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                <term xml:lang="en">CORN</term>
                <term xml:lang="en">N LEACHING</term>
                <term xml:lang="en">STICS</term>
                <term xml:lang="en">GROWTH</term>
                <term xml:lang="en">CLIMATE</term>
                <term xml:lang="en">WATER</term>
                <term xml:lang="en">YIELD</term>
                <term xml:lang="en">RISK</term>
                <term xml:lang="en">GENERIC MODEL</term>
                <term xml:lang="en">NITROGEN BALANCES</term>
                <term xml:lang="en">WINTER-WHEAT</term>
                <term xml:lang="en">UNCERTAINTY</term>
                <term xml:lang="en">WHEAT-WHEAT ROTATION</term>
                <term xml:lang="en">TAKE-ALL DIDEASE</term>
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              <p>This paper addresses the question of summer cover-crop adoption by farmers in presence of a risk of yield loss due to take-all disease and climate variability. To analyze the public incentives needed to encourage farmers to adopt summer cover crops as a means of reducing N leaching, we combine outputs from an economic, an epidemiological and an agronomic model. The economic model is a simple model of choice under risk. The farmer is assumed to choose among a range of summer fallow managements and input uses on the basis of the expected utility criterion (HARA assumption) in presence of both climate and take-all risks. The epidemiological model proposed by Ennaïfar et al. (Eur J Plant Pathol 118:127–143, 2007) is used to determine the impact of take all on yields and N uptake. The crop-soil model (STICS) is used to compute yield developments and N leaching under various management options and climatic conditions. The input parameters are chosen to match the conditions prevailing in Grignon, located in the main wheat-growing area in France. Eight management systems are examined: four summer fallow managements: ‘wheat volunteers’ (WV), ‘bare soil’ (BS), ‘early mustard’, ‘late mustard’, and two input intensities. We show that the optimal systems are BS (WV) when the take-all risk is (not) taken into account by agents. We then compute the minimum payment to each system such that it emerges in the optimum. We thus derive the required amounts of transfer needed to trigger catch-crop adoption. The results of the Monte Carlo sensitivity analysis show that the ranking of management systems is robust over a wide range of input parameters.</p>
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              <p>Cet article examine la question de l'adoption de cultures intermédiaires en présence d'un risque de rendement dû à une maladie (piétin) et au climat. Pour analyser les incitations requises pour encourager les exploitants à adopter une culture intermédiaire afin de réduire le lessivage d'azote, les auteurs combinent les résultats de trois modèles (économique, épidemiologique et agronomique). Le modèle économique est un simple modèle de choix en situation d'incertitude. L'exploitant est supposé choisir entre les différentes options de gestion de la période intercultures et d'intensité d'intrants sur la base de l'utilité espérée (HARA), le modèle épidemiologique proposé par Ennaifar et al. (2007) est utilisé pour déterminer l'impact du piétin sur le rendement et l'utilisation d'azote par la plante. Le modèle STICS est utilisé pour calculer les rendements et le lessivage d'azote dans les différentes situations. Ces modèles sont calibrés sur les conditions prévalant à Grignon, situé dans la principale zone de production de blé en France. Huit options sont considérées : 4 gestion de l'interculture 'repousses de blé' (WV), 'sol nu' (BS), 'moutarde précoce' (EM), 'moutarde tardive' (LM), et 2 niveaux d'intensité des intrants. Les auteurs montrent que les systèmes optimaux sont BS (WV) quand le risque de piétin est (n'est pas) pris en compte. Les auteurs calculent alors le paiement minimum pour que chaque système soit choisi à l'optimum. Les auteurs pouvent ainsi déduire les montants requis pour qu'une culture intermédiaire soit adoptée. Les résultats de l'analyse de sensibilité par méthode de Monte Carlo montrent que le classement des différents systèmes est robuste pour une large gamme de valeurs des paramètres.</p>
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