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Characterizing Weed Communities Among Various Rotations in Central South Dakota

Published online by Cambridge University Press:  20 January 2017

Randy L. Anderson  and
Dwayne L. Beck
Randy L. Anderson*
Affiliation:
Northern Grain Insects Research Laboratory, 2923 Medary Avenue Brookings, SD 57006
Dwayne L. Beck
Affiliation:
Dakota Lakes Research Farm, South Dakota State University, P.O. Box 2, Pierre, SD 57501
*
Corresponding author's E-mail: [email protected]
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Abstract

Producers in the Great Plains are exploring alternative crop rotations with the goal of reducing the use of fallow. In 1990, a study was established with no-till practices to compare eight rotations comprising various combinations of winter wheat (W), spring wheat (SW), corn (C), chickpea (CP), dry pea (Pea), soybean (SB), or fallow (F). After 12 yr, we characterized weed communities by recording seedling emergence in each rotation. Downy brome, cheat, redroot pigweed, and green foxtail were the most common weeds observed. Weed community density was highest for W–CP, being 13-fold greater than with Pea–W–C–SB. Downy brome and cheat were rarely observed in rotations where winter wheat was grown only once every 3 or 4 yr; in contrast, density of the brome species was 75-fold greater in W–CP. Warm-season weeds were also affected by rotation design; density of redroot pigweed and green foxtail was sixfold greater in W–C–CP compared with Pea–W–C–SB or W–F. One rotation design that was especially favorable for low weed density was arranging crops in a cycle of four, with two cool-season crops followed by two warm-season crops.

Keywords

Cheat, Bromus secalinus L. BROSEdowny brome, Bromus tectorum L. BROTEgreen foxtail, Setaria viridis L. SETVIredroot pigweed, Amaranthus retroflexus L. AMAREchickpea, Cicer arietinum L.corn, Zea mays L.dry peas, Pisum sativum L.soybean, Glycine max Merrillwheat, Triticum aestivum L.Rotation design
Type
Research
Information
Weed Technology , Volume 21 , Issue 1 , March 2007 , pp. 76 - 79
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

[AFPC] Agricultural and Food Policy Center 2005. Representative Farms Economic Outlook for the January FAPRI/AFPC Baseline. http://www.afp.tamu.edu. Accessed: December 15, 2005.Google Scholar
Anderson, R. L. 2003. An ecological approach to strengthen weed management in the semiarid Great Plains. Adv. Agron. 80:33–62.CrossRefGoogle Scholar
Anderson, R. L. 2005. A multi-tactic approach to manage weed populations in crop rotations. Agron. J. 97:1579–1583.Google Scholar
Anderson, R. L., Bowman, R. A., Nielsen, D. C., Vigil, M. F., Aiken, R. M., and Benjamin, J. G. 1999. Alternative crop rotations for the central Great Plains. J. Prod. Agric. 12:95–99.CrossRefGoogle Scholar
Blackshaw, R. E., Larney, F. O., Lindwall, C. W., and Kozub, G. C. 1994. Crop rotation and tillage effect on weed populations in the semi-arid Canadian prairies. Weed Technol. 8:231–237.CrossRefGoogle Scholar
Derksen, D. A., Anderson, R. L., Blackshaw, R. E., and Maxwell, B. 2002. Weed dynamics and management strategies for cropping systems in the Northern Great Plains. Agron. J. 94:174–185.Google Scholar
Dieleman, J. A., Mortensen, D. A., and Martin, A. R. 1999. Influence of velvetleaf (Abutilon theophrasti) and common sunflower (Helianthus annuus) density variation on weed management outcomes. Weed Sci. 47:81–87.CrossRefGoogle Scholar
Forcella, F. 1992. Prediction of weed seedling densities from buried seed reserves. Weed Res. 32:29–38.Google Scholar
Froud-Williams, R. J. 1988. Changes in weed flora with different tillage and agronomic management systems. in Altieri, M.A., Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. Boca Raton, FL CRC Press. 213–236.Google Scholar
Froud-Williams, R. J., Chancellor, R. J., and Drennan, D. S. H. 1981. Potential changes in weed floras associated with reduced-cultivation systems for cereal production in temperature regions. Weed Res. 21:99–109.Google Scholar
Leeson, J. Y., Sheard, J. W., and Thomas, A. G. 2000. Weed communities associated with arable Saskatchewan farm management systems. Can. J. Plant Sci. 80:177–185.CrossRefGoogle Scholar
Mohler, C. L. 1993. A model of the effects of tillage on emergence of weed seedlings. Ecol. Appl. 3:53–73.CrossRefGoogle Scholar
Mortensen, D. A., Bastiaans, L., and Sattin, M. 2000. The role of ecology in the development of weed management systems: an outlook. Weed Res. 40:49–62.CrossRefGoogle Scholar
Moyer, J. R., Romain, E. S., Lindwall, C. W., and Blackshaw, R. E. 1994. Weed management in conservation tillage systems for wheat production in North and South America. Crop Prot. 13:243–258.Google Scholar
Peterson, G. A., Schlegel, A. J., Tanaka, D. L., and Jones, O. R. 1996. Precipitation use efficiency as affected by cropping and tillage systems. J. Prod. Agric. 9:180–186.CrossRefGoogle Scholar
Peterson, G. A., Westfall, D. G., and Cole, C. V. 1993. Agroecosystem approach to soil and crop management research. Soil Sci. Soc. Am. J. 57:1354–1360.Google Scholar
Roberts, H. A. 1981. Seed banks in the soil. Adv. Appl. Biol. 6:1–55.Google Scholar
Wicks, G. A. and Smika, D. E. 1990. Central Great Plains. in Donald, W.W., ed. Systems of Weed Control in Wheat in North America. Lawrence, KS Weed Science Society of America. 127–157.Google Scholar
Winkle, M. E., Leavitt, J. R. C., and Burnside, O. C. 1981. Effects of weed density on herbicide absorption and bioactivity. Weed Sci. 29:405–409.CrossRefGoogle Scholar