Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T15:12:46.988Z Has data issue: false hasContentIssue false
  • English
  • Français

Winter Wheat Response to Preplant Applications of Aminocyclopyrachlor

Published online by Cambridge University Press:  20 January 2017

Andrew R. Kniss  and
Drew J. Lyon
Andrew R. Kniss*
Affiliation:
Department of Plant Sciences, University of Wyoming, Laramie, WY 82071
Drew J. Lyon
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Scottsbluff, NE 69361
*
Corresponding author's E-mail: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Field studies were conducted in Wyoming and Nebraska in 2007 through 2009 to evaluate winter wheat response to aminocyclopyrachlor. Aminocyclopyrachlor was applied at rates between 15 and 120 g ai ha−1 6, 4, and 2 mo before winter wheat planting (MBP). Redroot pigweed control was 90% with aminocyclopyrachlor rates of 111 and 50 g ha−1 when applied 4 or 2 MBP. Aminocyclopyrachlor at 37 g ha−1 controlled Russian thistle 90% when applied 6 MBP. At Sidney, NE, winter wheat yield loss was > 10% at all aminocyclopyrachlor rates when applied 2 or 4 MBP, and at all rates > 15 g ha−1 when applied 6 MBP. At Lingle, WY, > 40% winter wheat yield loss was observed at all rates when averaged over application timings. Although the maturing wheat plants looked normal, few seed were produced in the aminocyclopyrachlor treatments, and therefore preharvest wheat injury ratings of only 5% corresponded to yield losses ranging from 23 to 90%, depending on location. The high potential for winter wheat crop injury will almost certainly preclude the use of aminocyclopyrachlor in the fallow period immediately preceding winter wheat.

Se llevaron a cabo estudios de campo en Wyoming y Nebraska de 2007 hasta 2009, para evaluar la respuesta del trigo de invierno al aminocyclopyrachlor. Este herbicida fue aplicado a dosis entre 15 y 120 g ia ha−1 a los 6, 4, y 2 meses antes de la siembra del trigo (MBP). El control de Amaranthus retroflexus fue del 90% con dosis de 111 y 50 g ha−1 de aminocyclopyrachlor, cuando se aplicó a 4 y 2 MBP, respectivamente. El aminocyclopyrachlor aplicado a 37 g ha−1 controló Salsola tragus en un 90% cuando se aplicó 6 MBP. En Sidney, Nebraska, la pérdida de rendimiento del trigo fue >10% en respuesta a todas las dosis de aminocyclopyrachlor cuando se aplicó 2 ó 4 MBP, y a todas las dosis >15 g ha−1 cuando se aplicó 6 MBP. En Lingle, Wyoming, se observó una pérdida de rendimiento del trigo >40% en respuesta a todas las dosis, cuando se promediaron los momentos de aplicación. Aun cuando las plantas de trigo al madurar se veían normales, se produjeron pocas semillas en los tratamientos con aminocyclopyrachlor y por lo tanto, estimados visuales de daño pre-cosecha en el trigo de sólo 5% correspondieron a pérdidas de rendimiento que variaron de 23 a 90%, dependiendo del sitio. El alto potencial de daño al cultivo, seguramente impedirá el uso de aminocyclopyrachlor en el periodo de barbecho inmediatamente previo a la siembra del trigo de invierno.

Keywords

Aminocyclopyrachlorredroot pigweed, Amaranthus retroflexus L., AMARERussian thistle, Salsola tragus L. SASKRwinter wheat, Triticum aestivum L.6-Amino-5-chloro-2-cyclopropyl-4-pyrimidin methyl estercrop injuryDPX-KJM44DPX-MAT28fallowherbicidesoil residual
Type
Weed Management—Major Crops
Information
Weed Technology , Volume 25 , Issue 1 , March 2011 , pp. 51 - 57
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Weed Science Society of America

References

Literature Cited

Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol 107:239–252.Google Scholar
Derksen, D. A., Anderson, R. L., Blackshaw, R. E., and Maxwell, B. 2002. Weed dynamics and management strategies for cropping systems in the northern Great Plains. Agron. J. 94:174–185.Google Scholar
Donald, W. W. 2006. Between-observer differences in relative corn yield vs. rated weed control. Weed Technol. 20:41–51.Google Scholar
Finkelstein, B. L., Armel, R. G., Bolgunas, S. A., Clark, D. A., Claus, J. S., Crosswicks, R. J., Hirata, C. M., Hollinghaus, G. J., Koeppe, M. K., Rardon, P. L., Wittenbach, V. A., and Woodward, M. D. 2009. DuPont DPX-MAT28 herbicide. Technical Bulletin. Reorder No.: K15023. E.I. du Pont de Nemours and Company. 8 p.Google Scholar
Gillaspy, G., Ben-David, H., and Gruissem, W. 1993. Fruits: a developmental perspective. Plant Cell 5:1439–1451.Google Scholar
Heap, I. 2010. The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed: March 4, 2010.Google Scholar
Montgomery, D., Evans, C., and Martin, D. 2009. Control of kochia with DPX-KJM44 along Oklahoma highway rights-of-way. Proc. Weed Sci. Soc. Am 49:493.Google Scholar
Nielsen, D. C., Vigil, M. F., Anderson, R. L., Bowman, R. A., Benjamin, J. G., and Halvorson, A. D. 2002. Cropping system influence on planting water content and yield of winter wheat. Agron. J. 94:962–967.Google Scholar
R Development Core Team 2009. R: A language and environment for statistical computing. Vienna, Austria R Foundation for Statistical Computing. http://www.R-project.org.Google Scholar
Rinella, M. J., Haferkamp, M. R., Masters, R. A., Muscha, J. M., Bellows, S. E., and Vermeire, L. T. 2010. Growth regulator herbicides prevent invasive annual grass seed production. Invasive Plant Sci. Manag 3:12–16.Google Scholar
Ritz, C. and Spiess, A. N. 2008. qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis. Bioinformatics 24:1549–1551.Google Scholar
Ritz, C. and Streibig, J. C. 2005. Bioassay analysis using R. J. Statistical Software 12(5). http://www.jstatsoft.org/.Google Scholar
Seefeldt, S. S., Jensen, J. E., and Feurst, E. P. 1995. Log-logistic analysis of herbicide dose-response relationships. Weed Technol. 9:218–227.Google Scholar
Spiess, A. N. and Neumeyer, N. 2010. An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach. BMC Pharmacol 10:6. http://www.biomedcentral.com/1471-2210/10/6.Google Scholar
Taiz, L. and Zeiger, E. 2002. Auxin: The Growth Hormone. Pages 423–460. In Taiz, L. and Zeiger, E. Plant Physiology. 3rd ed. Sunderland, MA Sinauer Associates.Google Scholar
[USDA-ERS] U.S. Department of Agriculture Economic Research Service 2007. Major Land Uses. http://www.ers.usda.gov/data/majorlanduses/. Accessed: February 25, 2010.Google Scholar
Vassios, J. D., Douglass, C., Bridges, M., Lindenmayer, B., and Nissen, S. 2009. Native grass tolerance to aminopyralid and DPX-KJM44. Proc. Weed Sci. Soc. Am 49:153.Google Scholar
Westra, P., Wilson, R., and Edwards, M. 2008. Agronomic crop responses to KJM-44 herbicide. Proc. Western Soc. Weed Sci 61:62.Google Scholar
Westra, P., Nissen, S., Shaner, D., Lindenmayer, B., and Brunk, G. 2009. Invasive weed management with aminocyclopyrachlor in the Central Great Plains. Proc. Weed Sci. Soc. Am 49:407.Google Scholar