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Designing crop management systems by simulation

Este trabajo presenta un marco para disenar sistemas de cultivo basados en  modelos. Una sección se centra en la importancia de vincular los modelos de decisión con modelos biofísicos para el desarrollo de sistemas innovadores de gestión, otra describe el lazo conceptual general para disenar sistemas de gestión, una tercera ilustra las diferentes etapas del ciclo de diseno. La última abre el debate sobre el uso internacional de las simulaciones para el diseno de sistemas de gestión de cultivos y en varios problemas metodológicos generales, así como diversas propuestas para hacerles frente.

J.E. Bergez, N. Colbach, O. Crespo, F. Garcia, M.H. Jeuffroy, E. Justes, C. Loyce, N. Munier-Jolain, W. Sadok

Europ. J. Agronomy 32 (2010) 3–9

 

To help agricultural advisors to propose innovative crop management systems, simulation models can be a complementary tool to field experiments and prototyping. Crop management systems can be modelled either by using a vector representing dates and quantities used as input parameters in crop models or by developing specific decision models linked with biophysical models. The general design process of crop management systems by simulation follows a four-step loop (GSEC): (i) generation; (ii) simulation; (iii) evaluation; (iv) comparison and choice. The Generation step can follow different approaches: from blind generation before simulation to optimization procedures using artificial intelligence algorithms during the loop process. Simulation is mainly an engineering problem. Evaluation process means assigning a vector of indicators to the simulated crop management systems. A three-point evaluation can be carried out on the simulated cropmanagement systems: global, agronomic and analytical.Comparison and choice of different simulated crop management systemsraise the question of “monetary” versus “non-monetary” comparison and how to aggregate different quantities such as drainage, nitrogen fertilisers, labour, etc. Different examples are given to illustrate the GSEC loop on the basis of research programs conducted in France. Methodological advances and challenges are then discussed.