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Accuracy and cost effectiveness of GPS-assisted wild oat mapping in spring cereal crops

  • Lee R. Van Wychen (a1), Edward C. Luschei (a1), Alvin J. Bussan and Bruce D. Maxwell (a1)

Abstract

Managing weed infestations in a spatially precise manner requires accurate and cost-effective weed identification techniques. The goal of our research was to quantify the accuracy of continuous weed presence–absence maps and assess how management based on those maps may affect producer net returns. Each continuous sampled map covered the entire field and contained vector polygons labeled as either wild oat presence or wild oat absence. The accuracy of the continuous wild oat maps at each sampling time was determined from georeferenced quadrats of wild oat densities. The accuracy of the continuous wild oat seedling maps ranged from 48.3 to 87.1% among the six site-years. The accuracy of the wild oat seedling maps improved by at least 8% when a 10-m buffer was included around areas mapped as wild oat presence. The accuracy of continuous wild oat panicle maps from the combine at harvest ranged from 65.8 to 90.9% among the six site-years. The variation in accuracy for the wild oat seedling maps among sites was greater than the accuracy of the panicle maps. Net returns ($ ha−1) for four site-years were calculated and compared for four possible weed management approaches on each field. A site-specific herbicide application to areas mapped as wild oat presence always generated higher net returns than a herbicide application over the entire field for four sites. A site-specific herbicide application to areas mapped as wild oat presence plus a surrounding 10-m buffer area only resulted in a higher net return in one of the 12 site-years compared with a site-specific herbicide application without the 10-m buffer. This site had the lowest (48.3%) wild oat seedling map accuracy, and uncontrolled wild oat had a high-yield effect. This research indicates that using a continuous weed sampling method based on presence or absence for site-specific herbicide application can be profitable over a herbicide application to the entire field, even with the associated technology cost and seedling map errors.

Copyright

Corresponding author

Corresponding author. Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717.

References

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Cardina, J., Sparrow, D. H., and McCoy, E. L. 1995. Analysis of spatial distribution of common lambsquarters (Chenopodium album) in no-till soybean (Glycine max). Weed Sci. 43:258268.
Chancellor, R. J. and Peters, N.C.B. 1976. Competition between wild oat and crops. Pages 99112 In Price Jones, D., ed. Wild Oats in World Agriculture. London: Agricultural Research Council.
Clay, S. A., Lems, G. J., Clay, D. E., Forcella, F., Ellsbury, M. M., and Carlson, C. G. 1999. Sampling weed spatial variability on a fieldwide scale. Weed Sci. 47:674681.
Colbach, N., Forcella, F., and Johnson, G. A. 2000. Spatial and temporal stability of weed populations over five years. Weed Sci. 48:366377.
Felton, W. L., Doss, A. F., Nash, P. G., and McCloy, K. R. 1991. To selectively spot spray weeds. Am. Soc. Agric. Eng. Symp. 11:427432.
Johnson, G. A., Cardina, J., and Mortensen, D. A. 1997. Site-specific weed management: current and future directions. Pages 131147 In Pierce, F. J. and Sadler, E. J., eds. The State of Site-Specific Management for Agriculture. Madison, WI: ASA-CSSA-SSSA.
Lindquist, J. L., Dieleman, J. A., Mortensen, D. A., Johnson, G. A., and Pester, D. Y. 1998. Economic importance of managing spatially heterogeneous weed populations. Weed Technol. 12:713.
Luschei, E., Van Wychen, L. R., Maxwell, B. D., Bussan, A. J., Buschena, D., and Goodman, D. 2000. Parameterizing weed interference models with site-specific data. Proceedings of the 5th International Conference on Precision Agriculture. Madison, WI: ASA-CSSA-SSSA. pp. 221233.
Luschei, E., Van Wychen, L. R., Maxwell, B. D., Bussan, A. J., Buschena, D., and Goodman, D. 2001. Implementing and conducting on-farm weed research with the use of GPS. Weed Sci. 49:536542.
Maxwell, B. D. and Colliver, C. T. 1995. Expanding economic thresholds by including spatial and temporal weed dynamics. Proc. Br. Crop Prot. Conf.—Weeds. Brighton, Great Britain: 3:1,0691,076.
Medlin, C. R. and Shaw, D. R. 2000. Economic comparison of broadcast and site-specific herbicide applications in nontransgenic and glyphosate-tolerant Glycine max . Weed Sci. 48:653661.
Mortensen, D. A., Dieleman, J. A., and Johnson, G. A. 1998. Weed spatial variation and weed management. Pages 293309 In Hatfield, J. L., Buhler, D. D., and Stewart, B. A., eds. Integrated Weed and Soil Management. Chelsea, MI: Ann Arbor Press.
Mortensen, D. A., Johnson, G. A., and Young, L. J. 1993. Weed distribution in agricultural fields. Pages 113124 In Soil Specific Crop Management, 1130124. Madison, WI: ASA-CSSA-SSA.
Oriade, C. 1995. A Bioeconomic Analysis of Site-specific Management and Delayed Planting Strategies for Weed Control. Ph.D. dissertation. University of Minnesota, St. Paul, MN.
Paice, M.E.P., Miller, P.C.H., and Bodle, J. 1995. An experimental machine for evaluating spatially selective herbicide application. J. Agric. Eng. Res. 60:107116.
Rew, L. J. and Cousens, R. D. 2001. Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate? Weed Res. 41:118.
Rew, L. J., Cussans, G. W., Mugglestone, M. A., and Miller, P.C.H. 1996. A technique for mapping the spatial distribution of Elymus repens, with estimates of the potential reduction in herbicide usage by patch spraying. Weed Res. 36:283292.
Stafford, J. V., Le Bars, J. M., and Ambler, B. 1996. A hand-held data logger with integral GPS for producing weed maps by field walking. Comput. Electron. Agric. 14:235247.
Stafford, J. V. and Miller, P.C.H. 1993. Spatially selective application of herbicide to cereal crops. Comput. Electron. Agric. 9:217229.
Thompson, J. F., Stafford, J. V., and Miller, P.C.H. 1991. Potential for automatic weed detection and selective herbicide application. Crop Prot. 10:254259.
Wiles, L. J., Gold, H. J., and Wilkerson, G. G. 1993. Modeling the uncertainty of weed density estimates to improve post-emergence herbicide control decisions. Weed Res. 33:241252.
Wiles, L. J. and Schweizer, E. E. 1999. The cost of counting and identifying weed seeds and seedlings. Weed Sci. 47:667673.
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Weed Science
  • ISSN: 0043-1745
  • EISSN: 1550-2759
  • URL: /core/journals/weed-science
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