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A tool based on remotely sensed LAI, yield maps and a crop model to recommend variable rate nitrogen fertilization for wheat

Published online by Cambridge University Press:  01 June 2017

F. Bourdin*
Affiliation:
UMR 1114 Emmah INRA-UAPV, 84914 Avignon, cedex 9 - France
F.J. Morell
Affiliation:
UMR 1114 Emmah INRA-UAPV, 84914 Avignon, cedex 9 - France present address : Pioneer Hi-Bred Spain S.L., 41012 Sevilla, Spain
D. Combemale
Affiliation:
UMR 1114 Emmah INRA-UAPV, 84914 Avignon, cedex 9 - France
P. Clastre
Affiliation:
UMR 1114 Emmah INRA-UAPV, 84914 Avignon, cedex 9 - France
M. Guérif
Affiliation:
UMR 1114 Emmah INRA-UAPV, 84914 Avignon, cedex 9 - France
A. Chanzy
Affiliation:
UMR 1114 Emmah INRA-UAPV, 84914 Avignon, cedex 9 - France
*
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Abstract

Inversing the STICS crop model with remote-sensing-derived leaf area index (LAI) and yield data from the previous crop is used to retrieve some soil permanent properties and crop emergence parameters. Spatialized nitrogen (N) fertilization recommendations are provided to farmers, for the second and third N applications, following the screening of eleven N application rates under a range of possible forthcoming climates, with the objective to maximize of the gross margin while respecting some environmental constraints. As a first field validation, we show (1) the improvement brought by the assimilation of LAI and yield into STICS to simulate crop and soil variables and (2) the interest of site specific application to maximize both the gross margin and the agro-environmental criterion.

Type
Spatial Crop Models
Copyright
© The Animal Consortium 2017 

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