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Colaço, A.F
Acuna, T
Christiaens, R
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Authors
Walsh, O.S
Pandey, A
Christiaens, R
Trotter, M
Gregory, S
Trotter, T
Acuna, T
Swain, D
Fasso, W
Roberts, J
Zikan, A
Cosby, A.M
Trevisan, R.G
Eitelwein, M.T
Colaço, A.F
Molin, J.P
Eitelwein, M.T
Trevisan, R.G
Colaço, A.F
Vargas, M.R
Molin, J.P
Topics
Precision Nutrient Management
Agricultural Education
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Type
Poster
Oral
Year
2014
2016
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1. Precision Sensors For Improved Nitrogen Recommendations In Wheat

Crop sensor-based systems with developed algorithms for making mid-season fertilizer nitrogen (N) recommendations are commercially available to producers in some parts of the world. Although there is growing interest in these technologies by grain producers in Montana, use is limited by the lack of local research under Montana’s semiarid conditions. A field study was carried out at two locations in 2011, three locations in 2012, and two locations in 2013 in North West Montana:... O.S. Walsh, A. Pandey, R. Christiaens

2. SMARTfarm Learning Hub: Next Generation Precision Agriculture Technologies for Agricultural Education

The industry demands on higher education agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. This paper reports on the development of a key resource, the SMARTfarm Learning Hub (www.smartfarmhub.com) that will increase the skill base of higher education students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry... M. Trotter, S. Gregory, T. Trotter, T. Acuna, D. Swain, W. Fasso, J. Roberts, A. Zikan, A. Cosby

3. Sources of Information to Delineate Management Zones for Cotton

Cotton in Brazil is an input-intensive crop. Due to its cultivation in large fields, the spatial variability takes an important role in the management actions. Yield maps are a prime information to guide site-specific practices including delineation of management zones (MZ), but its adoption still faces big challenges. Other information such as historical satellite imagery or soil electrical conductivity might help delineating MZ as well as predicting crop performance. The objective of this work... R.G. Trevisan, M.T. Eitelwein, A.F. Colaço, J.P. Molin

4. On-the-go Measurements of pH in Tropical Soil

The objective of this study was to assess the performance of a mobile sensor platform with ion-selective antimony electrodes (ISE) to determine pH on-the-go in a Brazilian tropical soil. The field experiments were carried out in a Cambisol in Piracicaba-SP, Brazil. To create pH variability, increasing doses (0, 1, 3, 5, 7 and 9 Mg ha-1) of lime were added on the experimental plots (25 x 10 m) one year before the data acquisitions. To estimate soil pH levels we used a Mobile Sensor Platform... M.T. Eitelwein, R.G. Trevisan, A.F. Colaço, M.R. Vargas, J.P. Molin