Hostname: page-component-7dd5485656-tbj44 Total loading time: 0 Render date: 2025-11-02T10:25:05.216Z Has data issue: false hasContentIssue false
  • English
  • Français

Economic evaluation of HADSS™ computer program for weed management in nontransgenic and transgenic cotton

Published online by Cambridge University Press:  20 January 2017

George H. Scott ,
Shawn D. Askew ,
Andrew C. Bennett  and
John W. Wilcut
George H. Scott
Affiliation:
Crop Science Department, Box 7620, North Carolina State University, Raleigh, NC 27695-7620
Shawn D. Askew
Affiliation:
Crop Science Department, Box 7620, North Carolina State University, Raleigh, NC 27695-7620
Andrew C. Bennett
Affiliation:
Crop Science Department, Box 7620, North Carolina State University, Raleigh, NC 27695-7620
Get access Rights & Permissions [Opens in a new window]

Abstract

Field studies were conducted at four locations in North Carolina in 1998 and 1999 to evaluate the use of the Herbicide Application Decision Support System (HADSS™) for weed management in nontransgenic, bromoxynil-resistant, and glyphosate-resistant cotton. Weed management systems included trifluralin preplant incorporated (PPI) plus fluometuron preemergence (PRE) or no soil-applied herbicides. Postemergence (POST) options included bromoxynil, glyphosate, or pyrithiobac early POST (EPOST) followed by (fb) MSMA plus prometryn late postemergence–directed (LAYBY) or herbicide recommendations given by HADSS. Glyphosate-resistant systems provided control equivalent to or better than control provided by bromoxynil-resistant and nontransgenic systems for smooth pigweed, Palmer amaranth, large crabgrass, goosegrass, ivyleaf morningglory, and fall panicum. Trifluralin PPI fb fluometuron PRE fb HADSS POST provided equivalent or higher levels of weed control and yield than trifluralin PPI fb fluometuron PRE fb bromoxynil, glyphosate, or pyrithiobac EPOST fb MSMA plus prometryn LAYBY. The trifluralin PPI fb fluometuron PRE fb HADSS POST systems controlled large crabgrass at Goldsboro and fall panicum better than HADSS POST-only systems in nontransgenic cotton. Cotton yield and net returns in the glyphosate-resistant systems were always equal to or higher than the nontransgenic and bromoxynil-resistant systems. Net returns were higher for the soil-applied fb HADSS POST treatments in 8 of 12 comparisons with HADSS POST systems without soil-applied herbicides. Early-season weed interference reduced cotton lint yields and net returns in POST-only systems.

Keywords

BromoxynilfluometuronglyphosateMSMAprometrynpyrithiobactrifluralincotton, Gossypium hirsutum L. ‘Deltapine 51’, ‘BXN 47’, ‘Deltapine 5415RR’fall panicum, Panicum dichotomiflorum Michx. PANDIgoosegrass, Eleusine indica (L.) Gaertn. ELEINivyleaf morningglory, Ipomoea hederacea (L.) Jacq. IPOHElarge crabgrass, Digitaria sanguinalis (L.) Scop. DIGSAPalmer amaranth, Amaranthus palmeri S. Wats. AMAPAsmooth pigweed, Amaranthus hybridus L. AMACHComputer decision aidsHERBherbicide-resistant crops

Information

Type
Research Article
Information
Weed Science , Volume 49 , Issue 4 , August 2001 , pp. 549 - 557
Copyright
Copyright © Weed Science Society of America 

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.)

Article purchase

Temporarily unavailable

References

Literature Cited

Anonymous. 1998. Summary of Annual Ownership Costs, Performance Rates, and Hourly Operation Costs by Machines, 1998 Field Crop Budgets. Raleigh, NC: North Carolina State University. 3 p.Google Scholar
Anonymous. 1999. Crop Protection Reference. 15th ed. New York: C & P Press. p. 1508.Google Scholar
Askew, S. D., Bailey, W. A., Wilcut, J. W., and Hinton, J. D. 1998. Weed control in cotton with different tillage systems and herbicide resistances. Proc. Beltwide Cotton Conf. 22:866.Google Scholar
Askew, S. D. and Wilcut, J. W. 1999. Cost and weed management with herbicide programs in glyphosate-resistant cotton (Gossypium hirsutum). Weed Technol. 13:308–313.Google Scholar
Askew, S. D., Wilcut, J. W., and Cranmer, J. 1999. Weed management in peanut (Arachis hypogaea) with flumioxazin and postemergence herbicides. Weed Technol. 13:594–598.Google Scholar
Brown, A. B. and Cole, T. 1997. Cotton: Estimated Revenue, Operating Expenses, Annual Ownership Costs, and Net Revenue Per Acre. Raleigh, NC: North Carolina State University Department of Agriculture and Resource Economics Budget 76-1. 3 p.Google Scholar
Buchanan, G. A. 1992. Trends in weed control methods. Pages 47–72 In McWhorter, C. G. and Abernathy, J. R., eds. Weeds of Cotton: Characterization and Control. Memphis, TN: The Cotton Foundation.Google Scholar
Buchanan, G. A. and Burns, E. R. 1970. Influence of weed competition on cotton. Weed Sci. 18:149–154.Google Scholar
Byrd, J. D. Jr., and York, A. C. 1987. Interaction of fluometuron and MSMA with sethoxydim and fluazifop. Weed Sci. 35:270–276.Google Scholar
Culpepper, A. S. and York, A. C. 1998. Weed management in glyphosate-tolerant cotton. Cotton Sci. 4:174–185.Google Scholar
Culpepper, A. S. and York, A. C. 1997. Weed management in no-tillage bromoxynil-tolerant cotton (Gossypium hirsutum). Weed Technol. 11:335–345.Google Scholar
Dotray, P. A., Keeling, J. W., Henniger, C. G., and Abernathy, J. R. 1996. Palmer amaranth (Amaranthus palmeri) and devil's-claw (Proboscidea louisianica) control cotton (Gossypium hisutum) with pyrithiobac. Weed Technol. 10:7–12.Google Scholar
Frans, R., Talbert, R., Marx, D., and Crowley, H. 1986. Experimental design and techniques for measuring and analyzing plant responses to weed control practices. Page 37 In Camper, N. D., ed. Research Methods in Weed Science. 3rd ed. Champaign, IL: Southern Weed Science Society.Google Scholar
Jordan, D. L., Coble, H. D., Brandenburg, R. L., and Bailey, J. E. 1998. Relationship of weed populations and HERB in selected North Carolina peanut fields. Proc. South. Weed Sci. Soc. 51:215–216.Google Scholar
Jordan, D. L., Frans, R. E., and McClelland, M. R. 1993. Total postemergence herbicide programs in cotton (Gossypium hirsutum) with sethoxydim and DPX-PE350. Weed Technol. 7:196–201.Google Scholar
Keeling, J. W., Siders, K. T., and Abernathy, J. R. 1991. Palmer amaranth (Amaranthus palmeri) control in a conservation tillage system for cotton (Gossypium hirsutum). Weed Technol. 5:137–141.Google Scholar
Light, G. G., Dotray, P. A., and Mahan, J. R. 1999. Thermal dependence of pyrithiobac efficacy in Amaranthus palmeri . Weed Sci. 47:644–650.Google Scholar
MacDonald, G. E., Bridges, D. C., and Brecke, B. J. 1998. Validation of HERB computer decision aid for peanuts. Proc. South. Weed Sci. Soc. 51:216.Google Scholar
Monks, C. D., Bridges, D. C., Woodruff, J. W., Murphy, T. R., and Berry, D. J. 1995. Expert system evaluation and implementation for soybean (Glycine max) weed management. Weed Technol. 5:535–540.Google Scholar
Mortensen, D. A. and Coble, H. D. 1991. Two approaches to weed control decision-aid software. Weed Technol. 5:445–452.Google Scholar
Paulsgrove, M. D. and Wilcut, J. W. 1999. Weed management in bromoxynil-resistant Gossypium hirsutum . Weed Sci. 47:596–601.Google Scholar
Rankins, A. Jr., Shaw, D. R., and Byrd, J. D. Jr. 1998. HERB and MSUHERB validation for soybean (Glycine max) weed control in Mississippi. Weed Technol. 12:88–96.Google Scholar
Retzinger, E. J. Jr., and Mallory-Smith, C. 1997. Classification of herbicides by site of action for weed resistance management strategies. Weed Technol. 11:384–393.Google Scholar
Scott, G. H., Askew, S. D., Wilcut, J. W., and Bailey, W. A. 1999. Command 3ME® and Roundup Ultra® for Roundup Ready® cotton. Proc. Beltwide Cotton Conf. 23:734.Google Scholar
Shaw, D. R., Rankins, A. Jr., Ruscoe, J. T., and Byrd, J. D. Jr. 1998. Field validation of weed control recommendations from HERB and SWC herbicide recommendation models. Weed Technol. 12:78–87.Google Scholar
Snipes, C. E. and Mueller, T. C. 1992. Cotton (Gossypium hirsutum) yield response to mechanical and chemical weed control systems. Weed Sci. 40:249–254.Google Scholar
White, A. D. and Coble, H. D. 1997. Validation for HERB use in peanut (Arachis hypogaea). Weed Technol. 11:73–579.Google Scholar
Wilcut, J. W. and Askew, S. D. 1999. Chemical approaches to weed management. Pages 627–661 In Ruberson, J. R., ed. Handbook of Pest Management. New York: Marcel Dekker.Google Scholar
Wilcut, J. W., Askew, S. D., Brecke, B. J., et al. 1999a. A beltwide evaluation of weed management in transgenic and nontransgenic cotton. Proc. Beltwide Cotton Conf. 23:746.Google Scholar
Wilcut, J. W., Hayes, R., and Askew, S. D. 1998. New weed management programs for weed control in no-till cotton. Proc. Beltwide Cotton Conf. 22:865.Google Scholar
Wilcut, J. W., Jordan, D. L., Vencill, W. K., and Richburg, J. S. III. 1997. Weed management in cotton (Gossypium hirsutum) with soil-applied and post-directed herbicides. Weed Sci. 11:221–226.Google Scholar
Wilcut, J. W., Scott, G. H., and Askew, S. D. 1999b. Evaluation of peanut HERB in North Carolina. Proc. South. Weed Sci. Soc. 52:67.Google Scholar
Wilcut, J. W., York, A. C., and Jordan, D. L. 1995. Weed management for oil seed crops. Pages 343–400 In Smith, A. E., ed. Handbook of Weed Management Systems. New York: Marcel Dekker.Google Scholar
Wilkerson, G. G., Coble, H. D., and Modena, S. A. 1991. HERB: decision model for postemergence weed control in soybean. Agron. J. 83:413–417.Google Scholar