Proceedings
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| Filter results22 paper(s) found. |
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1. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 SurveyThe objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves |
2. Path Tracking Control of Tractors and Steerable Towed Implements Based On Kinematic and Dynamic Modelingrecise path tracking control of tractors became the enabling technology for automation of field work in recent years. More and more sophisticated control systems for tractors however revealed that exact positioning of the actual implement is equally or even more important. Especially sloped and curved terrain, strip till fields, buried drip irrigation tapes and high-value crop... G. Kormann, S. Mueller, R. Werner |
3. Temporal N Status Evaluation Using Hyperspectral Vegetation Indices in a Potato CropThe amount and timing of nitrogen (N) fertilization represents a leading issue in precision agriculture, especially for potato (Solanum tuberosum L.) crop since N is an essential element for plant growth and tuber yield. Therefore, the ability to assess in-season crop N status from non-destructive methods such as proximal sensing is a promising alternative to optimize N fertilization... A. Cambouris, K. Chokmani, T. Morier |
4. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, BrazilAlthough precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi |
5. Implementation of a Controller Unit Based on the ISO 11783 Standard for Automatic Measurement of the Electrical Conductivity of the Soil... L. M. rabello, R. R. d. pereira, W. C. lopes, R. Y. inamasu, R. V. de sousa |
6. Soil Salinity, Sand Encroachment and Erosion as Indicators of Land Degradation in Harad Center, Saudi ArabiaThis study presents the main results of a thorough evaluation of land degradation in Saudi Arabia (Harad Centre). The study was carried out in 2006-2007 as part of a project aimed to study features and causes of land degradation in Saudi Arabia. The study area occupies... O.A. Mahjoub, A.S. Modaihsh |
7. GNSS Positioning Techniques For AgricultureBroadacre, row crop and high value crops each have different positioning needs. Within these agricultural groups, individual practices such as mapping, guidance and machine control for tillage, application and harvest each have their own Global Navigation Satellite Systems (GNSS) needs for an optimal price/performance and value equation. New research and algorithm development by NovAtel has resulted in a significant simplification of positioning methodology with increased... P.M. Casiano, T.G. Morley, Z. Sadeque |
8. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement. However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (VDT)... D. Whattoff, D. Mouazen, D. Waine |
9. UAV-based Crop Scouting for Precision Nutrient ManagementPrecision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of wheat... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda |
10. Measuring Pasture Mass and Quality Indices Over Time Using Proximal and Remote SensorsTraditionally pasture has been measured or evaluated in terms of a dry matter yield estimate, which has no reference to other important quality factors. The work in this paper measures pasture growth rates on different slopes and aspects and pasture quality through nitrogen N% and metabolizable energy and ME concentration. It is known that permanent pasture species vary greatly in terms of quality and nutritional value through different stages of maturity. Pasture quality decreases as grass tillers... I.J. Yule, M.C. Grafton, L.A. Willis, P.J. Mcveagh |
11. Proximal Hyperspectral Sensing in Plant BreedingThe use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detection... H. Lilienthal, P. Wilde, E. Schnug |
12. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor AlgorithmNitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
13. Use of a Cropping System Model for Soil-specific Optimization of Limited WaterIn the arena of modern agriculture, system models capable of simulating the complex interactions of all the relevant processes in the soil-water-plant- atmosphere continuum are widely accepted as potential tools for decision support to optimize crop inputs of water to achieve location specific yield potential while minimizing environmental (soil and water resources) impacts. In a recent study, we calibrated, validated, and applied the CERES-Maize v4.0 model for simulating limited-water irrigation... L.R. Ahuja, S.A. Saseendran, L. Ma, D.C. Nielsen, T.J. Trout, A.A. Andales, N.C. Hansen |
14. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer ResponseImproving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer |
15. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your BenefitsClimate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet |
16. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean YieldThe ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet |
17. Development of a Machine Vision Yield Monitor for Shallot Onion HarvestersCrop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller |
18. Economic Potential of RoboWeedMaps - Use of Deep Learning for Production of Weed Maps and Herbicide Application MapsIn Denmark, a new IPM ‘product chain’ has been constructed, which starts with systematic photographing of fields and ends up with field- or site-specific herbicide application. A special high-speed camera, mounted on an ATV took sufficiently good pictures of small weed plants, while driving up to 50 km/h. Pictures were uploaded to the RoboWeedMaps online platform, where appointed internal- and external persons with agro-botanical experience executed ‘virtual field inspection’... P. Rydahl, O. Boejer, N. Jensen, B. Hartmann, R. Jorgensen, M. Soerensen, P. Andersen, L. Paz, M.B. Nielsen |
19. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and IndianaPrecision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor |
20. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical DataBayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri |
21. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase IntentionsClimate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, the... M. Michels, V. Bonke, H. Wever, O. Mußhoff |
22. Crop and Water Monitoring Networks with Low-cost, Internet of Things TechnologyMaking meaningful changes in agroecosystems often requires the ability to monitor many environmental parameters to accurately identify potential areas for improvement in water quality and crop production. Increasingly, research questions are requiring larger and larger monitoring networks to draw applicable insights for both researchers and producers. However, acquiring enough sensors to address a particular research question is often cost-prohibitive, making it harder to draw meaningful conclusions... A.J. Brown, E. Deleon, E. Wardle |