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An Emergence Model for Wild Oat (Avena fatua)

Published online by Cambridge University Press:  20 January 2017

Krishona Martinson*
Affiliation:
Andover Regional Center, 550 Bunker Lake Boulevard N.W., Suite L1, Andover, MN 55304
Beverly Durgan
Affiliation:
University of Minnesota Extension, 240 Coffey Hall, 1420 Eckles Avenue, St. Paul, MN 55108
Frank Forcella
Affiliation:
U.S. Department of Agriculture–Agricultural Research Service, 803 Iowa Avenue, Morris, MN, 56267
Jochum Wiersma
Affiliation:
Northwest Research and Outreach Center, 2900 University Avenue, Crookston, MN 56716
Kurt Spokas
Affiliation:
U.S. Department of Agriculture–Agricultural Research Service, 803 Iowa Avenue, Morris, MN, 56267
David Archer
Affiliation:
U.S. Department of Agriculture–Agricultural Research Service, Highway 6 South, Mandan, ND 58554
*
Corresponding author's E-mail: [email protected]

Abstract

Wild oat is an economically important annual weed throughout small grain producing regions of the United States and Canada. Timely and more accurate control of wild oat may be developed if there is a better understanding of its emergence patterns. The objectives of this research were to evaluate the emergence pattern of wild oat and determine if emergence could be predicted using soil growing degree days (GDD) and/or hydrothermal time (HTT). Research plots were established at Crookston, MN, and Fargo, ND, in 2002 and 2003. On a weekly basis, naturally emerging seedlings were counted and removed from six 0.37-m2 permanent quadrats randomly distributed in a wild oat–infested area. This process was repeated until no additional emergence was observed. Wild oat emergence began between May 1 and May 15 at both locations and in both years and continued for 4 to 6 wk. Base soil temperature and soil water potential associated with wild oat emergence were determined to be 1 C and −0.6 MPa, respectively. Seedling emergence was correlated with GDD and HTT but not calendar days (P = 0.15). A Weibull function was fitted to cumulative wild oat emergence and GDD and HTT. The models for GDD (n = 22, r2 = 0.93, root mean square error [RMSE] = 10.7) and HTT (n = 22, r2 = 0.92, RMSE = 11.2) closely fit observed emergence patterns. The latter model is the first to use HTT to predict wild oat emergence under field conditions. Both models can aid in the future study of wild oat emergence and assist growers and agricultural professionals with planning timely and more accurate wild oat control.

Type
Weed Biology and Ecology
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Alan, L. R. and Wiese, A. F. 1985. Effects of degree days on weed emergence. Proceedings of Southern Weed Science Society, 38th Annual Meeting. Raleigh, NC Southern Weed Science Society.Google Scholar
Archer, D. W., Forcella, F., Korth, A., Kuhn, A., Eklund, J., and Spokas, K. 2006. WeedCast version 4.0. Available at http://www.ars.usda.gov/services/software/download.htm?softwareid=112. Accessed May 21, 2007.Google Scholar
Banting, J. D. 1962. The dormancy behavior of Avena fatua L. in cultivated soils. Can. J. Plant Sci. 42:2239.Google Scholar
Banting, J. D. 1974. Growth habit and control of wild oats. Canadian Department of Agriculture Publication No. 1531. 34.Google Scholar
Bewick, T. A., Binming, L. K., and Yandell, B. 1988. A degree day model for predicting the emergence of swamp dodders in cranberry. J. Am. Soc. Hort. Sci. 113:839841.CrossRefGoogle Scholar
Bradford, K. J. 2002. Application of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci. 50:248260.CrossRefGoogle Scholar
Campbell, G. S. 1985. Soil Physics with BASIC: Transport Models for Soil–Plant Systems. Amsterdam; New York Elsevier. 150.Google Scholar
Dexter, A. G., Nalewaja, J. D., Rasmusson, D. D., and Buchli, J. 1981. Survey of wild oat and other weeds in North Dakota, 1978 and 1970. North Dakota State University Agriculture Experiment Station North Dakota Research Report No. 79.Google Scholar
Eizenberg, H., Colquhoun, J., and Mallory-Smith, C. 2004. A predictive degree-days model for small broomerape (Orobanche minor) parasitism in red clover in Oregon. Weed Sci. 53:3740.CrossRefGoogle Scholar
Ekeleme, F., Forcella, F., Archer, D. W., Chikoye, D., and Akobundu, I. O. 2004. Simulation of shoot emergence pattern of cogongrass (Imperata cylindrica) in the humid tropics. Weed Sci. 52:961967.CrossRefGoogle Scholar
Flerchinger, G. N. 2000. The Simultaneous Heat and Water (SHAW) Model: User's Manual. Boise, ID USDA-ARS. 24. Technical Report. NWRC 2000-10.Google Scholar
Forcella, F. 1998. Real-time assessment of seed dormancy and seedling growth for weed management. Seed Sci. Res. 8:201209.CrossRefGoogle Scholar
Forcella, F., Benech Arnold, R. L., Sanchez, R., and Ghersa, C. M. 2000. Modeling seedling emergence. Field Crops Res. 67:123139.CrossRefGoogle Scholar
Friesen, G. and Shebeski, L. H. 1961. The influence of temperature on the germination of wild oat seeds. Weeds. 9:634638.CrossRefGoogle Scholar
Gonzalez-Andujar, J. L., Forcella, F., Kegode, G., Gallagher, R., and Van Acker, R. 2001. Modelizacion de la emergencia de plantulas de Avena loca (Avena fatua L.) usando tiempo hidrotermal. Pages 243246. in. Congreso 2001 de la Sociedad Espanola de Malherbiologia. Leon, Spain Sociedad Espanola de Malherbiologia.Google Scholar
Grundy, A. C. 2003. Predicting weed emergence: a review of approaches and future challenges. Weed Res. 43:111.Google Scholar
Gummerson, R. J. 1986. The effect of constant temperatures and osmotic potential on the germination of sugar beet. J. Exp. Bot. 37:729741.CrossRefGoogle Scholar
Hammel, J. E., Papendick, R. I., and Campbell, G. S. 1981. Fallow tillage effects on evaporation and seed zone water content in a dry summer climate. Soil Sci. Soc. Am. J. 45:10161022.Google Scholar
Harvey, S. J. and Forcella, F. 1993. Vernal seedling emergence models for common lambsquarters (Chenopodium album). Weed Sci. 41:309316.Google Scholar
Imam, A. G. and Allard, R. W. 1965. Population studies in predominantly self-pollinated species. VI. Genetic variability between and within natural populations of wild oats from differing habitats in California. Genetics. 51:4962.CrossRefGoogle ScholarPubMed
King, C. A. and Oliver, L. R. 1994. A model for predicting large crabgrass (Digitaria sanguinalis) emergence as influenced by temperature and water potential. Weed Sci. 42:561567.CrossRefGoogle Scholar
Mather, H. J. 1946. The control of wild oats in Alberta. Alberta Department of Agriculture Circ. No. 71.Google Scholar
Mickelson, J. A. and Grey, W. E. 2006. Effect of soil water content on wild oat (Avena fatua) seed mortality and seedling emergence. Weed Sci. 54 (2):255262.CrossRefGoogle Scholar
Rawls, W. J., Brakenseik, D. L., and Saxton, K. E. 1982. Estimation of soil water properties. Trans. ASAE (Am. Soc. Agric. Eng.) 25:13161320.CrossRefGoogle Scholar
Roman, E. S., Murphy, S. D., and Swanton, C. J. 2000. Simulation of Chenopodium album seedling emergence. Weed Sci. 48:4550.CrossRefGoogle Scholar
Saxton, K. E., Rawls, W. J., Romberger, J. S., and Papendick, R. I. 1986. Estimating generalized soil-water characteristics from texture. Soil Sci. Soc. Amer. J. 50:10311036.CrossRefGoogle Scholar
Sexsmith, J. J. 1969. Dormancy of wild oat seed produced under various temperature and moisture conditions. Weed Sci. 17:405407.CrossRefGoogle Scholar
Sharma, M. P., McBeath, D. K., and Vanden Born, W. H. 1976. Studies of the biology of wild oat. I. Dormancy, germination and emergence. Can. J. Plant Sci. 56:611618.CrossRefGoogle Scholar
Sharma, M. P. and Vanden Born, W. H. 1978. The biology of Canadian weeds. 27. Avena fatua L. Can. J. Plant Sci. 58:141157.CrossRefGoogle Scholar
Simpson, G. M. 1990. Seed Dormancy in Grasses. New York: Cambridge University Press. 297.CrossRefGoogle Scholar
Spokas, K. and Forcella, F. 2006. Estimating hourly incoming solar radiation from limited meteorological data. Weed Sci. 54:182189.CrossRefGoogle Scholar
Stougaard, R. N., Maxwell, B. D., and Harris, J. D. 1997. Influence of application timing on the efficacy of reduced rate postemergence herbicides for wild oat (Avena fatua) control in spring barley (Hordeum vulgare). Weed Technol. 11:283289.Google Scholar
Willmott, C. J. 1982. Some comments on the evaluation of model performance. Bull. Am. Meteorol. Soc. 63:13091313.2.0.CO;2>CrossRefGoogle Scholar
Zollinger, R. K., Ries, J. L., and Hammond, J. J. 2003. Survey of weeds in North Dakota. NorthDakota Extension Service Publication ER-83.Google Scholar