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An integrated crop–livestock system (ICL) can help with enhancing soil quality and crop productivity, ultimately increasing farm income. Field experiments that evalu- ated the impact of cover crops (CCs) and grazing on crop productivity have shown mixed results primarily because of a relatively short duration of the crop–livestock system. Dynamic crop models can help to simulate the long-term impact of soils and crop management on crop yield. The objectives of the current study were to develop a simple simulation methodology for crop–livestock interaction using the Decision Support System for Agrotechnology Transfer (DSSAT) and to evaluate the perfor- mance of CC grazing on maize (Zea mays L.) production. Here, differences in pre- and postgrazing dry matter were used to determine the daily biomass consumption by livestock, and the in vitro dry matter digestibility (IVDMD) of the CCs was used to determine the amount of manure that is being returned to the soil during the graz- ing period. The data generated from the field experiments were used to calibrate and evaluate the cropping system model (CSM)-CERES-Maize of DSSAT. The index of agreement (d) for yield was 0.99 and 0.95, whereas relative root mean squared error (RRMSE) was 4.72 and 0.3% of the observed yield for calibration and evaluation, respectively. The trends in the field data were well represented by the simulated data. The current methodology provides evidence that crop modeling can be used to study ICLs, especially the crop–livestock interactions, by scientists and policy makers to help develop best management practices to increase yield and improve soil health.

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Agrosystems, Geosciences, & Environment





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