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Predicted Soybean Yield Loss As Affected by Emergence Time of Mixed-Species Weed Communities

  • Mark R. Jeschke (a1), David E. Stoltenberg (a1), George O. Kegode (a2), Christy L. Sprague (a3), Stevan Z. Knezevic (a4), Shawn M. Hock (a4) and Gregg A. Johnson (a5)...


Potential crop yield loss due to early-season weed competition is an important risk associated with postemergence weed management programs. WeedSOFT is a weed management decision support system that has the potential to greatly reduce such risk. Previous research has shown that weed emergence time can greatly affect the accuracy of corn yield loss predictions by WeedSOFT, but our understanding of its predictive accuracy for soybean yield loss as affected by weed emergence time is limited. We conducted experiments at several sites across the Midwestern United States to assess accuracy of WeedSOFT predictions of soybean yield loss associated with mixed-species weed communities established at emergence (VE), cotyledon (VC), first-node (V1), or third-node (V3) soybean. Weed communities across research sites consisted mostly of annual grass species and moderately competitive annual broadleaf species. Soybean yield loss occurred in seven of nine site-years for weed communities established at VE soybean, four site-years for weed communities established at VC soybean, and one site-year for weed communities established at V1 soybean. No soybean yield loss was associated with weed communities established at the V3 stage. Nonlinear regression analyses of predicted and observed soybean yield data pooled over site-years showed that predicted yields were less than observed yields at all soybean growth stages, indicating overestimation of soybean yield loss. Pearson correlation analyses indicated that yield loss functions overestimated the competitive ability of high densities of giant and yellow foxtail with soybean, indicating that adjustments to competitive index values or yield loss function parameters for these species may improve soybean yield loss prediction accuracy and increase the usefulness of WeedSOFT as a weed management decision support system.


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Crawley, M. J. 2002. Statistical Computing: An Introduction to Data Analysis Using S-Plus. West Sussex, England John Wiley & Sons. Pp. 305322.
Fickett, N. D., Stoltenberg, D. E., Boerboom, C. M., and Hammond, C. M. 2009. Estimated economic losses from early weed competition in Wisconsin corn and soybean fields. North Cent. Weed Sci. Soc. Proc. 64:93.
Gower, S. A., Loux, M. M., Cardina, J., Harrison, S. K., Sprankle, P. L., Probst, N. J., Bauman, T. T., Bugg, W., Curran, W. S., Currie, R. S., Harvey, R. G., Johnson, W. G., Kells, J. J., Owen, M. D. K., Regehr, D. L., Slack, C. H., Spaur, M., Sprague, C. L., VanGessel, M., and Young, B. G. 2003. Effect of postemergence glyphosate application timing on weed control and grain yield in glyphosate-resistant corn: results of a 2-yr multistate study. Weed Technol. 17:821828.
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. 2006a. Soybean row spacing and weed emergence time influence weed competitiveness and competitive indices. Weed Sci. 54:3846.
Hock, S. M., Knezevic, S. Z., Martin, A. R., and Lindquist, J. L. 2006b. Performance of WeedSOFT for predicting soybean yield loss. Weed Technol. 20:478484.
Jeschke, M. R., Stoltenberg, D. E., Kegode, G. O., Dille, J. A., and Johnson, G. A. 2009. Weed community emergence time affects accuracy of predicted corn yield loss by WeedSOFT. Weed Technol. 23:477485.
Kruger, G. R., Johnson, W. G., and Weller, S. C., et al. 2009. U.S. grower views on problematic weeds and changes in weed pressure in glyphosate-resistant corn, cotton, and soybean cropping systems. Weed Technol. 23:162166.
Moeching, M. J., Boerboom, C. M., Stoltenberg, D. E., and Binning, L. K. 2003. Growth interactions in communities of common lambsquarters (Chenopodium album), giant foxtail (Setaria faberi), and corn. Weed Sci. 51:363370.
Mulugeta, D. and Boerboom, C. M. 2000. Critical time of weed removal in glyphosate-resistant Glycine max . Weed Sci. 48:3542.
Myers, M. W., Curran, W. S., VanGessel, M. J., Majek, B. A., Scott, B. A., Mortensen, D. A., Calvin, D. D., Karsten, H. D., and Roth, G. W. 2005. The effect of weed density and application timing of weed control and corn grain yield. Weed Technol. 19:102107.
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.
Pinheiro, J. C. and Bates, D. M. 2000. Mixed-Effects Models in S and S-Plus. New York Springer. 530 p.
Ratkowsky, D. A. 1990. Handbook of Nonlinear Regression Models. Statistics, textbooks and monographs, Vol. 107, 241 p. New York Marcel Dekker.
Ritchie, S. W., Hanway, J. J., and Benson, G. O. 1997a. How a corn plant develops. Special Rep. 48. Ames, IA Iowa State University. 22 p.
Ritchie, S. W., Hanway, J. J., Thompson, H. E., and Benson, G. O. 1997b. How a soybean plant develops. Special Rep. 53. Ames, IA Iowa State University. 20 p.
Schmidt, A. A., Johnson, W. G., and 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.



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