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Stability of Corn (Zea mays)-Velvetleaf (Abutilon theophrasti) Interference Relationships

Published online by Cambridge University Press:  12 June 2017

John L. Lindquist ,
David A. Mortensen ,
Sharon A. Clay ,
Richard Schmenk ,
James J. Kells ,
Kirk Howatt  and
Philip Westra
John L. Lindquist
Affiliation:
Dep. Agron., Univ. Nebraska, Lincoln, NE 68583
David A. Mortensen
Affiliation:
Dep. Agron., Univ. Nebraska, Lincoln, NE 68583
Sharon A. Clay
Affiliation:
Dep. Agron., South Dakota State Univ., Brookings, SD 57007
Richard Schmenk
Affiliation:
Dep. Crop and Soil Sci., Michigan State Univ., East Lansing, MI 48824
James J. Kells
Affiliation:
Dep. Crop and Soil Sci., Michigan State Univ., East Lansing, MI 48824
Kirk Howatt
Affiliation:
Dep. Plant Path. and Weed Sci., Colorado State Univ., Fort Collins, CO 80523
Philip Westra
Affiliation:
Dep. Plant Path. and Weed Sci., Colorado State Univ., Fort Collins, CO 80523
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Abstract

The crop-weed interference relationship is a critical component of bioeconomic weed management models. Multi-year field experiments were conducted at five locations to determine the stability of corn-velvetleaf interference relationships across years and locations. Two coefficients (I and A) of a hyperbolic equation were estimated for each data set using nonlinear regression procedures. The I and A coefficients represent percent corn yield loss as velvetleaf density approaches zero, and maximum percent corn yield loss, respectively. The coefficient I was stable across years at two locations, but varied across years at one location. The coefficient A did not vary across years within locations. Both coefficients, however, varied among locations. Results do not support the use of common coefficient estimates for all locations within a region.

Keywords

Velvetleaf, Abutilon theophrasti Medik. ♯ ABUTHcorn, Zea mays L.Competitionbioeconomic modeleconomic thresholdintegrated weed management
Type
Weed Biology and Ecology
Information
Weed Science , Volume 44 , Issue 2 , June 1996 , pp. 309 - 313
Copyright
Copyright © 1996 by the Weed Science Society of America 

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References

Literature Cited

1. Bauer, T. A., Mortensen, D. A., Wicks, G. A., Hayden, T. A., and Martin, A. R. 1991. Environmental variability associated with economic thresholds for soybeans. Weed Sci. 39: 564–569.CrossRefGoogle Scholar
2. Bussler, B. H., Maxwell, B. D., and Puettmann, K. J. 1995. Using plant volume to quantify interference in corn (Zea mays) neighborhoods. Weed Sci. 43: 586–594.CrossRefGoogle Scholar
3. Coble, H. D. and Mortensen, D. A. 1992. The threshold concept and its application to weed science. Weed Technol. 6: 191–195.CrossRefGoogle Scholar
4. Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107: 239–252.CrossRefGoogle Scholar
5. Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Quart. 2: 13–20.Google Scholar
6. 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 weed emergence on crop yield. Weed Sci. 35: 720–725.CrossRefGoogle Scholar
7. Jordan, N. 1992. Weed demography and population dynamics: Implications for threshold management. Weed Technol. 6: 184–190.CrossRefGoogle Scholar
8. Kropff, M. J. and van Laar, H. H. 1993. Modelling crop-weed interactions. CAB International, Wallingford, UK.Google Scholar
9. Kropff, M. J. and Spitters, C. J. T. 1991. A simple model of crop loss by weed competition from early observations on relative leaf area of the weeds. Weed Res. 32: 437–450.CrossRefGoogle Scholar
10. Lindquist, J. L., Maxwell, B. D., Buhler, D. D., and Gunsolus, J. L. 1995. Velvetleaf (Abutilon theophrasti) recruitment, survival, seed production, and interference in soybean (Glycine max). Weed Sci. 43: 226–232.CrossRefGoogle Scholar
11. Lindquist, J. L., Maxwell, B. D., Buhler, D. D., and Gunsolus, J. L. 1995. Modeling the population dynamics and economics of velvetleaf (Abutilon theophrasti) control in a corn (Zea mays)—soybean (Glycine max) rotation. Weed Sci. 43: 269–275.CrossRefGoogle Scholar
12. Maxwell, B. D. 1992. Weed thresholds: The space component and considerations for herbicide resistance. Weed Technol. 6: 205–212.CrossRefGoogle Scholar
13. Ratkowsky, D. A. 1983. Pages 135–153 in Nonlinear regression modeling: a unified practical approach. Marcel Dekker, New York.Google Scholar
14. SAS Institute, Inc. 1988. SAS/STAT™ User's Guide, Release 6.03. SAS Inst., Inc., Cary, NC. 1028 pp.Google Scholar
15. Sattin, M., Zanin, G., and Berti, A. 1992. Case history for weed competition/population ecology: Velvetleaf (Abutilon theophrasti) in corn (Zea mays). Weed Technol. 6: 213–219.CrossRefGoogle Scholar
16. Snedecor, G. W. and Cochran, W. G. 1989. Pages 251–252 in Statistical methods. Iowa State Univ. Press, Ames, IA.Google Scholar
17. Swinton, S. M. and King, R. P. 1994. A bioeconomic model for weed management in corn and soybean. Agric. Sys. 44: 313–335.CrossRefGoogle Scholar
18. Swinton, S. M., Buhler, D. D., Forcella, F., Gunsolus, J. L., and King, R. P. 1994. Estimation of crop yield loss due to interference by multiple weed species. Weed Sci. 42: 103–109.CrossRefGoogle Scholar
19. Weaver, S. E. 1991. Size-dependent economic thresholds for three broadleaf weed species in soybeans. Weed Technol. 5: 674–679.CrossRefGoogle Scholar
20. 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