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Simulation of pigweed (Amaranthus spp.) seedling emergence in different tillage systems

Published online by Cambridge University Press:  12 June 2017

Joseph O. E. Oryokot ,
L. Anthony Hunt ,
Stephen Murphy  and
Clarence J. Swanton
Joseph O. E. Oryokot
Affiliation:
Department of Crop Science, University of Guelph, Guelph, ON, Canada N1G 2W1
L. Anthony Hunt
Affiliation:
Department of Crop Science, University of Guelph, Guelph, ON, Canada N1G 2W1
Stephen Murphy
Affiliation:
Department of Crop Science, University of Guelph, Guelph, ON, Canada N1G 2W1
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Abstract

On-farm implementation of IWM includes the biological and economic rationalization of weed management decisions. This, in turn, requires the ability to predict how weed populations and pressures will change with farm management options such as tillage method. We have developed a set of algorithms that simulate seedling emergence of mixed populations of green and redroot pigweed on the basis of the ecophysiological responses of seed germination and shoot elongation to temperature and, for germination, to moisture. The algorithms were calibrated using field data from 1993 and evaluated with data from two locations in 1994 and 1995. Over both sites and years, for four tillage systems, cumulative emergence was predicted with an overall root mean square error of 1.7%. Overprediction in one year was attributed to moisture shortage. Errors were greater for moldboard plowed plots than for those no-tilled. This decreased ability to predict emergence with increased tillage (soil disturbance) suggests that the algorithms should be modified to account for increased heterogeneity in weed seed distribution and soil moisture within disturbed soil. The algorithms, which were explicitly designed for incorporation within a crop growth model (e.g., CROPSIM), could become a useful part of a decision support system to rationalize weed management. Importantly, they could help predict changes in weed populations as farm management is adjusted, thereby reducing economic and environmental risk in agroecosystems.

Keywords

Corn, Zea mays L.green pigweed, Amaranthus powellii S. Wars AMAPOredroot pigweed, Amaranthus retroflexus L. AMAREChisel plowintegrated weed managementmechanistic modellingmoldboard plowno-tillpredictive modelssoil moisturesoil temperature
Type
Weed Biology and Ecology
Information
Weed Science , Volume 45 , Issue 5 , October 1997 , pp. 684 - 690
Copyright
Copyright © 1997 by the Weed Science Society of America 

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References

Literature Cited

Addae, P. C., Collis-George, N., and Pearson, C. J. 1991. Over-riding effects of temperature and soil strength on wheat seedlings under minimum and conventional tillage. Field Crops Res. 28: 103–116.Google Scholar
Addae, P. C. and Pearson, C. J. 1992. Thermal requirements for germination and seedling growth of wheat. Aust. J. Agric. Res. 43: 585–594.CrossRefGoogle Scholar
Alm, D. M., Stoller, E. W., and Wax, L. M. 1993. An index for predicting seed germination and emergence rates. Weed Technol. 7: 560–569.CrossRefGoogle Scholar
Benvenuti, S. and Macchia, M. 1995. Effect of hypoxia on buried weed seed germination. Weed Res. 35: 343–351.CrossRefGoogle Scholar
Bewley, J. D. and Black, M. 1994. Seeds: Physiology of Development and Germination. New York: Plenum Press. 367 p.Google Scholar
Blevins, R. L. and Frye, W. W. 1993. Conservation tillage: an ecological approach to soil management. Adv. Agron. 51: 33–78.CrossRefGoogle Scholar
Buhler, D. D. 1992. Population dynamics and control of annual weeds in corn (Zea mays) as influenced by tillage. Weed Sci. 40: 241–248.CrossRefGoogle Scholar
Buhler, D. D. and Mester, T. C. 1991. Effect of tillage systems on the emergence depth of giant (Setaria faberi) and green foxtail (Setaria viridis). Weed Sci. 39: 200–203.CrossRefGoogle Scholar
Chikoye, D., Wiese, S. F., and Swanton, C. J. 1995. Influence of common ragweed (Ambrosia artemisiifolia) time of emergence and density on white bean (Phaseolus vulgaris L.). Weed Sci. 43: 375–380.Google Scholar
Clements, D. R., Benoit, D. L., Murphy, S. D., and Swanton, C. J. 1996. Tillage effects of weed seed return and seedbank composition. Weed Sci. 44: 314–322.Google Scholar
Dieleman, A., Hamill, A. S., Wiese, S. F., and Swanton, C. J. 1995. Empirical models of pigweed (Amaranthus spp.) interference in soybean (Glycine max). Weed Res. 43: 612–618.Google Scholar
Forcella, F. 1993. Seedling emergence model for velvetleaf. Agron. J. 85: 929–933.Google Scholar
Forcella, F., Wilson, R. G., Renner, K. A., Dekker, J., Harvey, R. G., Alm, D. A., Buhler, D. D., and Cardina, J. 1992. Weed seedbank of the U.S. corn belt: magnitude, variation, emergence and application. Weed Sci. 40: 636–644.Google Scholar
Frost, R. A. 1971. Aspects of the comparative biology of three species of Amaranthus in southwestern Ontario. Ph.D. thesis. University of Western Ontario, London, ON, Canada. 644 p.Google Scholar
Fyfield, T. P. and Gregory, P. J. 1989. Effects of temperature and water potential on germination, radicle elongation and emergence of mungbean. J. Exp. Bot. 40: 667–674.CrossRefGoogle Scholar
Hall, M., Swanton, C. J., and Anderson, G. W. 1992. The critical period of weed control in corn (Zea mays). Weed Sci. 40: 441–447.Google Scholar
Harvey, S. J., and Forcella, F. 1993. Vernal seedling emergence model for common lambsquarters (Chenopodium album). Weed Sci. 41: 309–316.CrossRefGoogle Scholar
Hunt, L. A. and Pararajasingham, S. 1995. CROPSIM-WHEAT: a model describing the growth and development of wheat. Can. J. Plant Sci. 75: 619–632.CrossRefGoogle Scholar
Johnson, M. D. and Lowery, B. 1985. Effect of three conservation tillage practices on soil temperature and thermal properties. Soil Sci. Soc. Am. J. 49: 1547–1552.Google Scholar
King, C. A. and Oliver, L. R. 1994. A model for predicting large crabgrass (Digitaria saguinalis) emergence as influenced by temperature and water potential. Weed Sci. 42: 561–567.CrossRefGoogle Scholar
Knezevic, S. Z., Wiese, S. F., and Swanton, C. J. 1994. Interference of redroot pigweed (Amaranthus retroflexus) in corn (Zea mays). Weed Sci. 42: 568–573.CrossRefGoogle Scholar
McMaster, G. S., Wilhelm, W. W., and Morgan, J. A. 1992. Simulating winter wheat shoot apex phenology. J. Agric. Sci. 119: 1–12.CrossRefGoogle Scholar
Moore, M. J., Gillespie, T. J., and Swanton, C. J. 1994. Effects of cover crop muluches on weed emergence, weed biomass, and soybean (Glycine max) development. Weed Technol. 8: 512–518.Google Scholar
Oryokot, J.O.E. 1996. Modelling seedling emergence of pigweed populations in corn. Ph.D. thesis. University of Guelph, Guelph, ON. 145 p.Google Scholar
Oryokot, J.O.E., Murphy, S. D., and Swanton, C. J. 1997. Effect of tillage and corn on pigweed (Amaranthus spp.) seedling emergence and density. Weed Sci. 45: 120–126.CrossRefGoogle Scholar
Schonbeck, M. W. and Egley, G. H. 1988. Effects of ethylene and some environmental factors on different stages of germination in redroot pigweed (Amaranthus retroflexus L.) seeds. Plant Cell Environ. 11: 189–197.Google Scholar
Swanton, C. J. and Murphy, S. D. 1996. Weed science beyond the weeds: the role of integrated weed management (IWM) in agroecosystem health. Weed Sci. 44: 437–445.Google Scholar
Weaver, S. E. 1984. Differential growth and competitive ability of Amaranthus retroflexus, Apowellii and A. hybridus . Can. J. Plant Sci. 64: 715–724.Google Scholar
Weaver, S. E. and Thomas, A. G. 1986. Germination responses to temperature of atrazine-resistant and -susceptible biotypes of two pigweed (Amaranthus) species. Weed Sci. 34: 865–870.Google Scholar
Weaver, S. E., Tan, C. S., and Bran, P. 1988. Effects of temperature and soil moisture on time of emergence of tomatoes and four weed species. Can. J. Plant Sci. 68: 877–886.Google Scholar
Wiese, A. F. and Davis, R. G. 1967. Weed emergence from two soils at various moistures, temperatures and depths. Weeds 15: 118–121.Google Scholar
Wiles, L. J., King, R. P., Schweizer, E. E., Lydbecker, D. W., and Swinton, S. M. 1996. GWM: general weed management model. Agric. Syst. 50: 355–376.Google Scholar
Yenish, J. P., Doll, J. D., and Buhler, D. D. 1992. Effects of tillage on vertical distribution and viability of weed seed in soil. Weed Sci. 40: 429–433.Google Scholar