Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-30T19:56:36.215Z Has data issue: false hasContentIssue false
  • English
  • Français

Tank contamination with dicamba and 2,4-D influences dry edible bean

Published online by Cambridge University Press:  24 September 2019

Scott R. Bales  and
Christy L. Sprague Open the ORCID record for Christy L. Sprague [Opens in a new window]
Scott R. Bales
Affiliation:
Graduate Student
Christy L. Sprague*
Affiliation:
Professor, Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA.
*
Author for correspondence: Christy L. Sprague, Professor, Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, East Lansing, MI 48824. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The occurrence of herbicide tank contamination with dicamba or 2,4-D will likely increase with the recent commercialization of dicamba- and 2,4-D-resistant soybean. High-value sensitive crops, including dry bean, will be at higher risks for exposure. In 2017 and 2018, two separate field experiments were conducted in Michigan to understand how multiple factors may influence dry bean response to dicamba and 2,4-D herbicides, including 1) the interaction between herbicides applied POST to dry bean and dicamba or 2,4-D, and 2) the impact of low rates of glyphosate with dicamba or 2,4-D. Dry bean injury was 20% and 2% from POST applications of dicamba (5.6 h ae ha−1) and 2,4-D (11.2 g ae ha−1), respectively, 14 days after treatment (DAT). The addition of glyphosate (8.4 g ae ha−1) did not increase dry bean injury from dicamba or 2,4-D. Over 2 site-years the addition of dry bean herbicides to dicamba or dicamba + glyphosate (8.4 g ae ha−1) increased dry bean injury and reduced yield by 6% to 10% more than when dicamba or dicamba + glyphosate was applied alone. The interaction between 2,4-D (11.2 g ae ha−1) and dry bean herbicides was determined to be synergistic. However, 2,4-D (11.2 g ae ha−1) had little effect on dry bean with or without the addition of a dry bean herbicide program. These studies document that synergy also occurs between dicamba and dicamba + glyphosate and both common dry bean herbicide programs tested: 1) imazamox (35 g ha−1) + bentazon (560 g ha−1), and 2) fomesafen (280 g ha−1). The synergy between dry bean herbicide and dicamba and dicamba + glyphosate can increase plant injury, delay maturity, and reduce yield to a greater extent than dicamba or dicamba + glyphosate alone. This work emphasizes the need to properly clean out sprayers after applications of dicamba to reduce the risk of exposure to other crops.

Keywords

Lawrence E. Steckel, University of Tennessee2,4-D cholinedicambadry beanPhaseolus vulgaris L.2,4-D-resistant soybeanblack beandicamba-resistant soybeanspray tank-contamination
Type
Research Article
Information
Weed Technology , Volume 34 , Issue 1 , February 2020 , pp. 89 - 95
Copyright
© Weed Science Society of America, 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anonymous (2014) Reflex herbicide product label. Greensboro, NC: Syngenta, Research. 50 pGoogle Scholar
Anonymous (2015) Raptor herbicide product label. Research Triangle Park, NC: BASF Corporation. 26 pGoogle Scholar
Bauer, TA, Renner, KA, Penner, D, Kelly, JK (1995) Pinto bean (Phaseolus vulgaris) varietal tolerance to imazethapyr. Weed Sci 43:417–424CrossRefGoogle Scholar
Behrens, MR, Mutlu, N, Chakraborty, S, Dumitru, R, Jiang, W Z, LaVallee, BJ, Weeks, DP (2007) Dicamba resistance: enlarging and preserving biotechnology-based weed management strategies. Science 316:1185–1188CrossRefGoogle ScholarPubMed
Blackshaw, RE, Saindon, G (1996) Dry bean (Phaseolus vulagris) tolerance to imazethapyr. Can J Plant Sci 76:915–919CrossRefGoogle Scholar
Boerboom, C (2004) Field case studies of dicamba movement to soybeans. In Wisconsin Crop Management Conference: 2004 Proceedings Papers. Madison, WI: University of Wisconsin-MadisonGoogle Scholar
Brown, LR, Robinson, DE, Nurse, RE, Swanton, CJ, Sikkema, PH (2009) Soybean response to simulated dicamba/diflufenzopyr drift followed by postemergence herbicides. Crop Prot 28:539–542CrossRefGoogle Scholar
Christenson, DR, Brimhall, PB, Hubbell, L, Bricker, CE (2000) Yield of sugar beet, soybean, corn, field bean, and wheat as affected by lime application on alkaline soils. Comm Soil Sci Plant Anal 31:1145–1154CrossRefGoogle Scholar
Egan, JF, Barlow, KM, Martensen, DA (2014) A meta-analysis on the effects of 2,4-D and dicamba drift on soybean and cotton. Weed Sci 62:193–206CrossRefGoogle Scholar
Fageria, NK, Santos, AB (2008) Yield physiology of dry bean. J Plant Nutr 31:983–1004CrossRefGoogle Scholar
Gowing, DP (1960) Comments on test of herbicide mixtures. Weeds 8:379–391CrossRefGoogle Scholar
Hatterman-Valenti, H, Endres, G, Jenks, B, Ostlie, M, Reinhardt, T, Robinson, A, Stenger, J, Zollinger, R (2017) Defining glyphosate and dicamba drift injury to dry edible pea, dry edible bean, and potato. Hort Technol 27:502–509CrossRefGoogle Scholar
Kelley, KB, Wax, LM, Hager, AG, Riechers, DE (2005) Soybean response to plant growth regulator herbicides is affected by other postemergence herbicides. Weed Sci 53:101–112CrossRefGoogle Scholar
Kelly, JD, Cichy, KA (2013) Dry bean breeding and production technologies. Pages 23–54 in Siddiq, M. and Uebersax, M., eds. Dry beans and pulses production, processing and nutrition. Ames, IA: John Wiley & SonsGoogle Scholar
Knezevic, SZ, Streibig, JC, Ritz, C (2007) Utilizing R software package for dose-response studies: the concept and data analysis. Weed Technol 21:840–848CrossRefGoogle Scholar
Lyon, DJ, Wilson, RG (1986) Sensitivity of fieldbeans (Phaseolus vulgaris) to reduced rates of 2,4-D and dicamba. Weed Sci 34:953–956CrossRefGoogle Scholar
Osborne, PP, Xu, Z, Swanson, KD, Walker, T, Farmer, DK (2015) Dicamba and 2, 4-D residues following applicator cleanout: A potential point source to the environment and worker exposure. JAPCA 65:1153–1158Google ScholarPubMed
Probst, MA (2018) Effects of Tank-Contamination with Dicamba and 2, 4-D on Sugarbeet. MS Thesis, Michigan State University, 2018Google Scholar
R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Accessed: August 18, 2018Google Scholar
Soltani, N, Shropshire, C, Cowan, T, Sikkema, P (2017) Tolerance of black beans (Phaseolus vulgaris) to soil applications of s-metolachlor and imazethapyr. Weed Technol 18:111–118CrossRefGoogle Scholar
Sprague, CL, Burns, EE (2018) Weed control guide for field crops. Michigan State University Extension Bulletin E-434, East Lansing, MIGoogle Scholar
[USDA-NASS] US Department of Agriculture, National Agricultural Statistics Service (2018) Crop Production 2017 Summary. https://quickstats.nass.usda.gov/results/BD70E5AE-8384-3B19-9B5F-01A972736DFC. Accessed: August 18, 2018Google Scholar
Wilson, R (2005) Response of dry bean and weeds to fomesafen and fomesafen tank mixtures. Weed Technol 19:201–206CrossRefGoogle Scholar
Wright, TR, Shan, G, Walsh, TA, Lira, JM, Cui, C, Song, P, Zhuang, M, Arnold, NL, Lin, G, Yau, K, Russel, SM, Cicchillo, RM, Peterson, MA, Simpson, DM, Zhou, N, Ponsamuel, J, Zhang, Z (2010) Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate dioxygenase transgenes. Proc Natl Acad Sci USA 107:20240–20245CrossRefGoogle ScholarPubMed