Simulation models are useful tools for decision-making processes, allowing the exploration of different scenarios without having to test them experimentally. Modeling in agricultural systems, for example, enables upscale results obtained at plot/experimental site level to regional or national scale. This is the case of DNDC (i.e., DeNitrification-DeComposition) model of carbon and nitrogen biogeochemistry in agro-ecosystems. The model can be used for predicting crop growth, soil temperature and moisture regimes, soil carbon dynamics, nitrogen leaching, and emissions of trace gases including nitrous oxide (N2O), nitric oxide (NO), dinitrogen (N2), ammonia (NH3), methane (CH4) and carbon dioxide (CO2) [1 ]. COAPA research group is testing the efficiency of this model as a tool for making management decisions to improve production and reduce gaseous emissions for agro-ecosystems.


Another example is the set of DSSAT (Decision Support System for Agrotechnology Transfer) models that integrate more than 42 different types of crops and allow us to estimate the effects of the availability of water and fertilization on growth, production and development of crops. By understanding the soil-plant-atmosphere dynamics, DSSAT models offer information to users to quickly assess the adoption of new practices that can improve crop production, for example, from leaf nitrogen content it is possible to estimate the nitrogen demand of the corn plant with models like CSMIxim, as shown by results from AgSystems group [2]. This type of tool is particularly advantageous for predicting crop production in drought periods as well as optimizing the use of irrigation in semiarid areas.

[1] Li, CS. 2000. Modeling Trace Gas Emissions from Agricultural Ecosystems. Nut.
Cycl.Agroecosys. 58:259-276

[2] Lizaso, J.I., Boote, K.J., Jones, J.W., Porter, C.H., Echarte, L., Westgate, M.E., Sonohat, G. 2011. CSMIXIM: A New Maize Simulation Model for DSSAT version 4.5. Agronomy Journal, 103(3):766779