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Size-Dependent Economic Thresholds for Three Broadleaf Weed Species in Soybeans

Published online by Cambridge University Press:  12 June 2017

Susan E. Weaver
Susan E. Weaver*
Affiliation:
Agric. Can. Res. Stn., Harrow, Ont., Can. NOR 1G0
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Abstract

Soybean seed yield losses due to interference from common cocklebur, velvetleaf, and jimsonweed, with and without a PPI application of 0.42 kg ai ha-1 metribuzin, were determined in 1986, 1987, and 1988. Damage functions were calculated based on weed density, weed leaf density, and relative weed leaf area index, respectively. Functions relating crop yield losses to weed density varied significantly among treatments and years for each species. Weeds which escaped soil-applied metribuzin were shorter with fewer leaves at 3 wk after planting, and caused lower crop yield losses than control plants at equal densities. Yield loss estimates based upon relative weed leaf area at 3 wk after planting showed least variation between years and treatments.

Keywords

Metribuzin, 4-ammo-6-(1,1-dimethylethyl)-3-(methylthio)-1,2,4-triazine-5(4H)-onesoybean, Glycine max (L.) Merr. ‘Premier’common cocklebur, Xanthium strumarium L. ♯ XANSTjimsonweed, Datura stramonium L. ♯ DATSTvelvetleaf, Abutilon theophrasti Medik. ♯ ABUTHAbutilon theophrastiDatura stramoniumXanthium strumariumABUTHDATSTXANST

Information

Type
Symposium
Information
Weed Technology , Volume 5 , Issue 3 , September 1991 , pp. 674 - 679
Copyright
Copyright © 1991 Weed Science Society of America 

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References

Literature Cited

1. Adcock, T. E., and Banks, P. A. 1991. Effects of preemergence herbicides on the competitiveness of selected weeds. Weed Sci. 39: 54–56.Google Scholar
2. Adcock, T. E., Banks, P. A., and Bridges, D. C. 1990. Effects of preemergence herbicides on soybean (Glycine max): weed competition. Weed Sci. 38:108–112.Google Scholar
3. Aldrich, R. J. 1987. Predicting crop yield reductions from weeds. Weed Technol. 1:199–206.Google Scholar
4. Cousens, R. 1985. An empirical model relating crop yield to weed and crop density and a statistical comparison with other models. J. Agric. Sci. 105:513–521.Google Scholar
5. Cousens, R., Brain, P., O'Donovan, J. T., and O'Sullivan, P. 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. 35:720–725.Google Scholar
6. Kropff, M. 1988. Modelling the effects of weeds on crop production. Weed Res. 28:465–471.Google Scholar
7. 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. 31:97–105.CrossRefGoogle Scholar
8. Little, T. M., and Hills, F. J. 1978. Agricultural Experimentation. John Wiley and Sons, New York. 350 p.Google Scholar
9. Mortensen, D. A., and Coble, H. D. 1989. The influence of soil water content on common cocklebur (Xanthium strumarium) interference in soybeans (Glycine max). Weed Sci. 37:76–83.CrossRefGoogle Scholar
10. Pike, D. R., Stoller, E. W., and Wax, L. M. 1990. Modelling soybean growth and canopy apportionment in weed-soybean (Glycine max) competition. Weed Sci. 38:522–527.Google Scholar
11. Spitters, C.J.T., and Aerts, R. 1983. Simulation of competition for light and water in crop weed associations. Aspects Appl. Biol. 4:467–484.Google Scholar
12. Weaver, S. E., Smits, N., and Tan, C. S. 1987. Estimating yield losses of tomatoes (Lycopersicon esculentum) caused by nightshade (Solanum spp.) interference. Weed Sci. 35:163–168.Google Scholar