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Variation in Wild Proso Millet (Panicum miliaceum) Fecundity in Sweet Corn Has Residual Effects in Snap Bean

Published online by Cambridge University Press:  20 January 2017

Adam S. Davis  and
Martin M. Williams II
Adam S. Davis*
Affiliation:
United States Department of Agriculture, Agricultural Research Service, Invasive Weed Management Unit, 1102 S. Goodwin Avenue, Urbana, IL 61801
Martin M. Williams II
Affiliation:
United States Department of Agriculture, Agricultural Research Service, Invasive Weed Management Unit, 1102 S. Goodwin Avenue, Urbana, IL 61801
*
Corresponding author's E-mail: adam.davis@ars.usda.gov
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Abstract

Bioeconomic models are predicated upon the relationship between weed fecundity and crop yield loss in consecutive growing seasons, yet this phenomenon has received few empirical tests. Residual effects of wild proso millet (WPM) fecundity in sweet corn upon WPM seedling recruitment, weed management efficacy, and crop yield within a subsequent snap bean crop were investigated with field experiments in Urbana, IL, in 2005 and 2006. WPM fecundity in sweet corn showed strong positive associations with WPM seedbank density, seedling recruitment, and demographic transitions within snap bean. A negative exponential relationship between WPM initial seedling density and seedling survival of a single rotary hoe pass indicated that the rotary hoe was ineffective at low weed population densities, but its efficacy increased with increasing weed population density to a maximum of 75% seedling mortality. Efficacy of postemergent chemical control of WPM was unaffected by WPM population density. Path analysis models demonstrated dependence between WPM fecundity in sweet corn, WPM seedling recruitment in snap bean, and reductions in snap bean yield in subsequent growing season, mediated by negative impacts of WPM seedling establishment on snap bean stand. These results underscore the importance of expanding integrated weed management programs to include management of annual weed populations both at the end of their life cycle, by reducing fecundity and seed survival, and at the very beginning of their life cycle, by reducing seedling recruitment and establishment.

Keywords

Wild proso millet, Panicum miliaceum Lsweet corn, Zea mays L., ‘GH2547’, ‘Spirit’, ‘WHT2801’snap bean, Phaseolus vulgaris L., ‘Caprise’ and ‘Charon’Density dependencepopulation dynamicsintegrated weed managementweed suppressive hybridsinterferencepath analysissoil seedbanksafe sitesearly season control
Type
Weed Management
Information
Weed Science , Volume 55 , Issue 5 , October 2007 , pp. 502 - 507
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Boyd, N. S., Brennan, E. B., and Fennimore, S. A. 2006. Stale seedbed techniques for organic vegetable production. Weed Technol. 20:1051–1057.CrossRefGoogle Scholar
Boyd, N. and Van Acker, R. 2004. Seed and microsite limitations to emergence of four annual weed species. Weed Sci. 52:571–577.Google Scholar
Burnham, K. P. and Anderson, D. R. 2002. Model Selection and Inference: A Practical Information-Theoretic Approach. Pages 32–74. New York: Springer Verlag.Google Scholar
Bussan, A. J. and Boerboom, C. M. 2001. Modeling the integrated management of velvetleaf in a corn–soybean rotation. Weed Sci. 49:31–41.Google Scholar
Carmona, D. M., Menalled, F. D., and Landis, D. A. 1999. Gryllus pensylvanicus (Orthopera: Gryllidae): laboratory weed seed predation and within field activity-density. J. Econ. Entomol. 92:825–829.Google Scholar
Chee-Sanford, J. C., Williams, M. M. II, Davis, A. S., and Sims, G. K. 2006. Do microorganisms influence seed-bank dynamics? Weed Sci. 54:575–587.CrossRefGoogle Scholar
Colquhoun, J. B., Bellinder, R. R., and Kirkwyland, J. J. 1999. Efficacy of mechanical cultivation with and without herbicides in broccoli (Brassica oleracea), snap bean (Phaseolus vulgaris), and sweet corn (Zea mays). Weed Technol. 13:244–252.Google Scholar
Davis, A. S., Dixon, P. M., and Liebman, M. 2004. Using matrix models to determine cropping system effects on annual weed demography. Ecol. Appl. 14:655–668.Google Scholar
Davis, A. S. and Ngouajio, M. 2005. Introduction to the symposium Beyond thresholds: applying multiple tactics within integrated weed management systems. Weed Sci. 53:368.CrossRefGoogle Scholar
Davis, A. S., Renner, K. A., and Gross, K. L. 2005. Weed seedbank and community shifts in a long-term cropping systems experiment. Weed Sci. 53:296–306.CrossRefGoogle 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. 47:81–89.Google Scholar
Harrison, S. K., Regnier, E. E., and Schmoll, J. T. 2003. Postdispersal predation of giant ragweed (Ambrosia trifida) in no-tillage corn. Weed Sci. 51:955–964.Google Scholar
Heggenstaller, A. H. and Liebman, M. 2006. Demography of Abutilon theophrasti and Setaria faberi in three crop rotation systems. Weed Res. 46:138–151.CrossRefGoogle Scholar
Jordan, N. 1996. Weed prevention: priority research for alternative weed management. J. Prod. Agric. 9:485–490.Google Scholar
Liebman, M. and Gallandt, E. R. 1997. Many little hammers: ecological approaches for management of crop–weed interactions. Pages 291–343. in Jackson, L.E. ed. Ecology in Agriculture. San Diego Academic Press.CrossRefGoogle Scholar
Maron, J. L. and Gardner, S. N. 2000. Consumer pressure, seed versus safe-site limitation, and plant population dynamics. Oecologia. 124:260–269.Google Scholar
Melander, B., Rasmussen, I. A., and Barberi, P. 2005. Integrating physical and cultural methods of weed control—examples from European research. Weed Sci. 53:369–381.Google Scholar
Menalled, F. D., Liebman, M., and Renner, K. 2006. The ecology of weed seed predation in herbaceous crop systems. Pages 297–327. in Singh, H.P., Batish, D.R., Kohli, R.K. eds. Handbook of Sustainable Weed Management. Binghamton, NY Haworth Press.Google Scholar
Mertens, S. K., Yearsley, J. M., van den Bosch, F., and Gilligan, C. A. 2006. Transient population dynamics in periodic matrix models: methodology and effects of cyclic permutations. Ecology. 87:2338–2348.Google Scholar
Mitchell, R. J. 2001. Path analysis: pollination. Pages 217–234. in Scheiner, S.M., Gurevitch, J. eds. Design and Analysis of Ecological Experiments. New York Oxford University Press.Google Scholar
Mohler, C. L. 1996. Ecological bases for the cultural control of weeds. J. Prod. Agric. 9:468–474.Google Scholar
Mortensen, D. A. and Dieleman, J. A. 1998. Why weed patches persist: dynamics of edges and density. Pages 14–19. in Medd, R.W., Pratley, J.E. eds. Precision Weed Management in Crops and Pastures. Wagga Wagga CRC for Weed Management Systems, Adelaide.Google Scholar
[NASS] National Agricultural Statistics Service 2006. Vegetables 2005 Summary. 17–69. Washington, DC: U.S. Government Printing Office.Google Scholar
Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. 1996. Applied Linear Statistical Models. Chicago Irwin. 1408.Google Scholar
Norris, R. F. 1999. Ecological implications of using thresholds. Pages 31–58. in Buhler, D.D. ed. Expanding the Context of Weed Management. New York Food Products Press.Google Scholar
Rajcan, I., Chandler, K. J., and Swanton, C. J. 2004. Red-far red ratio of reflected light: a hypothesis of why early-season weed control is important in corn. Weed Sci. 52:774–778.Google Scholar
Rasmussen, I. A. and Holst, N. 2003. Computer model for simulating the long-term dynamics of annual weeds: from seedlings to seeds. Aspect. Appl. Biol. 69:277–284.Google Scholar
Ratkowski, D. A. 1983. Nonlinear Regression Modeling: A Unified Practical Approach. Pages 135–153. New York: Marcel Dekker.Google Scholar
Ross, M. A. and Harper, J. L. 1972. Occupation of biological space during seedling establishment. J. Ecol. 60:77–88.Google Scholar
Sit, V. and Poulin-Costello, M. 1994. Catalogue of Curves for Curve Fitting. Victoria Forest Science Research Branch. 110.Google Scholar
Taylor, K. L. and Hartzler, R. G. 2000. Effect of seed bank augmentation on herbicide efficacy. Weed Technol. 14:261–267.CrossRefGoogle Scholar
Wiles, L. J., Barlin, D. H., Schweizer, E. E., Duke, H. R., and Whitt, D. E. 1996. A new soil sampler and elutriator for collecting and extracting weed seeds from soil. Weed Technol. 10:35–41.CrossRefGoogle Scholar
Williams, M. M. II and Boydston, R. A. 2007. Sweet corn hybrid influences outcomes of wild proso millet suppression with sethoxydim. in. WSSA Abstracts, Volume 47. 121.Google Scholar
Williams, M. M. II, Boydston, R. A., and Davis, A. S. 2006. Canopy variation among three sweet corn hybrids and implications for light competition. HortScience. 41:1449–1454.Google Scholar
Williams, M. M. II, Boydston, R. A., and Davis, A. S. 2007. Wild proso millet (Panicum miliaceum) suppressive ability among three sweet corn hybrids. Weed Sci. 55:245–251.Google Scholar
Williams, M. M. II, Pataky, J. K., Nordby, J. N., Riechers, D. E., Sprague, C. L., and Masiunas, J. B. 2005. Cross-sensitivity in sweet corn to nicosulfuron and mesotrione applied postemergence. HortScience. 40:1801–1805.CrossRefGoogle Scholar
Woolley, B. L., Michaels, T. E., Hall, M. R., and Swanton, C. J. 1993. The critical period of weed control in white bean (Phaseolus vulgaris). Weed Sci. 41:180–184.Google Scholar