Skip to main content Accessibility help
×
Home

Canopy Measurements as Predictors of Weed-Crop Competition

  • J. I. Vitta (a1) and C. Fernandez Quintanilla (a2)

Abstract

The development of weed management systems requires accurate prediction of weed-crop competition. In this paper, simple regression models of crop yield losses based on weed density and weed leaf area are compared. In weed leaf area models, variations in the relative damage coefficient (q) were also analyzed. Finally, three simple methods to assess weed cover were compared: visual, photographic, and optic device assessment. Leaf area models were at least as accurate as weed density models. However, the generality of the leaf area models was restricted by changes in q, according to the date of leaf area evaluation and the year. Although all methods to assess weed cover correlated adequately with weed leaf area, visual estimates were the best to predict crop yield losses perhaps because very low levels of weed leaf area could be distinguished visually better than by other methods.

Copyright

References

Hide All
1. Baeumer, D. and de Wit, C. T. 1968. Competitive interference of plant species in monocultures and mixed stands. Neth. J. Agric. Sci. 16: 103122.
2. 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: 564569.
3. Christiensen, S. 1993. Electronic weed cover assessment. Pages 6370 in Proc. European Weed Res. Soc. Symp., Quantitative Approaches in Weed and Herbicide Research and their Practical Application.
4. Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107: 239252.
5. Firbank, L. G., Cousens, R., Mortimer, A. M., and Smith, R.G.R. 1990. Effects of soil type on crop yield-weed density relationships between winter wheat and Bromus sterilis . J. Appl. Ecol. 27: 308318.
6. Ghersa, C. M. and Martinez Ghersa, M. A. 1991. A field method for predicting yield losses in maize caused by johnsongrass (Sorghum halepense). Weed Technol. 5: 279285.
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: 97105.
8. Kropff, M. J. and Lotz, L.A.P. 1992. Optimization of weed management systems: the role of ecological models of interplant competition. Weed Technol. 6: 462467.
9. Kropff, M. J., Weaver, S. E., and Smits, M. A. 1992. Use of ecophysiological models for crop-weed interference: relation amongst weed density, relative time of weed emergence, relative leaf area, and yield loss. Weed Sci. 40: 296301.
10. Lotz, L.A.P., Kropff, M. J., and Groeneveld, R.M.W. 1993. The relative leaf cover model tested for practice. Pages 793798 in Proc. European Weed Res. Soc. Symp., Quantitative Approaches in Weed and Herbicide Research and their Practical Application.
11. Lotz, L.A.P., Kropff, M. J., Wallinga, J., Bos, H. J., and Groeneveld, R.M.W. 1994. Techniques to estimate relative leaf area and cover of weeds in crops for yield prediction. Weed Res. 34: 167175.
12. Lutman, P.J.W. 1992. Prediction of the competitive effects of weeds on the yields of several spring-sown arable crops. Pages 337344 in Proc. IXème Colloque International sur la Biologie dès Mauvaises Herbes.
13. Pike, D. R., Stoller, E. W., and Wax, L. M. 1990. Modeling soybean growth and canopy apportionment in weed-soybean (Glycine max) competition. Weed Sci. 38: 522527.
14. Streibig, J. C., Combellack, J. H., Pritchard, G. H., and Richardson, R. G. 1989. Estimation of thresholds for weed control in Australian cereals. Weed Res. 29: 117126.
15. Vitta, J. I., Satorre, E. H., and Leguizamón, E. S. 1994. Using canopy attributes to evaluate competition between Sorghum halepense (L.) Pers. and soybean. Weed Res. 34: 8997.

Keywords

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed