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Cerri, D.G
Carson, T
Congona Benavente, J
Tsibart, A
Jimenez, A
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Authors
Rice, K
Carson, T
Krum, J
Flitcroft, I
Cline, V
Carrow, R
Cerri, D.G
Magalh, P.S
Rodrigues Jr, F
Maglh, P.S
Cerri, D.G
Barros, M.F
Cugnasca, C.E
Congona Benavente, J
Tsibart, A
Postelmans, A
Dillen, J
Elsen, A
Van de Ven, G
Saeys, W
Oliveira, M.F
Morata, G.T
Ortiz, B
Silva, R.P
Jimenez, A
Topics
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2010
2022
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1. Spatial Mapping Of Penetrometer Resistance On Turfgrass Soils For Site-specific Cultivation

Site-specific management requires site-specific information.  Soil compaction at field capacity is a major stress on recreational turfgrass sites that requires frequent cultivation. Spatial mapping of penetrometer... K. Rice, T. Carson, J. Krum, I. Flitcroft, V. Cline, R. Carrow

2. Developing Of A Monitoring System Of Cutting, Carrying, And Transportation Of Sugar Cane In Order To Manage Fleet

In the productive process for obtaining sugar cane products, the costs associated to the activities of harvesting (cut), carrying and transport (CCT), represent great part of the final cost of the product. In order to reduce this costs new technologies should be adopted in the agricultural mechanization using precision agriculture methods. The use of the information technology combined with the use of intelligent components can help to improve the performance of machines and equipments and... D.G. Cerri, P.S. Magalh

3. Spatial Variability Analyse And Correlation Between Physical Chemical Soil Attributes And Sugarcane Quality Parameters

With the high increment in the ethanol demand, the trend is that the planted area with sugar cane in Brazil will increase from the actual 7 million ha up to 12 million ha in 15 years. The sugar cane expansion demands, beyond the enlargement of the boundaries with the installation of new industrial units, better use of the production areas and improvement of the yield and quality, together with production costs reduction. In such a way, the adoption of Precision Agriculture... F. Rodrigues jr, P.S. Maglh, D.G. Cerri

4. An Inter-connection Model Between Standard Zigbee And Isobus Network (ISO11783)

The typical five-step cyclical process of precision agriculture includes soil and environment data collection, diagnosis, data analysis, precision field correction operation and evaluations. Usually, some steps are executed in field, others in the farm office and others in both. This can result in a complex system and consequently in waste of time and high cost in equipment, tools and workmanship. To simplify this process, the challenge is running... M.F. Barros, C.E. Cugnasca, J. Congona benavente

5. Should We Increase or Decrease the Fertilization in the Zones with the Highest Crop Productivity Potential?

Introduction. In traditional farming, fertilizers are applied homogeneously on the agricultural fields taking into account the average crop recommendation. As most fields are not homogeneous, this results in overfertilization of certain zones and underfertilization of other zones. The excess of nitrate leaches to the surface and groundwaters which causes problems with the water quality. Precision fertilizer management has been proposed to reduce these negative effects.... A. Tsibart, A. Postelmans, J. Dillen, A. Elsen, G. Van de ven, W. Saeys

6. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices

In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez