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Alfalfa (Medicago sativa) Seed Yield Loss Due to Canada Thistle (Cirsium arvense)

Published online by Cambridge University Press:  12 June 2017

James R. Moyer ,
G. Bruce Schaalje  and
Peter Bergen
James R. Moyer
Affiliation:
Agric. Can. Res. Stn., Lethbridge, AB, Canada T1J 4B1
G. Bruce Schaalje
Affiliation:
Agric. Can. Res. Stn., Lethbridge, AB, Canada T1J 4B1
Peter Bergen
Affiliation:
Alberta Sugar Company, Taber, AB, Canada T0K 2G0
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Abstract

Alfalfa seed yield and Canada thistle densities were measured in 10 fields in southern Alberta to assess the effect of thistles on seed yield. Thistle density and seed yield from each field were fitted to the Weibull, hyperbolic, and linear equations and a random coefficient and linear equation were used to obtain an “average yield loss curve”. Estimated average losses in alfalfa seed yield were >34% and >48% at thistle densities of 10 and 20 shoots m–2, respectively.

Keywords

Alfalfa, Medicago sativa (L.)Canada thistle, Cirsium arvense (L.) Scop. ♯ CIRARCompetitionnonlinear modelsWeibull equationhyperbolic equationrandom coefficient model
Type
Research
Information
Weed Technology , Volume 5 , Issue 4 , December 1991 , pp. 723 - 728
Copyright
Copyright © 1990 by the Weed Science Society of America 

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References

Literature Cited

1. 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
2. Dew, D. A. 1972. An index of competition for estimating crop loss due to weeds. Can. J. Plant Sci. 52:921–927.CrossRefGoogle Scholar
3. Gallant, A. R. 1987. Nonlinear Statistical Models. John Wiley and Sons Inc., New York. p. 55–56.Google Scholar
4. Gumpertz, M., and Pantula, S. G. 1989. A simple approach to interference in random coefficient models. Am. Statis. 13:203–210.Google Scholar
5. Lindstrom, M. J., and Bates, D. M. 1990. Nonlinear mixed effects models for repeated measures data. Biometrics 46:673–687.CrossRefGoogle ScholarPubMed
6. Marriage, P. B. 1985. Canada thistle [Cirsium arvense (L.) Scop.]. Agdex 642, Ont. Ministry Agriculture and Food, Guelph, ON.Google Scholar
7. Morrison, I. 1980. Controlling Canada thistle. Agdex 640, Man. Agric., Winnipeg, MB.Google Scholar
8. Moyer, J. R., Richards, K. W., and Schaalje, G. B. 1991. Effect of plant density and herbicide application on alfalfa and weed yields. Can. J. Plant Sci. 71:481–489.CrossRefGoogle Scholar
9. O'Donovan, J. T., Ann de St. Remy, E., O'Sullivan, P. A., Dew, D. A., and Sharma, A. K. 1985. Influence of the relative time of emergence of wild oat (Avena fatua) on the yield loss of barley (Hordeum vulgare) and wheat (Triticum aestivum). Weed Sci. 33:498–503.CrossRefGoogle Scholar
10. O'Sullivan, P. A., Kossatz, V. C., Weiss, G. M., and Dew, D. A. 1982. An approach in estimating yield loss of barley due to Canada thistle. Can. J. Plant Sci. 62:725–731.Google Scholar
11. O'Sullivan, P. A., Weiss, G. M., and Kossatz, V. C. 1985. Indices of competition for estimating rapeseed yield loss due to Canada thistle. Can. J. Plant Sci. 65:145–149.CrossRefGoogle Scholar
12. Peschken, D. P., Thomas, A. G., and Wise, R. F. 1983. Loss in yield of rapeseed (Brassica napus, B. campestrus) caused by perennial sow thistle (Sonchus arvensis) in Saskatchewan and Manitoba. Weed Sci. 31:740–744.CrossRefGoogle Scholar
13. Racine-Poon, A. 1985. Bayesian approach to nonlinear random effects models. Biometrics 41:1015–1023.Google Scholar
14. Rawlings, J. O., and Cure, W. W. 1985. The Weibull function as a dose-response model to describe ozone effects on crop yields. Crop Sci. 25:807–814.CrossRefGoogle Scholar
15. Roush, M. L., Radosevich, S. R., Wagner, R. G., Maxwell, B. D., and Petersen, T. D. 1989. A comparison of methods for measuring effects of density and proportion in plant competition experiments. Weed Sci. 37:268–275.Google Scholar
16. Stahlman, P. W., and Miller, S. D. 1990. Downy brome (Bromus tectorum) interference and economic thresholds in winter wheat (Triticum aestivum). Weed Sci. 38:224–228.Google Scholar