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Soybean Yield Loss Potential Associated with Early-Season Weed Competition across 64 Site-Years

Published online by Cambridge University Press:  20 January 2017

Nathanael D. Fickett ,
Chris M. Boerboom  and
David E. Stoltenberg
Nathanael D. Fickett
Affiliation:
Department of Agronomy, 1575 Linden Drive, University of Wisconsin, Madison, WI 53706
Chris M. Boerboom
Affiliation:
Department of Agronomy, 1575 Linden Drive, University of Wisconsin, Madison, WI 53706
David E. Stoltenberg*
Affiliation:
Department of Agronomy, 1575 Linden Drive, University of Wisconsin, Madison, WI 53706
*
Corresponding author's E-mail: destolte@wisc.edu
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Abstract

Glyphosate applied POST can provide a high level of efficacy on many weed species in soybean, but delayed application beyond optimal weed growth stages might fail to fully protect yield potential. Further, we do not have a good understanding of the extent to which delayed glyphosate application and its associated yield loss is occurring on-farm. Our goal was to characterize on-farm weed communities in glyphosate-resistant soybean just prior to glyphosate application and estimate potential yield loss associated with early-season soybean-weed competition. In field surveys conducted across 64 site-yr in southern Wisconsin in 2008 and 2009, common lambsquarters, velvetleaf, dandelion, Polygonum spp., and Amaranthus spp. were the five most abundant broadleaf weed species across site-years, present in 92, 69, 64, 42, and 50% of all fields, respectively, at average densities of 14, 5, 5, 14, and 10 plants m−2, respectively. Average height of these species was 21 cm or less at or near the time of glyphosate application. Grass and sedge species occurred in 95% of fields at an average density of 41 plants m−2 and height of 21 cm. The mean and median values of total weed density across site-years were 101 and 41 plants m−2, with heights of 19 and 17 cm, respectively. Recommended height for treatment is 15 cm. Glyphosate application occurred on average at V3 to V4 soybean growth stage, which is later than V2 soybean typically targeted to protect yield. Average yield loss predicted by WeedSOFT® was 5% with a mean economic loss of $47 ha−1. Predicted yield loss was greater than 5% on one-fourth of the site-years, all of which were treated at V4 soybean or later. The maximum predicted yield loss was 27%. These results suggest that glyphosate was applied at weed height and soybean growth stages that were greater than optimal to protect yield in many fields across southern Wisconsin. A soil-residual herbicide applied PRE, or a more timely POST application of glyphosate would alleviate the majority of these losses.

Keywords

GlyphosateAmaranthus sppcommon lambsquarters, Chenopodium album L. CHEALdandelion, Taraxacum officinale G. H. Weber ex Wiggers TAROFvelvetleaf, Abutilon theophrasti Medik. ABUTHPolygonum sppsoybean, Glycine max (L.) MerrDecision support systemPOSTweed abundanceweed community compositionWeedSOFT
Type
Weed Management
Information
Weed Science , Volume 61 , Issue 3 , September 2013 , pp. 500 - 507
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Chandler, K., Shrestha, A., and Swanton, C. J. 2001. Weed seed return as influenced by the critical weed-free period and row spacing of no-till glyphosate-resistant soybean. Can. J. Plant Sci. 81:877–880.Google Scholar
Chikoye, D. and Ekeleme, F. 2003. Cover crops for cogongrass (Imperata cylindrica) management and effects on subsequent corn yield. Weed Sci. 51:792–797.CrossRefGoogle Scholar
Coulter, J. A. and Nafziger, E. D. 2007. Planting date and glyphosate timing on soybean. Weed Technol. 21:359–366.Google Scholar
Cullen, E., Davis, V., Esker, P., Jensen, B., and Renz, M. 2011. Pest Management in Wisconsin Field Crops: 2012. Madison, WI University of Wisconsin–Extension. 258 p.Google Scholar
Dalley, C. D., Kells, J. J., and Renner, K. A. 2004. Effect of glyphosate application timing and row spacing on corn (Zea mays) and soybean (Glycine max) yields. Weed Technol. 18:165–176.Google Scholar
Ellis, J. M. and Griffin, J. L. 2002. Benefits of soil-applied herbicides in glyphosate-resistant soybean (Glycine max). Weed Technol. 16:541–547.CrossRefGoogle Scholar
Eyherabide, J. J. and Cendoya, M. G. 2002. Critical periods of weed control in soybean for full field and in-furrow interference. Weed Sci. 50:162–166.Google Scholar
Fickett, N. D., Boerboom, C. M., and Stoltenberg, D. E. 2013. Predicted corn yield loss due to weed competition prior to postemergence herbicide application on Wisconsin farms. Weed Technol. 27:54–62.CrossRefGoogle Scholar
Frick, B. and Thomas, A. G. 1992. Weed surveys in different tillage systems in southwestern Ontario field crops. Can. J. Plant Sci. 72:1337–1347.Google Scholar
Givens, W. A., Shaw, D. R., Johnson, W. G., Weller, S. C., Young, B. G., Wilson, R. G., Owen, M. D. K., and Jordan, D. 2009. A grower survey of herbicide use patterns in glyphosate-resistant cropping systems. Weed Technol. 23:156–161.CrossRefGoogle Scholar
Gulden, R. H., Sikkema, P. H., Hamill, A. S., Tardif, F., and Swanton, C. J. 2009. Conventional vs. glyphosate-resistant cropping systems in Ontario: weed control, diversity, and yield. Weed Sci. 57:665–672.CrossRefGoogle Scholar
Gulden, R. H., Sikkema, P. H., Hamill, A. S., Tardif, F., and Swanton, C. J. 2010. Glyphosate-resistant cropping systems in Ontario: multivariate and nominal trait-based weed community structure. Weed Sci. 58:278–288.Google Scholar
Halford, C., Hamill, A. A., Zhang, J., and Doucet, C. 2001. Critical period of weed control in no-till soybean (Glycine max) and corn (Zea mays). Weed Technol. 15:737–744.CrossRefGoogle Scholar
Hock, S. M., Knezevic, S. Z., Martin, A. R., and Lindquist, J. L. 2006. Performance of WeedSOFT for predicting soybean yield loss. Weed Technol. 20:478–484.Google Scholar
Ivany, J. A. 2004. Comparison of weed control strategies in glyphosate-resistant soybean [Glycine max (L.) Merr.] in Atlantic Canada. Can. J. Plant Sci. 84:1199–1204.CrossRefGoogle Scholar
Jeschke, M. R., Stoltenberg, D. E., Kegode, G. O., Sprague, C. L., Knezevic, S. Z., Hock, S. M., and Johnson, G. A. 2011. Predicted soybean yield loss as affected by emergence time of mixed-species weed communities. Weed Sci. 59:416–423.CrossRefGoogle Scholar
Johnson, W. G., Gibson, K. D., and Conley, S. P. 2007. Does weed size matter? An Indiana grower perspective about weed control timing. Weed Technol. 21:542–546.CrossRefGoogle Scholar
Knezevic, S. Z., Evans, S. P., and Mainz, M. 2003. Row spacing influences the critical timing for weed removal in soybean (Glycine max). Weed Technol. 17:666–673.Google Scholar
Krausz, R. F., Young, B. G., Kapusta, G., and Matthews, J. L. 2001. Influence of weed competition and herbicides on glyphosate-resistant soybean (Glycine max). Weed Technol. 15:530–534.Google Scholar
Kruger, G. R., Johnson, W. G., Weller, S. C., Owen, M. D. K., Shaw, D. R., Wilcut, J. W., Jordan, D. L., Wilson, R. G., Bernards, M. L., and Young, B. G. 2009. U.S. grower views on problematic weeds and changes in weed pressure in glyphosate-resistant corn, cotton, and soybean cropping systems. Weed Technol. 23:162–166.CrossRefGoogle Scholar
McCully, K. V., Sampson, M. G., and Watson, A. K. 1991. Weed survey of Nova Scotia lowbush blueberry (Vaccinium angustifolium) fields. Weed Sci. 39:180–185.Google Scholar
Mulugeta, D. and Boerboom, C. M. 2000. Critical time of weed removal in glyphosate-resistant Glycine max . Weed Sci. 48:35–42.CrossRefGoogle Scholar
[NOAA–NCDC] National Oceanic and Atmospheric Administration, National Climatic Data Center. 2010. Coop Data. http://www7.ncdc.noaa.gov/IPS/coop/coop.html. Accessed June 2010.Google Scholar
Neeser, C., Dille, J. A., Krishnan, G., Mortensen, D. A., Rawlinson, J. T., Martin, A. R., and Bills, L. B. 2004. WeedSOFT®: a weed management decision support system. Weed Sci. 52:115–122.Google Scholar
Nurse, R. E., Hamill, A. S., Swanton, C. J., Tardif, F., Deen, W., and Sikkema, P. H. 2007. Is the application of a residual herbicide required prior to glyphosate application in no-till glyphosate-tolerant soybean (Glycine max). Crop Prot. 26:484–489.CrossRefGoogle Scholar
Sartorato, I., Berti, A., Zanin, G., and Dunan, C. M. 2011. Modeling glyphosate application timing in glyphosate-resistant soybean. Weed Sci. 59:390–397.CrossRefGoogle Scholar
Schmidt, A. A., Johnson, W. G., Mortensen, D. A., Martin, A. R., Dille, A., Peterson, D. E., Guza, C., Kells, J. J., Lins, R. D., Boerboom, C. M., Sprague, C. L., Knezevic, S. Z., Roeth, F. W., Medlin, C. R., and Bauman, T. T. 2005. Evaluation of corn (Zea mays L.) yield-loss estimations by WeedSOFT® in the North Central Region. Weed Technol. 19:1056–1064.CrossRefGoogle Scholar
Steel, D. G. R. and Torrie, J. H. 1980. Principles and Procedures of Statistics: A Biometrical Approach. New York McGraw-Hill. 633 p.Google Scholar
Thomas, A. G. 1985. Weed survey system used in Saskatchewan for cereal and oilseed crops. Weed Sci. 33:34–43.CrossRefGoogle Scholar
Thomas, A. G. and Dale, M. R. T. 1991. Weed community structure in spring-seeded crops in Manitoba. Can. J. Plant Sci. 71:1069–1080.CrossRefGoogle Scholar
Thomas, W. E., Pline-Srnic, W. A., Thomas, J. F., Edmisten, K. L., Wells, R., and Wilcut, J. W. 2004. Glyphosate negatively affects pollen viability but not pollination and seed set in glyphosate-resistant corn. Weed Sci. 52:725–734.Google Scholar
Tukey, J. W. 1977. Exploratory Data Analysis. 1st ed. Reading, MA Addison-Wesley. 688 p.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2008. Wisconsin: 2008 Acreage. Washington, DC USDA, http://www.nass.usda.gov/Statistics_by_State/Wisconsin/Publications/Crops/acreage.pdf. Accessed March 1, 2009.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2009. Wisconsin: 2009 Acreage. Washington, DC USDA, http://www.nass.usda.gov/Statistics_by_State/Wisconsin/Publications/Crops/acreage.pdf. Accessed March 17, 2010.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2011a. Acreage 2011. Washington, DC USDA, http://usda01.library.cornell.edu/usda/nass/Acre//2010s/2011/Acre-06-30-2011.pdf. Accessed May 10, 2012.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2011b. 2011 Wisconsin Agricultural Statistics Bulletin. Washington, DC USDA, http://www.nass.usda.gov/Statistics_by_State/Wisconsin/Publications/Annual_Statistical_Bulletin/bulletin2011_web.pdf. Accessed November 30, 2011.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2011c. Custom Rate Guide 2010. Washington, DC USDA, http://www.nass.usda.gov/Statistics_by_State/Wisconsin/Publications/custom_rates_2010.pdf. Accessed June 3, 2012.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2012a. Wisconsin—Crop Production. Washington, DC USDA, http://www.nass.usda.gov/Statistics_by_State/Wisconsin/Publications/Crops/crop_prod_ann.pdf. Accessed June 3, 2012.Google Scholar
[USDA–NASS] U.S. Department of Agriculture, National Agricultural Statistics Service. 2012b. Wisconsin Crop Production Values. Washington, DC USDA, http://www.nass.usda.gov/Statistics_by_State/Wisconsin/Publications/Crops/cpvalue.pdf. Accessed June 3, 2012.Google Scholar
Van Acker, R. C., Thomas, A. G., Leeson, J. Y., Knezevic, S. Z., and Frick, B. L. 2000. Comparison of weed communities in Manitoba ecoregions and crops. Can. J. Plant Sci. 80:963–972.CrossRefGoogle Scholar
Williams, M. M. II, Rabaey, T. L., and Boerboom, C. M. 2008. Residual weeds of processing sweet corn in the north central region. Weed Technol. 22:646–653.Google Scholar
Young, B. G. 2006. Changes in herbicide use patterns and production practices resulting from glyphosate-resistant crops. Weed Technol. 20:301–307.CrossRefGoogle Scholar