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Effect of proximity factors on competition between winter wheat (Triticum aestivum) and Italian ryegrass (Lolium multiflorum)

Published online by Cambridge University Press:  12 June 2017

Abul Hashem ,
S. R. Radosevich  and
M. L. Roush
Abul Hashem
Affiliation:
Department of Crop and Soil Science, Oregon State University, Corvallis, OR 97331
M. L. Roush
Affiliation:
Department of Forest Science, Oregon State University, Corvallis, OR 97331
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Abstract

Density and spatial arrangement (rectangularity) effects on the competitive relationships, yield performance, and dynamics in canopy dominance of winter wheat and Italian ryegrass were evaluated using two addition series experiments. In experiment 1, combinations of six densities of each species formed the treatment matrix of addition series. In experiment 2, each species was tested at four densities and three rectangularities (RE) of winter wheat. In monocultures, crop density (plants per square meter) explained 82 to 85% of the total variation in the per-plant biomass of winter wheat in experiment 1. In mixtures of crop and weed, initial wheat density (N1) and initial ryegrass density (N2) and interaction of N1 and N2 explained 74 to 80% of the total variation in the per-plant biomass of winter wheat and 68 to 79% of Italian ryegrass in experiment 1. Intraspecific competition was apparent between 15 and 90 days after emergence (DAE) in winter wheat and between 90 and 170 DAE in Italian ryegrass. In mixtures, RE influenced plant size of Italian ryegrass up to 50 DAE only. Maximum winter wheat intraspecific competition occurred at 170 DAE, but maximum interspecific competition occurred during reproductive stages in mixtures. High RE increased seed yield, seed size, and harvest index of winter wheat and reduced biomass of Italian ryegrass. Grain yield of winter wheat was reduced up to 92% by competition from ryegrass. Even nine ryegrass plants in 100 winter wheat plants m−2 reduced winter wheat grain yield by 33%. However, the extent of loss in winter wheat grain yield was less in RE 16 (wider spacing) than in RE 1 (square planting) or 4 (close row spacing). Winter wheat was the stronger competitor during vegetative stages, but Italian ryegrass became the stronger competitor during the reproductive stages of development. Winter wheat leaves dominated at the top canopy during the vegetative stage, but ryegrass dominated at the top canopy during the reproductive stages. In the top canopy of mixtures at 200 DAE, the leaf area indices (LAI) of ryegrass was 6.6 times greater than winter wheat at RE 1 compared to only 1.6 times at RE 16. Greater LAI of Italian ryegrass in the top canopy reduced photosynthetically active radiation available to winter wheat by 68% at booting stage.

Keywords

Winter wheat, Triticum aestivum (L.)Italian ryegrass, Lolium multiflorum (Lam)Densityspatial arrangement (rectangularity)addition seriescompetitionlinear modelcanopy dominance
Type
Weed Biology and Ecology
Information
Weed Science , Volume 46 , Issue 2 , April 1998 , pp. 181 - 190
Copyright
Copyright © 1998 by the Weed Science Society of America 

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References

Literature Cited

Angonin, C., Caussanel, J. P., and Meynard, J. M. 1996. Competition between winter wheat and Veronica hederiifolia: influence of weed density and the amount and timing of nitrogen application. Weed Res. 36: 175–187.CrossRefGoogle Scholar
Appleby, A. P., Olson, P. O., and Colbert, D. R. 1976. Winter wheat yield reduction from interference by Italian ryegrass. Agron. J. 68: 463–466.Google Scholar
Auld, B. A., Kemp, D. R., and Medd, R. W. 1983. The influence of spatial arrangement on the grain yield of wheat. Aust. J. Agric. Res. 34: 99–108.CrossRefGoogle Scholar
Austin, M. P. 1982. Use of a relative physiological performance value in the prediction of performance in multispecies mixtures from monocultures performance. J. Appl. Ecol. 70: 559–570.Google Scholar
Barbour, M. G., Burk, J. H., and Pitts, W. D. 1987. Pages 198–204 in Terrestrial Plant Ecology. Menlo Park, CA: Benjamin/Cummings.Google Scholar
Burrill, L. C., Braunworth, W. S. Jr., William, R. D., Parker, R. R., Swan, D. G., and Kidder, D. W. 1988. Pages 29–48 in Pacific Northwest Handbook. Corvallis, OR: Oregon State University.Google Scholar
Concannon, J. A. 1987. The Effects of Density and Proportion of Spring Wheat and Lolium multiflorum Lam. . Oregon State University, Corvallis, OR. 101 p.Google Scholar
Cripps, J.E.L., Melville, F., and Nicol, H. I. 1975. The relationships of granny apple tree growth and early cropping to planting density and rectangularity. J. Hortic. Sci. 50: 291–299.CrossRefGoogle Scholar
Cunia, T. 1973. Dummy variables and some of their uses in regression analysis. Pages 1–146 in Cunia, T. et al., eds. Proceeding of IUFRO Meeting. France. June 25–29, 1973.Google Scholar
Doli, H., Holm, O., and Sogaard, B. 1994. Effect of crop density on competition by wheat and barley with Agrostemma githago and other weeds. Weed Res. 35: 391–396.Google Scholar
Fischer, R. A. and Miles, R. E. 1973. The role of spatial pattern in the competition between crop plants and weeds. A theoretical analysis. Math. Biosci. 18: 335–350.Google Scholar
Gaudit, G. L. and Keddy, P. A. 1988. A comparative approach to predicting competitive ability from plant traits. Nature 334: 242–243.Google Scholar
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: 279–285.CrossRefGoogle Scholar
Goodall, W. D. 1957. Some consideration in the use of point quadrat methods for the analysis of vegetation. Aust. J. Biol. Sci. 5: 1–41.CrossRefGoogle Scholar
Grace, J. B. 1990. On the relationships between plant traits and competitive ability. Pages 51–65 in Grace, J. B. and Tilman, D. T., eds. Perspective on Plant Competition. New York: Academic Press.Google Scholar
Hashem, A., Radosevich, S. R., and Roush, M. L. 1994. Morphology and growth of winter wheat as affected by competition from Italian ryegrass (Lolium multiflorum Lam). Ann. Bangladesh Agric. 4: 53–60.Google Scholar
Holliday, R. 1963. The effect of row width on the yield of cereals. Field Crop Abstr. 16: 71–81.Google Scholar
Hume, L. 1985. Crop loss in wheat (Triticum aestivum) as determined using weeded and non-weeded quadrats. Weed Sci. 33: 734–740.Google Scholar
Huxley, P. A. 1963. Considerations when experimenting with changes in plant spacing. Working paper # 15. ICRAF, P.O. Box 30677, Nairobi.Google Scholar
Kropff, M. J. 1988. Modeling the effects of weeds on crop production. Weed Res. 28: 465–471.Google Scholar
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.Google Scholar
Loomis, R. S. and Williams, W. A. 1969. Productivity and morphology of crop stands: pattern with leaves. in Eastin, J. D. et al., eds. Physiological Aspects of Crop Yield. Madison, WI: ASA and CSA.Google Scholar
Martin, R. J., Cullis, J. B., and McNamara, D. W. 1987. Prediction of wheat yield loss due to competition by wild oats (Avenu spp.). Aust. J. Agric. Res. 38: 487–499.Google Scholar
Medd, R. W., Auld, B. A., Kemp, D. R., and Musisom, R. D. 1985. The influence of wheat density and spatial arrangements on annual ryegrass, Lolium rigidum, competition. Aust. J. Agric. Res. 36: 361–371.Google Scholar
Monsi, M. and Saeki, T. 1953. Uber den Lichtfaktor in den Pflanzengesllshaften und seine beduetung fur die Stoffproduktion. Jap. J. Bot. 14: 22–52.Google Scholar
Radford, B. J., Wilson, B. J., Cartiledge, O., and Watkins, F. B. 1980. Effect of wheat seeding rate on wild oat competition. Aust. J. Exp. Agric. Anim. Husb. 20: 77–81.Google Scholar
Radosevich, S. R. 1987. Methods to study interaction among crops and weed. Weed Technol. 1: 190–198.Google Scholar
Radosevich, S. R. 1988. Methods to study crop and weed interaction. Pages 121–143 in Alteiri, M. A. and Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. Boca Raton, FL: CRC Press.Google Scholar
Roush, M. L. 1988. Models of a Four-Species Annual Weed Community Dynamics. . Oregon State University, Corvallis, OR. 217 p.Google Scholar
[SAS] Statistical Analysis Systems. 1987. SAS/STAT Guide for Personal Computers. Version 6. Cary, NC: Statistical Analysis Systems Institute.Google Scholar
Shainsky, L. J. 1988. Competitive Interactions Between Douglas-fir and Red Alder Seedling: Growth Analysis, Resource Use, and Physiology. . Oregon State University, Corvallis, OR. 221 p.Google Scholar
Spitters, C.J.T. 1983. An alternative approach to the analysis of mixed cropping experiment. I. Estimation of competition effects. Neth. J. Agric. Sci. 31: 1–11.Google Scholar
Stern, W. R. and Donald, C. M. 1962. The influence of leaf area and radiation on the growth of clover swards. Aust. J. Agric. Sci. 13: 615–623.Google Scholar
Vitta, J. I. and Quintanilla, C. F. 1996. Canopy measurements as predictors of weed-crop competition. Weed Sci. 44: 511–516.Google Scholar
Watkinson, A. R. 1981. Interference in pure and mixed population of Agrostemma githago . J. Appl. Ecol. 18: 967–976.Google Scholar
Wilson, B. J. and Wright, K. J. 1990. Predicting the growth and competitive effects of annual weeds in wheat. Weed Res. 30: 201–212.Google Scholar
Wilson, B. J., Wright, K. J., Brain, P., Clements, M., and Stephens, E. 1995. Predicting the competitive effects of weed and crop density on weed biomass, weed seed production and crop yield in wheat. Weed Res. 35: 265–278.Google Scholar