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Yousef, D.A
Barlage, M
Graeff, S
Bussher, W.J
Hagan, B.A
Bisson, G
Rodrigues Júnior, F.H
Nguyen-Xuan, T
Farahmand, K
Ransom, C
Haneklaus, S
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Authors
Garcia, A.H
Rodrigues Júnior, F.H
Bastos, A.H
Magalhaes, P.S
Silva, M.J
Sharaf, S
Elshafie, A
Kamel, N.N
Yousef, D.A
Graeff, S
Pfenning, J
Claupein, W
Mahoney, W
Barlage, M
Gochis, D
Chen, F
Momsen, E
Xu, J
Franzen, D.W
Nowatzki, J.F
Farahmand, K
Denton, A.M
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Lilienthal, H
Schnug, E
Haneklaus, S
Bauer, P.J
Stone, K.C
Bussher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Hagan, B.A
Cue, R.I
Bouroubi, Y
Bugnet, P
Nguyen-Xuan, T
Bélec, C
Longchamps, L
Vigneault, P
Gosselin, C
Fadul-Pacheco, L
Bisson, G
Lacroix, R
Séguin, M
Roy, R
Vasseur, E
Lefebvre, D
Topics
Sensor Application in Managing In-season Crop Variability
Modeling and Geo-statistics
Precision Horticulture
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
No Group Selected
Precision Dairy and Livestock Management
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
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Authors

Filter results11 paper(s) found.

1. Adoption Of N-application Rates In Different Broccoli Cultivars By Reflectance Measurements

 To date many sensors have been solely developed and tested for arable crops. This project aims to develop the means to rapidly map N-demand in broccoli plants on a site-specific, plant-by-plant basis using reflectance measurements. The aim of this specific study was to monitor nitrogen status in six different broccoli cultivars using reflectance measurements and to derive suitable N-fertilization strategies based on the sensor measurements.A... S. Graeff, J. Pfenning, W. Claupein

2. Assembly of an Ultrasound Sensors System for Mapping of Sugar Cane Height

In Precision Agriculture, the use of sensors provides faster data collection on plant, soil, and climate, allowing collecting larger sample sets with better information quality. The objective of this study was the development of a system for plant height measurement in order to mapping of sugar cane crop, so that regions with plant growth variation and grow failures could be identified... A.H. Garcia, F.H. Rodrigues júnior, A.H. Bastos, P.S. Magalhaes, M.J. Silva

3. A High-Reliability Database-Supported Modular Precision Irrigation System

Title of Abstract:          A High-Reliability Database-Supported Modular Precision Irrigation System Authors of Abstract:     N. Kamel1, S. Sharaf1, A. El-Shafei2,... S. Sharaf, A. Elshafie, N.N. Kamel, D.A. Yousef

4. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision Support

Technological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilation... W. Mahoney, M. Barlage, D. Gochis, F. Chen

5. Use Of Quality And Quantity Information Towards Evaluating The Importance Of Independent Variables In Yield Prediction

Yield predictions based on remotely sensed data are not always accurate.  Adding meteorological and other data can help, but may also result in over-fitting.  Working with American Crystal Sugar, we were able to demonstrate that the relevance of independent variables can be tested much more reliably when not only yield but also quality attributes are known, such as the sugar content and the sugar... E. Momsen, J. Xu, D.W. Franzen, J.F. Nowatzki, K. Farahmand, A.M. Denton

6. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

7. 25 Years Precision Agriculture in Germany - a Retrospective

It all started with the availability of Global Positioning Systems for civil services in 1988. In the same year variable rate applications of fertilizers were demonstrated in northern Germany and Denmark, which were globally the first of their kind and introduced a new era of agricultural production. The idea of Computer Aided Farming (CAF) was born. Only one year later the first yield maps were established. In 1992 at the Soil Specific Crop Management Workshop in Bloomington, Minnesota which... H. Lilienthal, E. Schnug, S. Haneklaus

8. Site-specific Irrigation of Peanuts on a Coastal Plain Field

Irrigator-Pro is an expert system that prescribes irrigation for corn (Zea mays L.), cotton (Gossypium hirsutum L.) and peanut (Arachis hypogaea). We conducted an experiment in 2007 to evaluate Irrigator-Pro as a tool for variable rate irrigation of peanut using a site-specific center pivot irrigation system. Treatments were irrigation of whole plots based on the expert system, irrigation of individual soils within plots based on the expert system, irrigation of individual...

9. A Tool for Monitoring Genetic Selection Differentials in Dairy Herds in Canada

A software tool was developed to allow a dairy producer and/or agricultural advisor to monitor the genetic selection differentials (GSD) that a dairy farm is making. The objectives of this study were (i) to monitor GSD in individual farms, over years, so that producers can be advised as to whether or not they are achieving their selection objectives (and hence optimizing productivity and profitability); (ii) the development of a prototype software tool and visualization model to assist producers... B.A. Hagan, R.I. Cue

10. Pest Detection on UAV Imagery Using a Deep Convolutional Neural Network

Presently, precision agriculture uses remote sensing for the mapping of crop biophysical parameters with vegetation indices in order to detect problematic areas, and then send a human specialist for a targeted field investigation. The same principle is applied for the use of UAVs in precision agriculture, but with finer spatial resolutions. Vegetation mapping with UAVs requires the mosaicking of several images, which results in significant geometric and radiometric problems. Furthermore, even... Y. Bouroubi, P. Bugnet, T. Nguyen-xuan, C. Bélec, L. Longchamps, P. Vigneault, C. Gosselin

11. Usage of Milk Revenue Per Minute of Boxtime to Assess Cows Selection and Farm Profitability in Automatic Milking Systems

The number of farms implementing robotic milking systems, usually referred as automatic milking systems (AMS), is increasing rapidly. AMS efficiency is a priority to achieve high milk production and higher incomes from dairy herds. Recent studies suggested that milkability (i.e., amount of milk produced per total time spent in the AMS [kg milk/ minute of boxtime]) could be used for as a criteria for genetic evaluations. Therefore, an indicator of milkability was developed, which combines economical... L. Fadul-pacheco, G. Bisson, R. Lacroix, M. Séguin, R. Roy, E. Vasseur, D. Lefebvre