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Datura stramonium interference and seed rain in Gossypium hirsutum

Published online by Cambridge University Press:  20 January 2017

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
Cavell Brownie
Affiliation:
Department of Statistics, Box 8203, North Carolina State University, Raleigh NC 27695-8203

Abstract

Experiments were conducted in 1998 and 1999 at the Central Crops Research Station near Clayton, NC, to evaluate density-dependent effects of Datura stramonium on weed growth and seed rain and Gossypium hirsutum growth and yield. Datura stramonium height was not affected by density in either year. Crop height never exceeded weed height during the growing season, indicating that competition for light occurred between the two species. Eight weeks after planting or later, G. hirsutum height decreased as D. stramonium density increased. An increase in D. stramonium density from 1 to 32 plants (9.1 m of row)−1 resulted in a decrease in capsule production per plant of 92 and 60 in 1998 and 1999, respectively. Total D. stramonium dry weight per 9.1 m of row increased via a quadratic relationship as weed density increased. Gossypium hirsutum lint yields decreased as D. stramonium biomass and density increased in both years. Estimated yield losses of 10 and 25% were caused by D. stramonium at 0.5 and 1.5 plants (9.1 m of row)−1 (572 and 1,716 plants ha−1), respectively, in 1998 and 0.6 and 1.8 plants (9.1 m of row)−1 (690 and 2,060 plants ha−1), respectively, in 1999.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

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References

LITERATURE CITED

Anonymous. 1998. Summary of annual ownership Costs, performance rates, and hourly operation costs by machines. Pages 13 In 1998 Field Crop Budgets. Raleigh, NC: North Carolina State University.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. 13:308313.Google Scholar
Askew, S. D. and Wilcut, J. W. 2000. Tropic croton interference in cotton and peanut. Weed Sci. Soc. Am. Abst. 40:135.Google Scholar
Askew, S. D., Wilcut, J. W., Bailey, W. A., and Scott, G. H. 1999a. Interference and seed-rain dynamics of four Polygonum species in cotton. Proc. South. Weed Sci. Soc. 52:177.Google Scholar
Askew, S. D., Wilcut, J. W., Bailey, W. A., and Scott, G. H. 1999b. Weed management in conventional and no-tillage cotton using BXN®, Roundup Ready®, and Staple® OT systems. Proc. Beltwide Cotton Conf. 23:743.Google Scholar
Bauer, T. A. and Mortensen, D. A. 1992. A comparison of economic and economic optimum thresholds for two annual weeds in soybean. Weed Technol. 6:228235.Google Scholar
Bridges, D. C., Brecke, B. J., and Barbour, J. C. 1992. Wild poinsettia (Euphorbia heterophylla) interference with peanut (Arachis hypogaea). Weed Sci. 40:3742.Google Scholar
Bridges, D. C. and Chandler, J. M. 1987. Influence of johnsongrass (Sorghum halepense) density and period of competition on cotton yield. Weed Sci. 35:6367.Google Scholar
Buhler, D. D., Hartzler, R. G., and Forcella, F. 1997. Implications of weed seedbank dynamics to weed management. Weed Sci. 45:329336.Google Scholar
Byrd, J. D. Jr., and Coble, H. D. 1991. Interference of selected weeds in cotton (Gossypium hirsutum). Weed Technol. 5:263269.CrossRefGoogle Scholar
Cavers, P. B. 1983. Seed demography. Can. J. Bot. 61:35783590.CrossRefGoogle Scholar
Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107:239252.Google Scholar
Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Q. 2:1320.Google Scholar
Cousens, R., Brain, P., O’Donovan, J. T., and O’Sullivan, A. 1987. The use of biologically realistic equations to describe the effects of weed density and relative time of emergence on crop yield. Weed Sci. 35:720725.Google Scholar
Czapar, G. F., Curry, M. P., and Wax, L. M. 1997. Grower acceptance of economic thresholds for weed management in Illinois. Weed Technol. 11:828831.Google Scholar
Dowler, C. C. 1998. Weed survey—southern states. Proc. South. Weed Sci. Soc. 51:250275.Google Scholar
Frazee, R. W. and Stoller, E. W. 1974. Differential growth of corn, soybean, and seven dicotyledonous weed seedlings. Weed Sci. 22:336339.CrossRefGoogle Scholar
Hagood, E. S. Jr., Bauman, T. T., Williams, J. L. Jr., and Schreiber, M. 1981. Growth analysis of soybean (Glycine max) in competition with jimsonweed (Datura stramonium). Weed Sci. 29:500504.CrossRefGoogle Scholar
Keeley, P. E. and Thullen, R. J. 1978. Light requirements of yellow nutsedge (Cyperus esculentus) and light interception by crops. Weed Sci. 29:500504.Google Scholar
Mitich, L. W. 1989. Jimsonweed. Weed Technol. 3:208210.Google Scholar
Oliver, L. R., Chandler, J. M., and Buchanan, G. A. 1991. Influence of geographic region on jimsonweed (Datura stramonium) interference in soybean (Glycine max) and cotton (Gossypium hirsutum). Weed Sci. 39:585589.Google Scholar
Patterson, D. T. and Flint, E. P. 1983. Comparative water relations, photosynthesis, and growth of soybean (Glycine max) and seven associated weeds. Weed Sci. 31:318323.Google Scholar
Rushing, D. W., Murray, D. S., and Verhalen, L. M. 1985. Weed interference with cotton (Gossypium hirsutum). II. tumble pigweed (Amaranthus albus). Weed Sci. 33:815818.Google Scholar
Sartorato, I., Berti, A., and Zanin, G. 1996. Estimation of economic thresholds for weed control in soybean [Glycine max (L.) Merr.]. Crop Prot. 15:6368.CrossRefGoogle Scholar
[SAS] Statistical Analysis Systems. 1998. SAS/STAT® User's Guide. Release 7.00. Cary, NC: Statistical Analysis Systems Institute. 1,028 p.Google Scholar
Senseman, S. A. and Oliver, L. R. 1993. Flowering patterns, seed production, and somatic polymorphism of three weed species. Weed Sci. 41:418425.Google Scholar
Smith, B. S., Murray, D. S., and Weeks, D. L. 1990a. Velvetleaf (Abutilon theophrasti) interference with cotton. Weed Technol. 4:799803.Google Scholar
Smith, B. S., Pawlak, J. A., Murray, D. S., Verhalen, L. M., and Green, J. D. 1990b. Interference from established stands of silverleaf nightshade (Solanum elaeagnifolium) on cotton (Gossypium hirsutum) lint yield. Weed Sci. 38:129133.Google Scholar
Snipes, C. E., Buchanan, G. A., Street, J. E., and McGuire, J. A. 1982. Competition of common cocklebur (Xanthium pensylvanicum) with cotton (Gossypium hirsutum). Weed Sci. 30:553556.Google Scholar
Stoller, E. W. and Woolley, J. T. 1985. Competition for light by broadleaf weeds in soybean (Glycine max). Weed Sci. 33:199202.CrossRefGoogle Scholar
Wilcut, J. W. and Askew, S. D. 1999. Chemical approaches to weed management. Pages 627661 In Ruberson, J. R., ed. Handbook of Pest Management. New York: Marcel Dekker.Google Scholar
Wilcut, J. W., Coble, H. D., York, A. C., and Monks, D. W. 1996. The niche for herbicide-resistant crops in U.S. agriculture. Pages 213230 In Duke, S. O., ed. Herbicide-Resistant Crops: Agricultural, Environmental, Economic, Regulatory, and Technical Aspects. New York: CRC and Lewis.Google Scholar
Wilcut, J. W., York, A. C., and Jordan, D. L. 1995. Weed management systems for oil seed crops. Pages 343400 In Smith, A. E., ed. Handbook of Weed Management Systems. New York: Marcel-Dekker.Google Scholar