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Differential Response of Fall Panicum (Panicum dichotomiflorum) Populations in Florida Sugarcane to Asulam

Published online by Cambridge University Press:  21 November 2018

Jose V. Fernandez ,
D. Calvin Odero ,
Gregory E. MacDonald ,
Jason A. Ferrell ,
Brent A. Sellers  and
P. Christopher Wilson
Jose V. Fernandez
Affiliation:
Graduate Student, Agronomy Department, University of Florida, Gainesville, FL, USA
D. Calvin Odero*
Affiliation:
Associate Professor, Everglades Research and Education Center, University of Florida, Belle Glade, FL, USA
Gregory E. MacDonald
Affiliation:
Professor, Agronomy Department, University of Florida, Gainesville, FL, USA
Jason A. Ferrell
Affiliation:
Professor, Agronomy Department, University of Florida, Gainesville, FL, USA
Brent A. Sellers
Affiliation:
Professor, Rangeland Cattle Research and Education Center, University of Florida, Ona, FL, USA
P. Christopher Wilson
Affiliation:
Professor, Soil and Water Sciences Department, University of Florida, Gainesville, FL, USA
*
Author for correspondence: D. Calvin Odero, Everglades Research and Education Center, University of Florida, 3200 E. Palm Beach Road, Belle Glade, FL 33430. (Email: dcodero@ufl.edu)
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Abstract

Sugarcane growers in Florida have been reporting reduced control of fall panicum with asulam, the main herbicide used for POST grass control. Therefore, outside container experiments were conducted to determine the response of four fall panicum populations from Florida to asulam applied alone and to evaluate whether tank-mix combination with trifloxysulfuron enhances control. Asulam was applied at 230 to 7,400 g ai ha−1, corresponding to 1/16 to 2X the maximum labeled rate for a single application in sugarcane, with or without combination with trifloxysulfuron at 16 g ai ha−1. Three fall panicum populations were collected from fields in which reduced control had been reported, while one population was from a field not used for sugarcane production but adjacent to a sugarcane field. The potency of asulam based on ED50 values (the rate required to cause 50% dry weight reduction at 28 d after treatment) ranged from 2,249 to 5,412 g ha−1 for tolerant populations with reported reduced fall panicum control compared with 1,808 g ha−1 for the susceptible population from the field not used for sugarcane production, showing that the latter was most sensitive to asulam. Addition of trifloxysulfuron to asulam increased potency on fall panicum by 5- to 15-fold, indicating that the tank mix enhanced dry weight reduction for all populations. The probability of fall panicum survival (regrowth after aboveground biomass harvesting) at the labeled rate of asulam ranged from 2% to 47% compared with 0% to 6% when trifloxysulfuron was added to the tank mix. Our results show differential response of fall panicum populations in Florida to asulam, which can be overcome by tank mixing with trifloxysulfuron even for populations that are difficult to control in sugarcane, but no evolution of resistance to asulam.

Keywords

Mark VanGessel, University of DelawareAsulamtrifloxysulfuronfall panicumPanicum dichotomiflorum Michx. PANDIsugarcane, Saccharum spp.Herbicide resistanceherbicide tolerancesugarcanetank mix
Type
Note
Information
Weed Technology , Volume 32 , Issue 6 , December 2018 , pp. 762 - 767
Copyright
© Weed Science Society of America, 2018. 

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References

Anonymous (2018a) Archived SFWMD Station Data. University of Florida/IFAS and the South Florida Water Management District. http://erec.ifas.ufl.edu/WD/Ewdmain.htm. Accessed: February 9, 2018Google Scholar
Anonymous (2018b) Asulox® H herbicide. United Phosphorus. http://www.upi-usa.com/agricultural-products/asulox. Accessed: February 9, 2018Google Scholar
Anonymous (2018c) Envoke® herbicide. Syngenta Crop Protection. http://www.syngenta-us.com/herbicides/envoke. Accessed: February 9, 2018Google Scholar
Brecke, BJ, Duke, WB (1980) Dormancy, germination, and emergence characteristics of fall panicum (Panicum dichotomiflorum) seed. Weed Sci 28:683–685 Google Scholar
Bryson, CT, DeFelice, MS (2009) Weeds of the South. Athens, GA: University of Georgia Press. 395 pGoogle Scholar
Busi, R, Gaines, TA, Walsh, MJ, Powles, SB (2011) Understanding the potential for resistance evolution to the new herbicide pyroxasulfone: field selection at high dose versus recurrent selection at low doses. Weed Res 52:489–499 Google Scholar
Dalley, CD, Richard, EP (2008) Control of rhizome johnsongrass (Sorghum halepense) insugarcane with trifloxysulfuron and asulam. Weed Technol 22:397–401 Google Scholar
Fausey, JC, Renner, KA (1997) Germination, emergence, and growth of giant foxtail (Setaria faberi) and fall panicum (Panicum dichotomiflorum). Weed Sci 45:423–425 Google Scholar
Govinthasamy, K, Cavers, PB (1995) The effects of smut (Ustilago destruens) on seed production, dormancy, and viability in fall panicum (Panicum dichotomiflorum). Can J Bot 73:1628–1634 Google Scholar
Heap, I (2018) The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed: February 6, 2018Google Scholar
Hossain, MA, Kuramochi, H, Ishimine, Y, Akamine, H (2001) Application timing of asulam for torpedograss (Panicum repens L.) control in sugarcane in Okinawa island. Weed Bio and Manag 1:108–114 Google Scholar
Neve, P, Powles, S (2005) Recurrent selection with reduced herbicide rates results in the rapid evolution of herbicide resistance in Lolium rigidum . Theor Appl Genet 110:1154–1166 Google Scholar
Odero, DC, Duchrow, M, Havranek, N (2016) Critical timing of fall panicum (Panicum dichotomiflorum) removal in sugarcane. Weed Technol 30:13–20 Google Scholar
Odero, DC, Dusky, JA (2014) Weed Management in Sugarcane. EDIS Publication SS-AGR-09. http://edis.ifas.ufl.edu/wg04. Accessed: March 20, 2017Google Scholar
Odero, DC, Sellers, B, Baucum, L, Curtis, R (2014) Fall Panicum: Biology and Control in Sugarcane. EDIS Publication SS-AGR-132. http://edis.ifas.ufl.edu/sc079. Accessed: March 20, 2017Google Scholar
Odero, DC, Shaner, DL (2014) Dissipation of pendimethalin in organic soils in Florida. Weed Technol 28:82–88 Google Scholar
R Core Team (2017) R: A Language and Environment for Statistical Computing. Vienna: Austria: R Foundation for Statistical Computing. http://www.R-project.org Google Scholar
Richard, EP (1991) Optimizing diluent volume improves Johnsongrass control in sugarcane (Saccharum sp.) with asulam. Weed Technol 5:363–368 Google Scholar
Ritz, C, Kniss, AR, Streibig, JC (2015) Research methods in weed science: statistics. Weed Sci 63(SP1):166–187 Google Scholar
Ritz, C, Streibig, JC (2005) Bioassay analysis using R. J Stat Sofw 12:1–22 Google Scholar
Seefeldt, SS, Jensen, JE, Fuerst, EP (1995) Log-logistic analysis of herbicide dose-response relationships. Weed Technol 9:21 Google Scholar
Teuton, TC, Unruh, JB, Brecke, BJ, MacDonald, GE, Miller, GL, Ducar, JT (2004) Tropical signalgrass (Urochloa subquadripara) control with preemergence- and postemergence-applied herbicides. Weed Technol 18:419–425 Google Scholar
[USDA-NASS] U.S. Department of Agriculture–National Agricultural Statistics Service (2018) Crop Production. https://www.nass.usda.gov/Quick_Stats/Lite/result.php?88899F9B-2FA5-35AA-94BE-E6AB971FD906. Accessed: February 6, 2018Google Scholar
VanWeelden, M, Swanson, S, Davidson, W, Rice, R (2017) Sugarcane variety census. Florida 2016. Sugar J July:12–25Google Scholar
Venables, WN, Ripley, BD (2002) Modern Applied Statistics with S. 4th ed. New York: Springer. 495 pGoogle Scholar