability on Soybean YieldDue to its role as a plant essential nutrient, Potassium (K) serves as a fundamental component for plant growth. Soybeans are heavily reliant upon this nutrient for root growth and the production of pods, so much so that after nitrogen, potassium is the second most in-demand nutrient. Much of the overall soybean crop grown in Oklahoma is not managed with the fertility of K directly in mind. However, as the potential and expectation for greater yield increases, so does interest from producers... J. Derrick, S. Akin, R. Sharry, B. Arnall |