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\hypersetup{pdftitle={Crop Simulation Model for Poverty Alleviation and Sustainable Development in Low Income Countries},pdfauthor={Djoko Noumodje Patrice},pdfsubject={Tropentag 2010: Abstract},pdfkeywords={Carbon emission, crop simulation model, disease occurrence, economic threshold, farm income, food safety, food security, forecasting yield},pdfpagemode=None,colorlinks=true}
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\parbox[b]{13.4cm}{\centering \large{\textbf{Tropentag, September 14-16, 2010, Zurich}}\\[1ex] \Large{``World Food System  ---\\A Contribution from Europe''\\[2ex]}}
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\Large{\textbf{Crop Simulation Model for Poverty Alleviation and Sustainable Development in Low Income Countries\footnote{\textbf{Contact Address:} Djoko Noumodje Patrice, Wwe Cameroon, Culture Protection and Agricultural Economics, Rue Du Discobole 3/003, 1348~Louvain La Neuve, Belgium, \mbox{e-mail}: \email{dnpatrice2001@yahoo.fr}}\\[0.8ex]}}
\normalsize{\textsc{Djoko Noumodje Patrice}}
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\begin{itemize*}
\item[]{\small{\textit{Wwe Cameroon, Culture Protection and Agricultural Economics, Belgium}}}
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\index[author]{Patrice, Djoko Noumodje}
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\textbf{Abstract}
\begin{abstract}
\normalsize{
For producers, processors, and exporters the challenges of international competitiveness in higher value food trade has become increasingly linked to the development of capacity to manage food safety, food security, and plant health risks.



Crop simulation model has been becoming the core of agricultural production management and resource optimisation management. Of particular concern is to assess the importance of crop simulation models in poverty alleviation, environmental protection and reduction of dependency of farmers on pesticides used, and assure that new opportunities are exploited.  



On the basis of understanding the occurrence condition, popularity season, key impact factors for the most economically important diseases, it is essential to design a model for crop growth and diseases occurrence.



A multivariate regression model will be run to assess association within biophysical conditions by taking disease occurrence (incidence or severity) as dependent variable and key abiotic, biotic, and agronomic parameter as independent variables. In another hand, the same approach will also be implemented in order to assess association between socioeconomic and biophysical conditions by considering farm income as dependent variable and intensity of plant diseases, cost of acquisition and application of pesticides and distance to the market (carbon emission) as independent variables. The confrontation of these two models will held in the establishment of economic threshold of intervention for diseases control. This economic threshold calculated by the system incorporates historical weather data to predict the growth rate of the pathogen population will help farmer, technician and decision maker to use crop growth simulation model better and provide decision making support. So farmers will reduce cost of production, reduce risk of infringements since they use less pesticide in export oriented agricultural production, contribute to environmental protection and improve the competiveness of their products in international market. 



At the regional scale, these two system analysis, when integrated in a computer technology, will be used to forecast yield with typical application such as forecasting regional yield and evaluating the effects of environment and social economy changes on agriculture.



}

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\noindent \textbf{Keywords:} Carbon emission, crop simulation model, disease occurrence, economic threshold, farm income, food safety, food security, forecasting yield
\index[key]{Carbon emission}
\index[key]{Crop!simulation model}
\index[key]{Disease occurrence}
\index[key]{Economic!threshold}
\index[key]{Farm!income}
\index[key]{Food!safety}
\index[key]{Food!security}
\index[key]{Forecasting yield}
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