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Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea Crop
1L. Garcia-Torres, 2D. Gomez-Candon, 2J. J. Caballero-Novella, 2M. Gomez-Casero, 3J. M. Pe, 2M. Jurado-Exp, 2F. Lopez-Granados, 3I. Castillejo-Gonz, 3A. Garc
1. Institute for Sustainable Agriculture, CSIC, Cordoba, Spain
2. IAS-CSIC
3. Univ. Cordoba

 

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 of each micro-plot.

     Spatial patches aggregation of biotic/ non-biotic factors and their corresponding pesticide/ fertilizer variable rates application prescription maps can be achieved through SARI® from remote images and complementary ground-taken data. An example of SARI® implementation in the remote image of a pea’s field infested by the parasitic weed/ pathogen Orobanche crenata Forsk. at Montalban (Cordoba, Spain) is described. Infestation pressure between micro-plots greatly varies from virtually parasitic weed free micro-plots up to completely infested micro-plots. SARI® also provides geo-referenced and visualised herbicide prescription maps, which can be used in variable-rate application equipments. The work herein developed has shown that remotely sensed imagery managed with SARI® can play an important role in developing cost-effective precision agriculture.

Keyword: Crop spatial management, variable-rate prescription maps, peas, Orobanche crenata.