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Evaluation and Adaptation of the HADSS® Computer Program in Texas Southern High Plains Cotton

Published online by Cambridge University Press:  20 January 2017

Leanna L. Lyon ,
J. Wayne Keeling  and
Peter A. Dotray
Leanna L. Lyon
Affiliation:
Texas Agricultural Experiment Station, Rt. 3 Box 219, Lubbock, TX 79403
J. Wayne Keeling*
Affiliation:
Texas Agricultural Experiment Station, Rt. 3 Box 219, Lubbock, TX 79403
Peter A. Dotray
Affiliation:
Texas Agricultural Experiment Station, Rt. 3 Box 219, Lubbock, TX 79403
*
Corresponding author's E-mail: [email protected]
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Abstract

Field experiments were conducted in 1999 and 2000 to evaluate and adapt the Herbicide Application Decision Support System (HADSS®) program for Texas Southern High Plains cotton production. Weed management systems (in glyphosate-resistant, bromoxynil-resistant, and nontransgenic cotton varieties) included trifluralin preplant incorporated (PPI) followed by (fb) HADSS postemergence-topical (POST) recommendations (PPI fb POST HADSS), HADSS recommendations alone (POST HADSS), and Texas Agricultural Experiment Station (TAES) recommendations for the Texas Southern High Plains. In both years, effective season-long weed control was achieved with all weed management systems in the glyphosate-resistant variety, but only the PPI fb POST HADSS and TAES weed management systems controlled Palmer amaranth and devil's-claw in the bromoxynil-resistant and nontransgenic varieties, compared with POST HADSS alone. No differences in cotton lint yield or net returns over weed control costs were observed with weed management systems across variety in 1999; however, in general, the glyphosate-resistant and nontransgenic varieties produced higher yields and net returns than the bromoxynil-resistant variety. In 2000, plots from the TAES weed management system produced higher lint yields than the plots of PPI fb POST HADSS recommendations in the glyphosate- and bromoxynil-resistant varieties, but plots of all management systems yielded similarly in the nontransgenic variety. In 2000, plots from the TAES system produced the highest net returns in the glyphosate- and bromoxynil-resistant varieties. In the nontransgenic variety, the PPI fb POST HADSS and TAES weed management systems produced higher net returns over weed control costs than the POST HADSS system.

Keywords

BromoxynilglyphosatetrifluralinPalmer amaranth, Amaranthus palmeri S. Wats. # AMAPAdevil's-claw, Proboscidea louisianica (Mill.) Thellung # PROLOcotton, Gossypium hirsutum L. ‘Paymaster 2326RR’, ‘Stoneville BXN 47’, ‘Paymaster HS26’Computer decision aidherbicide-tolerant cottonHERBfb, followed byHADSS, Herbicide Application Decision Support SystemNHA, no herbicide applicationPDIR, postemergence directedPOST, postemergence topicalPPI, preplant incorporatedPRE, preemergenceTAES, Texas Agricultural Experiment Station
Type
Research
Information
Weed Technology , Volume 18 , Issue 2 , June 2004 , pp. 315 - 324
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Asher, B. S., Keeling, J. W., and Dotray, P. A. 2002. Weed management in transgenic and non-transgenic cotton (Gossypium hirsutum) in the Texas High Plains. Texas J. Agric. Nat. Resour. 15:27–36.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.CrossRefGoogle Scholar
Coble, H. D. and Mortensen, D. A. 1992. The threshold concept and its application to weed science. Weed Technol. 6:191–195.CrossRefGoogle 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 in cotton (Gossypium hirsutum) with pyrithiobac. Weed Technol. 10:7–12.CrossRefGoogle Scholar
Johnson, E. M. 1996. Roundup Ready™ gene in cotton. in Dugger, P. and Richter, D. A., eds. Proceedings of the Beltwide Cotton Conference. Memphis, TN: National Cotton Council of America. P. 51.Google Scholar
Jones, C. L., Keeling, J. W., Henniger, C. G., Abernathy, J. R., and Hake, K. A. 1994. Postemergence weed control in transgenic cotton with bromoxynil. Proc. South. Weed Sci. Soc. 47:55.Google Scholar
Keeling, J. W. and Dotray, P. A. 1997. Weed management in conservation tillage systems using Roundup Ultra in Roundup Ready cotton. in Dugger, P. and Richter, D. A., eds. Proceedings of the Beltwide Cotton Conference. Memphis, TN: National Cotton Council of America. P. 781.Google Scholar
McLaughlin, R. D. 1992. Reviews of the 1992 field trial results on bromoxynil-tolerant cotton. in Herber, D. J. and Richter, D. A., eds. Proceedings of the Beltwide Cotton Conference. Memphis, TN: National Cotton Conference of America. P. 1316.Google Scholar
Murdock, E. C. 1994. Weed control in bromoxynil-tolerant cotton. Proc. South. Weed Sci. Soc. 47:53.Google Scholar
Paulsgrove, M. D. and Wilcut, J. W. 1999. Weed management in bromoxynil-resistant Gossypium hirsutum . Weed Sci. 47:596–601.CrossRefGoogle Scholar
Rankins, A. Jr., Shaw, D. R., and Byrd, J. D. Jr. 1998. HERB and MSU-HERB field validation for soybean (Glycine max) weed control in Mississippi. Weed Technol. 12:88–96.CrossRefGoogle Scholar
Renner, K. A. and Black, J. R. 1991. SOYHERB: a computer program for soybean herbicide decision making. Agron. J. 83:921–925.CrossRefGoogle Scholar
Renner, K. A., Swinton, S. M., and Kells, J. J. 1999. Adaptation and evaluation of the WEEDSIM weed management model for Michigan. Weed Sci. 47:338–348.CrossRefGoogle Scholar
[SAS] Statistical Analysis Systems. 1988. SAS/STAT™ User's Guide. Release. 6.03 ed. Cary, NC: Statistical Analysis Systems Institute. Pp. 551–636.Google Scholar
Scott, G. H., Askew, S. D., Bennett, A. C., and Wilcut, J. W. 2001. Economic evaluation of HADSS™ computer program for weed management in nontransgenic and transgenic cotton. Weed Sci. 49:549–557.CrossRefGoogle Scholar
Scott, G. H., Askew, S. A., Wilcut, J. W., and Bailey, W. A. 1999a. Command 3ME and Roundup Ultra systems for Roundup Ready cotton. in Dugger, P. and Richter, D. A., eds. Proceedings of the Beltwide Cotton Conference. Memphis, TN: National Cotton Council of America. P. 734.Google Scholar
Scott, G. H., Wilcut, J. W., and Wilkerson, G. G. 1999b. Cotton HERB—A new decision-making tool for weed management in cotton. Proc. South. Weed Sci. Soc. 52:9.Google Scholar
Stigliani, L. and Resina, C. 1993. SELOMA: expert system for weed management in herbicide-intensive crops. Weed Technol. 7:550–559.CrossRefGoogle Scholar
Sturgill, M. C., Wilkerson, G. G., Coble, H. D., and Buol, G. S. 1997. HERB Version 7.0 User's Manual. Research Rep. 165. Raleigh, NC: Department of Crop Science, North Carolina State University.Google Scholar
Wilkerson, G. G., Modena, S. A., and Coble, H. D. 1991. HERB: decision model for postemergence weed control in soybean. Agron. J. 83:413–417.CrossRefGoogle Scholar