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Modeling the integrated management of giant foxtail in corn–soybean

  • Alvin J. Bussan and Chris M. Boerboom (a1)

Abstract

The objectives of this study were to use a computer simulation model to predict the influence of herbicides and mechanical treatments on giant foxtail population dynamics, annualized net return (ANR), and the giant foxtail economic optimum threshold (EOT) in a corn–soybean rotation over 20 yr. Mechanical treatments were interrow cultivation in corn and rotary hoe in soybean. Herbicides at full (1 ×) and half (½ ×) rates applied alone reduced giant foxtail seedbank 95% within 4 and 8 yr, respectively. Predicted seedbank dynamics had more variability when managed with herbicides at ½ × than at 1 × rates applied alone. Mechanical treatments integrated with herbicide at ½ × rates resulted in giant foxtail seedbank and variability similar to herbicides at 1 × rates applied alone. ANR was maximized when herbicides were applied between ⅜ × and 9/16 × rates applied alone. As initial giant foxtail density increased from 100 to 10,000 seeds m−2, the herbicide rate that maximized ANR increased. Economic optimum thresholds (EOTs) did not vary when herbicides were applied at different rates, but integrating mechanical treatment with herbicides increased the EOT from 0.1 to 0.7 seedlings m−2. Sensitivity analysis determined that giant foxtail seedbank demographics, seedling survival, and seed production per plant had the most influence on model predictions. Model sensitivity varied little between 1 × and ½ × rates. Integrating herbicides and mechanical treatment decreased the sensitivity of the model to perturbations in parameter estimates. Herbicides at reduced rates were more profitable over the long term than 1 × rates, but risk of herbicide failure increased as rate decreased. Integration of herbicides applied at reduced rates with mechanical treatments increased ANR and minimized the risk of herbicide failure compared to herbicides applied at 1 × rates alone.

Copyright

Corresponding author

Corresponding author. Department of Agronomy, University of Wisconsin, Madison, WI 53706.

References

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Weed Science
  • ISSN: 0043-1745
  • EISSN: 1550-2759
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