Farmer's knowledge is that of experience, from years and seasons to relatively recurring climatic events, and to plants whose physiology is known and controlled.

Modeling is a scientific and innovative strategy of prediction. It is at the crossroad of several domains of knowledge, computerized in an equation to predict the development of the plant/climate.

On the one hand, it is a set of historical climate contextual data. The model "foresees" the climate of the coming months out of past climatic data. It allows to deduce likely climatic trends. However the limit is that it does not allow prediction of extreme climatic events.

On the other hand, it is a compilation of agronomic models, deducing the growth data of a plant according to its pedo-climatic context. Agronomic models are generally produced by research centers and other technical institutes.

Finally, economic modeling can also be used to predict the behavior of agricultural commodity markets, again depending on their past fluctuations and contextual elements.

The intersection of these domains is thus done through a mathematical / computer model, proposing a probable climate scenario, and making it possible to suggest to the farmer the technical actions to consider to maximize the efficiency of its interventions. The modeling technology opens up prospects in terms of reducing greenhouse gas emissions and the impacts of agricultural activity: rationalizing nitrogen inputs, anticipating pest pressure, adapting to water availability, etc. Crossing this information is an opportunity to inform the farmer in his decisions to help him reduce his impacts.