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Fernandez, C.J
Fulton, J
Fallon, E
Fernandez, F.G
Usui, K
Yeh, M
Felipe dos Santos, A
Figueiredo, D.M
Filippini A., J
Yang, W
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Authors
Flores, C
Filippini A., J
Miele, A
Yang, C
Odvody, G.N
Fernandez, C.J
Landivar, J.A
Nichols, R.L
Chou, T
Yeh, M
Chen, J
Basso, B
Moon, J
Kim, S
Lee, J
Yang, W
Kim, D
Umeda, H
Shibusawa, S
Li, Q
Usui, K
Kodaira, M
Shibusawa, S
Umeda, H
Usui, K
Kodaira, M
Li, Q
Vigneault, P
Tremblay, N
Bouroubi, M.Y
Belec, C
Fallon, E
Bean, G.M
Kitchen, N.R
Camberato, J.J
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Sawyer, J.E
Scharf, P.C
Colley III, R
Fulton, J
Douridas, N
Port, K
Colley III, R
Fulton, J
Virk, S
Hawkins, E
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
de Azevedo, K.K
Figueiredo, D.M
Dallago, G.M
Vieira, J.A
Silveira, R.R
da Silva, L.D
Santos, R.A
Rennó, L.N
Pacheco, G.B
Khun, K
Vigneault, P
Fallon, E
Tremblay, N
Codjia, C
Cavayas, F
Colley III, R
Lin, Y
Fulton, J
Shearer, S
Lee, J
Fulton, J
Port, K
Colley III, R
Boatswain Jacques, A.A
Diallo, A.B
Cambouris, A
Lord, E
Fallon, E
Topics
Precision Horticulture
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Modeling and Geo-statistics
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Site-Specific Nutrient, Lime and Seed Management
Farm Animals Health and Welfare Monitoring
Applications of Unmanned Aerial Systems
Decision Support Systems
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2014
2018
2024
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Authors

Filter results16 paper(s) found.

1. Spatial Variability of Inceptisol and Entisol Soils and Their Effect on Merlot Grape Must Composition

Technologies associated to precision agriculture are being used in some crops in Brazil, mainly soybean, wheat, corn and sugarcane. However, information on its use in viticulture is scarce. Thus, a research was carried out during the vegetative cycle of 2010/2011 in a clone 347 Merlot... C. Flores, J. Filippini a., A. Miele

2. Evaluating Spectral Measures Derived From Airborne Multispectral Imagery for Detecting Cotton Root Rot

Cotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivore, is one of the most destructive plant diseases occurring... C. Yang, G.N. Odvody, C.J. Fernandez, J.A. Landivar, R.L. Nichols

3. I-SALUS: New Web Based Spatial Systems for Simulating Crop Yield and Environmental Impact

  SALUS (System Approach to Land Use Sustainability) model is designed to simulate the impact of agronomic management on yield and environmental impact. SALUS model has new approaches and algorithms for simulating soil carbon, nitrogen, phosphorous, tillage, soil water balance and yield components. In the past, the use of the crop model was not easy for general... T. Chou, M. Yeh, J. Chen, B. Basso

4. A Study On Diagnostic System Based On ISOAgLIB For Agricultural Vehicles

  Nowadays the growth of the embedded electronics and communications has demanded the development of applications in agricultural machinery in Korean agroindustry. The root reason is that most of agricultural machineries produced in Korea does not apply international standard. Therefore, the incompatibility problem between hardware, software and data formats has become a major obstacle for exporting agricultural products made by Korea to the world. In... J. Moon, S. Kim, J. Lee, W. Yang, D. Kim

5. 3D Map in the Depth Direction of Field for Precision Agriculture

 By a change in eating habits with economic development and the global population growth, we have been faced with the need for increased food production again. In order to solve the food problem in the future, the introduction of agriculture organization is progressing in emerging countries as well as developed countries. However, the occurrence of natural disasters and abnormal weather, which is becoming a worldwide problem at present, is further weakening the crops of farm... H. Umeda, S. Shibusawa, Q. Li, K. Usui, M. Kodaira

6. Using A Potable Spectroradiometer For In-Situ Measurement Of Soil Properties In A Slope Citrus Field

     In precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for crop and soil management. However, the spatial variability of soil properties is consider to be high cost and time consuming to characterize using traditional soil analysis method. To achieve cost and time reduction, the potential benefits of in-situ measurement of soil spectra have been recognized.     ... S. Shibusawa, H. Umeda, K. Usui, M. Kodaira, Q. Li

7. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In Corn

A number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) response... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon

8. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

9. On-Farm Digital Solutions and Their Associated Value to North American Farmers

Digital tools and data collection have become standard in a wide variety of present day agricultural operations. An array of digital tools, such as high resolution operational mapping, remote sensing, and farm management software offer solutions to many of the problems in modern agriculture. These technologies and services can, if implemented correctly, provide both immediate and long term agronomic value. A growing number of producers in Ohio and around North America question the proper method... R. Colley iii, J. Fulton, N. Douridas, K. Port

10. Field Level Management and Data Verification of Variable Rate Fertilizer Application

Increased cost efficiencies and ease of use make spinner-disc spreaders the primary method of applying fertilizers throughout much of the United States. Recently, advances in spreader systems have enabled multiple fertilizer products to be applied at variable application rates. This provides greater flexibility during site-specific management of in-field fertility. Physical and aerodynamic properties vary for fertilizer granules of different sources and densities, these properties in turn affect... R. Colley iii, J. Fulton, S. Virk, E. Hawkins

Showing 1 to 10 of 16 entries