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Defining the Rate Requirements for Synergism Between Mesotrione and Atrazine in Redroot Pigweed (Amaranthus retroflexus)

Published online by Cambridge University Press:  20 January 2017

Josie A. Hugie ,
German A. Bollero ,
Patrick J. Tranel  and
Dean E. Riechers
Josie A. Hugie
Affiliation:
Department of Crop Sciences, University of Illinois, Urbana, IL 61801
German A. Bollero
Affiliation:
Department of Crop Sciences, University of Illinois, Urbana, IL 61801
Patrick J. Tranel
Affiliation:
Department of Crop Sciences, University of Illinois, Urbana, IL 61801
Dean E. Riechers*
Affiliation:
Department of Crop Sciences, University of Illinois, Urbana, IL 61801
*
Corresponding author's E-mail: [email protected]
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Abstract

Joint action of the effects of atrazine and mesotrione can lead to synergistic herbicidal activity in broadleaf weed species. The objective of these experiments was to determine if specific rates are required to provide synergistic joint activity between mesotrione and atrazine in both triazine-sensitive (TS) and triazine-resistant (TR) redroot pigweed. Herbicide rates were evaluated in TS and TR redroot pigweed in two experiments: a dose response of mesotrione alone and in mixture with a constant rate of atrazine and a dose response of atrazine alone and in mixture with a constant rate of mesotrione. Results from these experiments revealed that synergism was detected in the TS pigweed when 56 g ai ha−1 mesotrione was mixed with 126 g ai ha−1 atrazine. In the TR pigweed, synergism was detected when mesotrione rate at 10 to 56 g ha−1 was mixed with a constant rate of atrazine at 126 g ha−1. Additionally, when mesotrione was held constant at 10 g ha−1, synergism was detected in mixture with atrazine from 31 to 3556 g ha−1 in TR pigweed. Furthermore, in TR pigweed, analysis of slope deviation across the dose-response curves of mesotrione with and without atrazine revealed a divergence that increased in magnitude as the rate of mesotrione increased. In other words, increased synergism was observed with increased mesotrione rate in the TR pigweed, which was also supported by biomass reduction and atrazine-like injury to the leaves. An additional experiment investigated synergism between mesotrione and bromoxynil in both TS and TR pigweed. Mesotrione at 10 g ha−1 was synergistic when paired with bromoxynil from 70 to 210 g ha−1 in both the TS and the TR pigweed.

Keywords

Atrazinebromoxynilmesotrioneredroot pigweed, Amaranthus retroflexus L. AMAREDose responseherbicide joint actionHPPD inhibitorphotosystem II inhibitortriazine resistance
Type
Weed Management
Information
Weed Science , Volume 56 , Issue 2 , April 2008 , pp. 265 - 270
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Abendroth, J. A., Martin, A. R., and Roeth, F. W. 2006. Plant response to combinations of mesotrione and photosystem II inhibitors. Weed Technol. 20:267–274.CrossRefGoogle Scholar
Anonymous 2006a. Callisto® Herbicide Label. Greensboro, NC Syngenta Crop Protection. 14. p.Google Scholar
Anonymous 2006b. AAtrex Nine-O® Herbicide Label. Greensboro, NC Syngenta Crop Protection. 16. p.Google Scholar
Anonymous 2006c. Buctril® 4EC Label. Research Triangle Park, NC Bayer CropScience. 36. p.Google Scholar
Burnet, M. W. M., Hildebrand, O. B., Holtum, J. A. M., and Powles, S. B. 1991. Amitrole, triazine, substituted urea, and metribuzin resistance in a biotype of rigid ryegrass (Lolium rigidum). Weed Sci. 39:317–323.CrossRefGoogle Scholar
Colby, S. R. 1967. Calculating synergistic and antagonistic responses of herbicide combinations. Weeds. 15:20–22.CrossRefGoogle Scholar
Corbett, J. L., Askew, S. D., Thomas, W. E., and Wilcut, J. W. 2004. Weed efficacy evaluations for bromoxynil, glufosinate, glyphosate, pyrithiobac, and sulfosate. Weed Technol. 18:443–453.CrossRefGoogle Scholar
Devine, M. D. and Preston, C. 2000. The molecular basis of herbicide resistance. Pages 72–104. in Cobb, A. H. and Kirkwood, R. C. Herbicides and their mechanisms of action. Sheffield, England, UK Sheffield Academic.Google Scholar
Diggle, A. J., Neve, P. B., and Smith, F. P. 2003. Herbicides used in combination can reduce the probability of herbicide resistance in finite weed populations. Weed Res. 43:371–382.CrossRefGoogle Scholar
Duke, S. O., Dayan, F. E., Romagni, J. G., and Rimando, A. M. 2000. Natural products as sources of herbicides: current status and future trends. Weed Res. 40:99–111.CrossRefGoogle Scholar
Flint, J. L., Cornelius, P. L., and Barrett, M. 1988. Analyzing herbicide interactions: a statistical treatment of Colby's method. Weed Technol. 2:304–309.CrossRefGoogle Scholar
Foes, M. J., Liu, J., Tranel, P. J., Wax, L. M., and Stoller, E. W. 1998. A biotype of common waterhemp (Amaranthus rudis) resistant to triazine and ALS herbicides. Weed Sci. 46:514–520.CrossRefGoogle Scholar
Gowing, D. P. 1960. Comments on tests of herbicide mixtures. Weeds. 8:379–391.CrossRefGoogle Scholar
Green, J. M., Jensen, J. E., and Streibig, J. C. 1997. Defining and characterizing synergism and antagonism for xenobiotic mixtures. Pages 263–274. in Hatzios, K. K. Regulation of Enzymatic Systems Detoxifying Xenobiotics in Plants. City, The Netherlands Kluwer Academic.CrossRefGoogle Scholar
Heap, I. 2007. The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed: September 5, 2007.Google Scholar
Kelly, T. L. W. and Chapman, P. F. 1995. The design and analysis of mixture experiments to meet different objectives: a practical summary. Aspects Appl. Biol. 41:51–59.Google Scholar
Kudsk, P. and Mathiassen, S. K. 2004. Joint action of amino acid biosynthesis-inhibiting herbicides. Weed. Res. 44:313–322.CrossRefGoogle Scholar
Lee, D. L., Knudsen, C. G., Michaely, W. J., Chin, H. L., Nguyen, N. H., Carter, C. G., Cromartie, T. H., Lake, B. H., Schribbs, J. M., and Fraser, T. 1998. The structure-activity relationships of the triketone class of HPPD herbicides. Pestic. Sci. 54:377–384.3.0.CO;2-0>CrossRefGoogle Scholar
Mitchell, G., Bartlett, D. W., Fraser, T. E. M., Hawkes, T. R., Holt, D. C., Townson, J. K., and Wichert, R. A. 2001. Mesotrione: a new selective herbicide for use in maize. Pest. Manag. Sci. 57:120–128.3.0.CO;2-E>CrossRefGoogle ScholarPubMed
Patzoldt, W. L., Tranel, P. J., and Hager, A. G. 2005. A waterhemp (Amaranthus tuberculatus) biotype with multiple resistance across three herbicide sites of action. Weed Sci. 53:30–36.CrossRefGoogle Scholar
[R] R Development Core Team 2005. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org.Google Scholar
Ritz, C. and Streibig, J. C. 2005. Bioassay analysis using R. J. Stat. Softw. 12 (5):1–22.CrossRefGoogle Scholar
[SAS] SAS Institute Inc 2004. SAS/STAT® 9.1 User's Guide. Cary, NC SAS Institute Inc. 5136. p.Google Scholar
Seefeldt, S. S., Jensen, J. E., and Fuerst, E. P. 1995. Log-logistic analysis of herbicide dose-response relationships. Weed Technol. 9:218–227.CrossRefGoogle Scholar
Streibig, J. C. and Jensen, J. E. 2000. Actions of herbicides in mixtures. Pages 153–180. in Cobb, A. H. and Kirkwood, R. C. Herbicides and Their Mechanisms of Action. Sheffield, England, UK Sheffield Academic.Google Scholar
Streibig, J. C., Kudsk, P., and Jensen, J. E. 1998. A general joint action model for herbicide mixtures. Pestic. Sci. 53:21–28.3.0.CO;2-L>CrossRefGoogle Scholar
Sutton, P., Richards, C., Buren, L., and Glasgow, L. 2002. Activity of mesotrione on resistant weeds in maize. Pest Manag. Sci. 58:981–984.CrossRefGoogle ScholarPubMed
Zhu, X., Govindjee, , Baker, N. R., deSturler, E., Ort, D. R., and Long, S. P. 2005. Chlorophyll a fluorescence induction kinetics in leaves predicted from a model describing each discrete step of excitation energy and electron transfer associated with photosystem II. Planta. 223:114–133.CrossRefGoogle Scholar