Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-18T20:56:24.507Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  20 January 2017

Lee R. Van Wychen
Affiliation:
Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717
Edward C. Luschei
Affiliation:
Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717
Bruce D. Maxwell
Affiliation:
Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717

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.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

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.Google Scholar
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.Google Scholar
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.Google Scholar
Colbach, N., Forcella, F., and Johnson, G. A. 2000. Spatial and temporal stability of weed populations over five years. Weed Sci. 48:366377.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.CrossRefGoogle Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.CrossRefGoogle Scholar
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.CrossRefGoogle Scholar
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.CrossRefGoogle Scholar
Stafford, J. V. and Miller, P.C.H. 1993. Spatially selective application of herbicide to cereal crops. Comput. Electron. Agric. 9:217229.Google Scholar
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.Google Scholar
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.CrossRefGoogle Scholar
Wiles, L. J. and Schweizer, E. E. 1999. The cost of counting and identifying weed seeds and seedlings. Weed Sci. 47:667673.Google Scholar