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Evaluation of Corn (Zea mays L.) Yield-loss Estimations by WeedSOFT® in the North Central Region

  • Andrew A. Schmidt (a1), William G. Johnson (a2), David A. Mortensen (a3), Alex R. Martin (a4), Anita Dille (a5), Dallas E. Peterson (a5), Corey Guza (a6), James J. Kells (a6), Ryan D. Lins (a7), Chris M. Boerboom (a7), Christy L. Sprague (a8), Stevan Z. Knezevic (a9), Fred W. Roeth (a10), Case R. Medlin (a11) and Thomas T. Bauman (a2)...
Abstract

Field studies were conducted in 2000 and 2001 to evaluate corn yield-loss predictions generated by WeedSOFT, a computerized weed management decision aid. Conventional tillage practices were used to produce corn in 76-cm rows in Illinois, Indiana, Kansas, Michigan, Missouri, Nebraska, and Wisconsin. A total of 21 site-years from these seven states were evaluated in this study. At 4 wk after planting, weed densities and size, crop-growth stage, estimated weed-free yield, and environmental conditions at the time of application were entered into WeedSOFT to generate POST treatments ranked by percent maximum yield (PMY). POST treatments were chosen with yield losses ranging from 0 to 20%. Data were subjected to linear regression analysis by state and pooled over all states to determine the relationship between actual and predicted yield loss. A slope value equal to one implies perfect agreement between actual and predicted yield loss. Slope value estimates for Illinois and Missouri were equal to one. Actual yield losses were higher than the software predicted in Kansas and lower than predicted in Michigan, Nebraska, and Wisconsin. Slope value estimate from a data set containing all site years was equal to one. This research demonstrated that variability in yield-loss predictions occurred at sites that contained a high density of a single weed specie (>100/m2) regardless of its competitive index (CI); at sites with a predominant broadleaf weed with a CI greater than five, such as Palmer amaranth, giant ragweed, common sunflower, and common cocklebur; and at sites that experience moderate to severe drought stress.

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Corresponding author's E-mail: wgj@purdue.edu
References
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Allen, J. A., Johnson, W. G., Smeda, R. J., and Kremer, R. J. 2000. ALS-resistant Helianthus annuus interference in Glycine max . Weed Sci. 48:461466.
Buhler, D. D., King, R. P., Swinton, S. M., Gunsolus, J. L., and Forcella, F. 1997. Field evaluation of a bioeconomic model for weed management in soybean (Glycine max). Weed Sci. 45:159165.
Fausey, J. C. and Renner, K. A. 1997. Germination, emergence, and growth of giant foxtail (Setaria faberi) and fall panicum (Panicum dichotomiflorum). Weed Sci. 45:423425.
Forcella, F., King, R. P., Swinton, S. M., Buhler, D. D., and Gunsolus, J. L. 1996. Multi-year validation of a decision aid for integrated weed management in row crops. Weed Sci. 44:650661.
Massinga, R. A., Currie, R. S., and Horak, M. J. 2001. Interference of Palmer amaranth in corn. Weed Sci. 49:202208.
Mortensen, D. A. and Coble, H. D. 1991. Two approaches to weed control-decision aid software. Weed Technol. 5:445452.
Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. 1996. Applied Linear Regression. 3rd ed. New York: McGraw-Hill. Pp. 5153.
Renner, K. A., Swinton, S. M., and Kells, J. J. 1999. Adaptation and evaluation of the WEEDSIM weed management model in Michigan. Weed Sci. 47:338348.
Snedecor, G. W. and Cochran, W. G. 1989. Statistical Methods. 8th edition. Ames, IA: Iowa State University Press. Pp. 6482.
Snipes, C. E., Street, J. E., and Walker, R. H. 1987. Interference periods of common cocklebur (Xanthium strumarium) with cotton (Gossypium hirsutum). Weed Sci. 4:529532.
Swinton, S. M. and King, R. P. 1994. The value of weed population information in a dynamic setting: the case of weed control. Am. J. Agric. Econ. 75:3646.
Wilkerson, G. G., Modena, S. A., and Coble, H. D. 1991. HERB: decision model for postemergence weed control in soybean. Agron. J. 83:413417.
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Weed Technology
  • ISSN: 0890-037X
  • EISSN: 1550-2740
  • URL: /core/journals/weed-technology
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