Proceedings
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| Filter results7 paper(s) found. |
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1. Developing An Active Crop Sensor-based In-season Nitrogen Management Strategy For Rice In Northeast ChinaCrop sensor-based in-season N management strategies have been successfully developed and evaluated for winter wheat around the world, but little has been reported for rice. The objective of this study was to develop an active crop sensor-based in-season N management strategy for upland rice in Northeast... Y. Yao, Y. Miao, S. Huang, M.L. Gnyp, R. Jiang, X. Chen, G. Bareth |
2. Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton ProductionTechnology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of... D.M. Lambert, J.A. Larson, B.C. English, R.M. Rejesus, M.C. Marra, A.K. Mishra, C. Wang, P. Watcharaanantapong, R.K. Roberts, M. Velandia |
3. In-season Diagnosis of Rice Nitrogen Status Using an Active Canopy Sensor... Y. Yao, Y. Miao, S. Huang, M. Gnyp, R. Khosla, R. Jiang, G. Bareth |
4. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural CropsAerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John |
5. Using Profitability Map to Make Precision Farming Decisions: A Case Study in MississippiRecent development in precision agriculture technologies have generated massive amount of geospatial data of farming, such as yield mapping, seeding rates, input applications, and so on. However, producers are still struggling to convert those precision data into farm management decisions to improve productivity and profitability of farming. Indeed, deriving accurate decisions at each site of the field requires complex and comprehensive modeling of crop yield responses to various... X. Li, K. Coble |
6. Data Clustering Tools for Understanding Spatial Heterogeneity in Crop Production by Integrating Proximal Soil Sensing and Remote Sensing DataRemote sensing (RS) and proximal soil sensing (PSS) technologies offer an advanced array of methods for obtaining soil property information and determining soil variability for precision agriculture. A large amount of data collected using these sensors may provide essential information for precision or site-specific management in a production field. In this paper, we introduced a new clustering technique was introduced and compared with existing clustering tools for determining relatively homogeneous... M. Saifuzzaman, V.I. Adamchuk, H. Huang, W. Ji, N. Rabe, A. Biswas |
7. Developing Geospatial Method for Autopilot Harvester Trampling Evaluation in Colombian Sugarcane FieldsSugarcane is a crop of great importance for the geographical valley of the Cauca River in Colombia, where it covers approximately 241,000 hectares and is cultivated by 13 sugar mills and about 4,200 cultivators. This region is characterized by its favorable climate, which enables year-round sugarcane harvesting and its high productivity, making it a global leader in this sector. This achievement is largely attributed to the technological advances developed by Colombia Sugarcane Research Center... J.D. Ome narvaez, D.F. Sandoval, S.A. Galeano, H.B. Tarapues, A. Estrada, J.P. Zuñiga, J.M. Valencia-correa |