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| Filter results13 paper(s) found. |
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1. Recision Management For Enhancing Farmer Net Returns With The Conservation Reserve ProgramYield maps have successfully been combined with economic principles in establishing precision guided recommendations for enrollment in the Conservation Reserve Program (CRP). This can and has resulted in greater net returns for farmers than not enrolling in CRP or enrolling all eligible land in CRP without the consideration of foregone economic opportunities (Stull et al. 2004). This study expands these concepts by recognizing the adaptive behavior of the farmer and opportunities resulting from... C. Dillon, J. Shockley |
2. Profitability Of RTK Autoguidance And Its Influence On Peanut ProductionEfficient harvest of peanuts (Arachis hypogea L.) requires that the digging implement be accurately positioned directly over the target rows. Small driving... K. Balkcom, B. Ortiz, J. Shockley, J.P. Fulton |
3. Estimation of Nitrogen of Rice in Different Growth Stages Using Tetracam Agriculture Digital CameraMany methods are available to monitor nitrogen content of rice during various growth stages. However, this monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera (ADC) was used to acquire high spatial and temporal resolution in order to determine the status of nitrogen (N) and predict the grain yield of rice (Oriza sativa L.). In this study, 12 pots of rice with four different N treatments (0, 125,... A. Gholizadeh , M. Mohd soom , M. Saberioon |
4. Visible And Near-Infrared Spectroscopy For Monitoring Potentially Toxic Elements In Reclaimed Dumpsite Soils Of The Czech RepublicDue to rapid economic development, high levels of potentially harmful elements and heavy metals are continuously being released into the brown coal mining dumpsites of the Czech Republic. Elevated metal contents in soils not only dramatically impact the soil quality, but also due to their persistent nature and long biological half-lives, contaminant elements can accumulate in the food chain and can eventually endanger human health. Conventional methods for investigating potentially... L. Borùvka, M. Saberioon, R. Vašát, A. Gholizadeh |
5. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance SpectraSuccessful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and Memory... A. Gholizadeh, M. Saberioon, L. Borůvka |
6. Active and Passive Crop Canopy Sensors As Tools for Nitrogen Management in CornThe objectives of this research were to (i) assess the correlation between active and passive crop canopy sensors’ vegetation indices at different corn growth stages and (ii) assess sidedress variable rate nitrogen (N) recommendation accuracy of active and passive sensors compared to the agronomic optimum N rate (AONR). The experiment was conducted near Central City, Nebraska on a Novina sandy loam planted to corn on 15 April 2015. The experiment was a randomized complete-block design with... L. Bastos, R. Ferguson |
7. Regional Usefulness of Nitrogen Management Zone Delineation ToolsIn the Northern Plains of Montana, North Dakota and Minnesota, a number of site-specific tools have been used to delineate nitrogen management zones. A three-year study was conducted using yield mapping, elevation measurements, satellite imagery, aerial Ektochrome® photography, and soil EC to delineate nitrogen management zones and compare these zones to residual fall soil nitrate. At most of the sites, variable-rate N was applied and compared with uniform N application. The site-specific... D. Franzen, F. Casey, J. Staricka, D. Long, J. Lamb, A. Sims, M. Halvorson, V. Hofman |
8. A Comparison of Three-Dimensional Data Acquisition Methods for Phenotyping ApplicationsCurrently Phenotyping is primarily performed using two-dimensional imaging techniques. While this yields interesting data about a plant, a lot of information is lost using regular cameras. Since a plant is three-dimensional, the use of dedicated 3D-imaging sensors provides a much more complete insight into the phenotype of the plant. Different methods for 3D-data acquisition are available, each with their inherent advantages and disadvantages. These have to be addressed depending on the particular... O. Scholz, F. Uhrmann, S. Gerth, K. Pieger, J. Claußen |
9. Active and Passive Sensor Comparison for Variable Rate Nitrogen Determination and Accuracy in Irrigated CornThe objectives of this research were to (i) compare active and passive crop canopy sensors’ sidedress variable rate nitrogen (VRN) derived from different vegetation indices (VI) and (ii) assess VRN recommendation accuracy of active and passive sensors as compared to the agronomic optimum N rate (AONR) in irrigated corn. This study is comprised of six site-years (SY), conducted in 2015, 2016 and 2017 on different soil types (silt loam, loam and sandy loam) and with a range of preplant-applied... L. Bastos, R.B. Ferguson |
10. Economics of Swarm Bot Profitability for Cotton HarvestImproved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine |
11. Machine Learning Techniques for Early Identification of Nitrogen Variability in MaizeCharacterizing and managing nutrient variability has been the focus of precision agriculture research for decades. Previous research has indicated that in-situ fluorescence sensor measurements can be used as a proxy for nitrogen (N) status in plants in greenhouse conditions employing static sensor measurements. Indeed, practitioners of precision N management require determination of in-season plant N status in real-time at field scale to enable the most efficient N fertilizer... D. Mandal, R.D. Siqueira, L. Longchamps, R. Khosla |
12. Creating a Comprehensive Software Framework for Sensor-driven Precision AgricultureRobots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if their... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties |
13. Cherry Yield Forecast: Harvest Prediction for Individual Sweet Cherry TreesDigitalization continues to transform the agricultural sector as a whole and also affects specific niches like horticulture. Particularly in fruit and wine production, the focus is on the application of sensor systems and data analysis aiming at automated detection of drought stress or pests in vineyards or orchards. As part of the “For5G” project, we are developing an end-to-end methodology for the creation of digital twins of fruit trees, with a strong focus... A. Gilson, L. Meyer, A. Killer, F. Keil, O. Scholz, D. Kittemann, P. Noack, P. Pietrzyk, C. Paglia |