Skip to main content Accessibility help
×
Home

Weed Community Emergence Time Affects Accuracy of Predicted Corn Yield Loss by WeedSOFT

  • Mark R. Jeschke (a1), David E. Stoltenberg (a1), George O. Kegode (a2), J. Anita Dille (a3) and Gregg A. Johnson (a4)...

Abstract

WeedSOFT is a state-of-the-art decision support system for weed management in the north central region of the United States, but its accuracy to predict corn yield loss associated with later-emerging weed communities has not been adequately assessed. We conducted experiments in 2004 and 2005 to compare observed and predicted corn yield related to four establishment times of mixed-species weed communities for validation of competitive index modifier (CIM) values in WeedSOFT. Weed communities were established at VE, V2, V4, and V6 corn (emergence, second-leaf, fourth-leaf, and sixth-leaf stages, respectively), and consisted largely of annual grass and moderately competitive annual broadleaf species. Compared to weed-free corn, yield loss occurred in each of seven site-years for weed communities established at VE corn, but in only one site-year for communities established at V2 corn. No corn yield loss was associated with weed communities established at V4 or V6 corn. For communities established at VE corn, predicted corn yield differed from observed yield in all but one site year, with predicted yield less than observed yield in three site-years, and greater than observed yield in two site-years; however, nonlinear regression analyses of yield data pooled over site-years showed that fitted values were similar between predicted and observed yield. For communities established at V2 and V4 corn, predicted yield was less than observed yield in six and five site-years, respectively. For communities established at V6 corn, predicted yield was less than observed yield in three of six site-years, but was similar to observed yield in three of six site-years. These results indicated that the CIM values in WeedSOFT tended to overestimate the competitiveness of late-emerging weed communities. Corn yield data from a pooled analysis of all site-years were used to generate a revised set of growth stage CIM values, which improved the accuracy of predicted corn yield. These results should improve weed management decisions and reduce the need for herbicide applications to late-emerging weeds.

Copyright

Corresponding author

Corresponding author's E-mail: destolte@wisc.edu.

References

Hide All
Aldrich, R. J. 1987. Predicting crop yield reductions from weeds. Weed Technol 1:199206.
Buhler, D. D., Liebman, M., and Obrycki, J. J. 2000. Theoretical and practical challenges to an IPM approach to weed management. Weed Sci 48:274280.
Coble, H. D. and Mortensen, D. A. 1992. The threshold concept and its application to weed science. Weed Technol 6:191195.
Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Q 2:1320.
Crawley, M. J. 2002. Statistical Computing: An Introduction to Data Analysis Using S-Plus. West Sussex, England: John Wiley & Sons Ltd. 305322.
Deines, S. R., Dille, J. A., Blinka, E. L., Regehr, D. L., and Staggenborg, S. A. 2004. Common sunflower (Helianthus annuus) and shattercane (Sorghum bicolor) interference in corn. Weed Sci 52:976983.
Hock, S. M., Knezevic, S. Z., Johnson, W. G., Sprague, C., and Martin, A. R. 2007. WeedSOFT: Effects of corn-row spacing for predicting herbicide efficacy on selected weed species. Weed Technol 21:219224.
Hock, S. M., Knezevic, S. Z., Martin, A. R., and Lindquist, J. L. 2006. Performance of WeedSOFT for predicting soybean yield loss. Weed Technol 20:478484.
Neeser, C., Dille, J. A., Krishman, G., Mortensen, D. A., Rawlinson, J. T., Martin, A. R., and Bills, L. B. 2004. WeedSOFT®: a weed management decision support system. Weed Sci 52:115122.
O'Donovan, J. T. 1996. Weed economic thresholds: useful agronomic tool or pipe dream? Phytoprotection 77:1328.
Pinheiro, J. C. and Bates, D. M. 2000. Mixed-Effects Models in S and S-Plus. New York: Springer Verlag. 528.
Ratkowsky, D. A. 1990. Handbook of Nonlinear Regression Models. New York: Marcel Dekker. 241.
Schmidt, A. A., Johnson, W. G., Mortensen, D. A., et al. 2005. Evaluation of corn (Zea mays L.) yield-loss estimations by WeedSOFT® in the north central region. Weed Technol 19:10561064.
Schnitker, D. D., Young, B. G., Johnson, W. G., and Loux, M. M. 2006. Accuracy of WeedSOFT® for predicting early-season competitive loads following residual herbicides in glyphosate-resistant corn. North Cent. Weed Sci. Soc. Abstr 61:37.
Swanton, C. J., Weaver, S., Cowan, P., Van Acker, R., Deen, W., and Shrestha, A. 1999. Weed thresholds: theory and applicability. Pages 929. In Buhler, D. D. Expanding the Context of Weed Management. Binghamton, NY: Food Products.

Keywords

Related content

Powered by UNSILO

Weed Community Emergence Time Affects Accuracy of Predicted Corn Yield Loss by WeedSOFT

  • Mark R. Jeschke (a1), David E. Stoltenberg (a1), George O. Kegode (a2), J. Anita Dille (a3) and Gregg A. Johnson (a4)...

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.