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White, J.W
Westerdijk, K
Pagani, A
Namdarian, I
Virgawati, S
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Authors
Nino, P
Vanino, S
Lupia, F
Altobelli, F
Vuolo, F
Namdarian, I
De Michele, C
Virgawati, S
Feher, T
Kocks, C
Kempenaar, C
Westerdijk, K
Thorp, K.R
White, J.W
Conley, M.M
Mon, J
Bronson, K.F
Puntel, L
Pagani, A
Archontoulis, S
Topics
Remote Sensing Applications in Precision Agriculture
Global Proliferation of Precision Agriculture and its Applications
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Decision Support Systems
Type
Poster
Oral
Year
2012
2014
2018
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Filter results5 paper(s) found.

1. Applications for Precision Agriculture: the Italian Experience of SIRIUS Project

    This paper reports the results of the project SIRIUS (Sustainable Irrigation water management and River-basin... P. Nino, S. Vanino, F. Lupia, F. Altobelli, F. Vuolo, I. Namdarian, C. De michele

2. The Opportunities to Implement Precision Agriculture Technology in Indonesia: A Review

... S. Virgawati

3. Use Of Active Radiometers To Estimate Biomass, Leaf Area Index, And Plant Height In Cotton

Active radiometers have been tested extensively as tools to assess in-season nitrogen (N) status of crops like wheat (Triticum aestivum), corn (Zea mays), and cotton (Gossypium hirsutum).  Fewer studies target in-season plant growth parameters such as biomass, plant height or leaf area index (LAI).  Uses of this plant data include simulation modeling, total N uptake measurements, evapotranspiration (ET) estimates and irrigation... K.R. Thorp, J.W. White, M.M. Conley, J. Mon, K.F. Bronson

4. First Results Of Development Of A Smart Farm In The Netherlands

GNSS technology has been introduced on about 20 % of the Dutch arable farms in The Netherlands today. Use of sensor technology is also slowly but gradually being adopted by farmers, providing them large amounts of digital data on soil, crop and climate conditions. Typical data are spatial variation in soil organic matter, crop biomass, crop yield, and presence of pests and diseases. We still have to make major steps to use all this data in a way that agriculture becomes more sustainable. We... T. Feher, C. Kocks, C. Kempenaar, K. Westerdijk

5. Prediction of Corn Economic Optimum Nitrogen Rate in Argentina

Static (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aires,... L. Puntel, A. Pagani, S. Archontoulis