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Caballero-Novella, J.J
Costa, C.C
Colaço, A
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Authors
Gómez-Candón, D
Caballero-Novella, J.J
Peña-Barragán, J.M
Jurado-Expósito, M
López-Granados, F
Garcia-Torres, L
deCastro, A.I
Gómez-Candón, D
Caballero-Novella, J.J
Peña-Barragán, J.M
Jurado-Expósito, M
Garcia-Torres, L
López-Granados, F
deCastro, A.I
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Gomez-Casero, M
Pe, J.M
Jurado-Exp, M
Lopez-Granados, F
Castillejo-Gonz, I
Garc, A
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Pe, J.M
Jurado-Exp, M
Castillejo-Gonz, I
Garc, A
Lopez-Granados, F
Prassack, L
Burnquist, H.L
Costa, C.C
Anselmi, A.A
Molin, J.P
eitelwein, M.T
Trevisan, R
Colaço, A
Topics
Remote Sensing Applications in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Profitability, Sustainability and Adoption
Spatial Variability in Crop, Soil and Natural Resources
Type
Poster
Oral
Year
2012
2010
2014
2016
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Authors

Filter results6 paper(s) found.

1. Automatic Remote Image Processing For Agriculture Uses Through Specific Software

Abstract ... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, F. López-granados, L. Garcia-torres, A.I. Decastro

2. Position Error of Input Prescription Map Delineated From Remote Images

     The spatial variability of biotic factors... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, L. Garcia-torres, F. López-granados, A.I. Decastro

3. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea Crop

  The software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc

4. Management Of Remote Imagery For Precision Agriculture

Satellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack

5. Conditioning Factors For Decision-Making Regarding Precision Agriculture Techniques Usage

The eventual goal of using the techniques of precision agriculture (described as inputs applied at varied rates) is to get one of the following results: (a) lowering cost by reducing inputs, (b) decreasing the pollution of water, soil and the atmosphere and (c) increasing agricultural productivity by the more efficient use of inputs. However, studies on these techniques do not reach similar conclusions. This could be expected, since the effectiveness of these techniques would depend... H.L. Burnquist, C.C. Costa

6. Positioning Strategy of Maize Hybrids Adjusting Plant Population by Management Zones

Choice of hybrid and accurate amount of plants per area determines grain yield and consequently net incomes. Local field adjustment in plant population is a strategy to manage spatial variability and optimize environmental resources that are not under farmer control (like soil type and water availability). This study aims to evaluate the response of hybrids by levels of plant population across management zones (MZ). Six different hybrids and five rates of plant populations were analyzed starting... A.A. Anselmi, J.P. Molin, M.T. Eitelwein, R. Trevisan, A. Colaço