Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-14T23:22:37.299Z Has data issue: false hasContentIssue false
  • English
  • Français

A Field Method for Predicting Yield Losses in Maize Caused by Johnsongrass (Sorghum halepense)

Published online by Cambridge University Press:  12 June 2017

Claudio M. Ghersa  and
Maria A. Martinez-Ghersa
Claudio M. Ghersa
Affiliation:
Oregon State Univ., Corvallis, OR 97331-5705
Maria A. Martinez-Ghersa
Affiliation:
Oregon State Univ., Corvallis, OR 97331-5705
Get access Rights & Permissions [Opens in a new window]

Abstract

The objective of this research was to modify the senior author's previously developed method for predicting yield losses in maize crops attributable to johnsongrass. The new method is based on the following assumptions: a) relative leaf frequency determines relative biomass; b) total biomass is constant despite the crop/weed ratio; and c) biomass, and therefore leaf frequency, are related to grain yield. Experiments in Argentina from 1986 to 1989 supported the above hypotheses, and the new method was more accurate than the old for predicting relative species biomass in johnsongrass/maize mixtures. Maize grain yield reductions associated with weed interference were also more accurately predicted.

Keywords

Maize, Zea mays L.johnsongrass, Sorghum halepense (L.) Pers. ♯ SORHAJohnsongrassyield lossesprediction
Type
Research
Information
Weed Technology , Volume 5 , Issue 2 , June 1991 , pp. 279 - 285
Copyright
Copyright © 1991 Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Auld, B. A., and Tisdell, C. A. 1986. Economic threshold/ critical density models in weed control. Proc. Eur. Weed Res. Soc. Symp. on Economic Weed Control:261–268.Google Scholar
2. Baumann-Fonay, C., Aguirre, M., Scotto, M., and Marre de Baumann Fonay, C. 1988. Comportamiento de los materiales geneticos de maiz flint y dentado en funcion de la fertilidad del suelo. I. Analisis del rendimiento y sus componentes. Proc. II Congreso Nac. de Maiz, Pergamino, Argentina II:46–53.Google Scholar
3. Beaumer, K., and de Wit, C. T. 1968. Competitive interference of species in monocultures and mixed stands. Neth. J. Agric. Sci. 16: 103–122.Google Scholar
4. Coble, H. D. 1989. Using economic thresholds for weeds in soybean. Proc. World Soybean Res. Conf. IV. Asociacion Argentina de la Soja, Buenos Aires, Argentina, p. 1607–1612.Google Scholar
5. Dew, D. A. 1972. An index of competition for estimating crop loss due to weeds. Can. J. Plant Sci. 52:921–927.Google Scholar
6. Eagle, H. A., and Hardacre, A. K. 1979. Genetic variation in Zea mays for germination and emergence at 10° C. Euphitica 28:287–295.Google Scholar
7. Eagle, H. A., and Hardacre, A. K. 1979. Genetic variations in maize for early seedling growth in low temperature environment. N. Z. Agric. Res. 22:553–559.Google Scholar
8. Firbank, L. G., and Watkinson, A. R. 1986. Modelling the population dynamics of an arable weed and its effects upon crop yield. J. Appl. Ecol. 23:147–159.Google Scholar
9. Ghersa, C. M., Leon, R.J.C., and Soriano, A. 1985. Efecto del sorgo de Alepo sobre la produccion de soja, de maiz y de las malezas presentes en estos cultivos. Rev. Fac. Agronomia Univ. Buenos Aires 6:123–129.Google Scholar
10. Ghersa, C. M., and Satorre, E. H. 1985. Evaluacion de la infestation de sorgo de Alepo. Tecnicrea 4:3–6.Google Scholar
11. Greig-Smith, P. 1964. Quantitative Plant Ecology. Butterworths & Co., London. 256 p.Google Scholar
12. Hall, A. J., Ginzo, H. D., Lemcoff, J. H., and Soriano, A. 1980. Influence of drought during pollen shedding on flowering, growth and yield of maize. Zur Acker-und pflanzenbau 149:287–298.Google Scholar
13. Hall, A. J., Rebella, C. M., Ghersa, C. M., and Culot, J. P. 1991. Field crops systems of the Pampas. In Pearson, C. J., ed. Field Crop Ecosystems. Elsevier Science Publishers, Amsterdam (in press).Google Scholar
14. Harper, J. L. 1977. Population Ecology of Plants. Academic Press, London. p. 151–194.Google Scholar
15. Hawton, D. 1980. Yield effects of herbicides on competition between crop and weed communities. Aust. J. Agric. Res. 31:1075–1081.Google Scholar
16. Kropff, M. J. 1988. Modelling the effect of weeds on crop production. Weed Res. 28:465–471.Google Scholar
17. Leguizamon, E. S., and Vitta, J. I. 1989. Analisis de la funcion de daño por sorgo de Alepo (Sorghum halepense (L.) Pers.) en soja (Glycine max (L.) Merr.). Proc. World Soybean Res. Conf. IV. Asociacion Argentina de la Soja, Buenos Aires, Argentina. 4:1632–1638.Google Scholar
18. Radosevich, S. R., and Holt, J. S. 1984. Weed Ecology: Implications for Vegetation Management. John Wiley and Sons, New York. p. 227–241.Google Scholar
19. Rebella, C. M., Frutos, E., Puig, R., and Perez, O. 1976. Influencia del stress hidrico sobre los rendimientos del maiz en la localidad de Pergamino. IDIA 32:160–167.Google Scholar
20. Rebella, C. M., Zeljkovich, L. T., and Funston, L. A. 1976. Contribucion al conocimiento de las necesidades termicas del maiz. Aplicacion del metodo de suma de temperaturas. IDIA 32:140–150.Google Scholar
21. Ross, M. A., and Harper, J. L. 1972. Occupation of biological space during seedling establishment. J. Ecol. 60:77–88.Google Scholar
22. Satorre, E. H. 1988. The competitive ability of spring cereals. Ph.D. Thesis, Univ. of Reading, U.K. 202 p.Google Scholar
23. Satorre, E. H., and Ghersa, C. M. 1985. Sistema de diagnostico para predecir el desarrollo de sorgo de Alepo en un lote. Tecnicrea 3:5–10.Google Scholar
24. Satorre, E. H., Ghersa, C. M., and Pataro, A. M. 1985. Prediction of Sorghum halepense (L.) Pers. rhizome sprout emergence in relation to air temperature. Weed Res. 25:103–109.Google Scholar
25. Senigagliesi, C., Garcia, R., and Galetto, M. 1984. Evaluacion de la respuesta del maiz a la fertilizacion nitrogenada y fosfatada en el area centro-norte de Buenos Aires y sur de Santa Fe. Proc. III Congreso Nac. de Maiz. Pergamino, Argentina. p. 238–244.Google Scholar
26. Sokal, R. R., and Rohlf, F. J. 1969. Biometry. The Principles and Practice of Statistics in Biological Research. Freeman, San Francisco. 776 p.Google Scholar
27. Spitters, C.J.T. 1983. An alternative approach to the analysis of mixed cropping experiments. I. Estimation of competition effects. Neth. J. Agric. Sci. 31:1–11.Google Scholar
28. Spitters, C.J.T., and van den Bergh, J. P. 1982. Competition between crops and weeds: a system approach. p. 137–148 in Holzner, W. and Numata, M., eds. Biology and Ecology of Weeds. Dr. W. Junk Publisher, The Hague. 461 p.Google Scholar