Saturday, 15 July 2006
116-54

Simulating the Soil Organic Carbon Dynamic for Different Crop Rotations in Southwest Burkina Faso.

Cecilia M. Tojo Soler, The Univ of Georgia, Dept Biological & Agricultural Engineering, 1109 Experiment St., Griffin, GA 30223, Vincent Bado, Inera, Bobo-Dioulasso, Burkina Faso, McNair Bostick, Univ of Florida, 2700 SW Archer Rd #b22, Gainesville, FL 32608, Gerrit Hoogenboom, Univ of Georgia, Dept Biological & Agricultural Engineering, 1109 Experiment St., Griffin, GA 30223-1797, and James Jones, University of Florida, PO Box 110570, Gainesville, FL 32611-0570.

Agricultural systems are normally studied through classical field experiments. However this methodology is resource intensive. Dynamic crop simulation models can be used as a complementary tool to help analyze these types of cropping systems, especially if it involves long-term crop rotations. The goal of this study was to simulate the Soil Organic Carbon (SOC) dynamic for different crop rotations in Burkina Faso, West Africa using the Cropping System Model (CSM) of DSSAT Version 4.0. A crop rotation experiment conducted in Farakô-Ba, Burkina Faso from 1993 to 2004 was used to evaluate the performance of the model. Eight crop rotations, including cotton, sorghum, peanut, maize and fallow, and three different management scenarios, with nitrogen (N), without N (control), and with manure applications were studied. It was found that the SOC content for all rotations decreased during the experiment, except for the continuous fallow (native grassland) in which the SOC remained stable. The model simulated the SOC for the continuous fallow system with a high accuracy and for the other crop rotations the differences between the observed and simulated values of SOC were, in general, less than 15%. The crop rotations that included supplemental N-fertilizer applications and manure caused an increase in the average aboveground biomass for the different crops. If incorporated after harvest, it reduced the loss of SOC when compared to the control treatment. This study showed that DSSAT and CSM model are promising decision support tools for the identification of cropping systems that have potential for carbon sequestration.

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