Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-29T14:57:05.434Z Has data issue: false hasContentIssue false
  • English
  • Français

Sampling to make maps for site-specific weed management

Published online by Cambridge University Press:  20 January 2017

Lori J. Wiles
Lori J. Wiles*
Affiliation:
U.S. Department of Agriculture, Agricultural Research Service, Water Management Research Unit, Fort Collins, CO 80526; [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Growers need affordable methods to sample weed populations to reduce herbicide use with site-specific weed management. Sampling programs and methods of developing sampling programs for integrated pest management are not sufficient for site-specific weed management because more and different information is needed to make treatment maps than simply estimate average pest density. Sampling plans for site-specific weed management must provide information to map the weeds in the field but should be developed for the objective of prescribing spatially variable management. Weed scientists will be most successful at designing plans for site-specific weed management if they focus on this objective throughout the process of designing a sampling plan. They must also learn more about the spatial distribution and dynamics of weed populations and use that knowledge to identify cost-effective plans, recommend methods to make maps as well as collect data, and find ways to evaluate maps that reflect management to be prescribed from the map. Foremost, sampling must be thought of as an ongoing process over time that uses many types of information rather than a single event of collecting one type of information. Specifically, scientists will need to identify common characteristics rather than just differences of the spatial distribution of weeds among fields and species, recognize that map accuracy may be a poor indicator of the value of a sampling plan, and develop methods to use growers' knowledge of the distribution of weeds and past spatially variable management within a field for both making a map and recommending a sampling plan. The value of proposed methods for sampling and mapping must also be demonstrated or adoption of site-specific weed management might be limited to growers who enjoy using sophisticated technology.

Keywords

Geostatisticsscoutingspatial correlationspatial dependence
Type
Symposium
Information
Weed Science , Volume 53 , Issue 2 , April 2005 , pp. 228 - 235
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

Audsley, E. and Beaulah, S. A. 1996. Combining weed maps to produce a treatment for patch spraying. Asp. Appl. Biol 46:111–117.Google Scholar
Berti, A., Zanin, G., Baldoni, G., Grignani, C., Mazzondini, M., Montemurro, P., Tei, F., Vazzanan, C., and Viggianti, P. 1992. Frequency distribution of weed counts and applicability of a sequential sampling method to integrated weed management. Weed Res 32:39–44.Google Scholar
Buntin, G. D. 1994. Developing a primary sampling program. Pages 99–115 in Pedigo, L. P. and Buntin, G. D. eds. Handbook of Sampling Methods for Arthropods in Agriculture. Boca Raton, FL: CRC.Google Scholar
Burgess, T. M., Webster, R., and McBratney, A. B. 1981. Optimal interpolation and isarithmic mapping of soil properties. IV. Sampling strategy. J. Soil Sci 32:643–699.CrossRefGoogle Scholar
Burrough, P. A. 1991. Sampling designs for quantifying map unit composition. Pages 89–125 in Mausbach, M. J. and Wilding, L. P. eds. Spatial Variabilities of Soils and Landforms. SSSA Special Publ. 28. Madison, WI: Soil Science Society of America.Google Scholar
Cardina, J., Johnson, G. A., and Sparrow, D. H. 1997. The nature and consequence of weed spatial distribution. Weed Sci 45:364–373.Google Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. 1995. Analysis of spatial distribution of common lambsquarters (Chenopodium album) in no-till soybean. Weed Sci 43:258–268.CrossRefGoogle Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. 1996. Spatial relationships between seedbank and seedling populations of common lambsquarters (Chenopodium album) and annual grasses. Weed Sci 44:298–308.Google Scholar
Clay, S. A., Lems, G. J., Clay, D. E., Forcella, F., Ellsbury, M. E., and Carlson, C. G. 1999. Sampling weed spatial variability on a fieldwide scale. Weed Sci 47:674–681.CrossRefGoogle Scholar
Colbach, N., Dessaint, F., and Forcella, F. 2000a. Evaluating field-scale methods for the estimation of mean plant densities. Weed Res 40:411–430.CrossRefGoogle Scholar
Colbach, N., Forcella, F., and Johnson, G. A. 2000b. Spatial and temporal stability of weed populations over five years. Weed Sci 48:366–377.CrossRefGoogle Scholar
Cousens, R. D., Brown, R. W., McBratney, A. G., and Moerkerk, M. 2002. Sampling strategy is important for producing weed maps: a case study using kriging. Weed Sci 50:542–546.Google Scholar
Davis, P. 1993. Statistics for describing populations. Pages 33–55 in Pedigo, L. P. and Buntin, G. D. eds. Handbook of Sampling Methods for Arthropods in Agriculture. Boca Raton, FL: CRC.Google Scholar
Dieleman, J. A. and Mortensen, D. A. 1999. Characterizing the spatial pattern of Abutilon theophrasti seedling patches. Weed Res 39:455–467.Google Scholar
Dille, J. A., Milner, M., Groeteke, J. J., Mortensen, D. A., and Williams, M. M. II. 2002a. How good is your weed map? A comparison of spatial interpolators. Weed Sci 51:44–55.CrossRefGoogle Scholar
Dille, J. A., Mortensen, D. A., and Young, L. J. 2002b. Predicting weed species occurrence based on site properties and previous year's weed presence. Precision Agric 3:193–207.Google Scholar
Faechner, T., Norrena, K., Thomas, A. G., and Deutsch, C. V. 2002. A risk-qualified approach to calculate locally varying herbicide application rates. Weed Res 42:476–485.Google Scholar
Flatman, G. T., Englund, E. J., and Yfanis, A. A. 1988. Geostatistical approaches to the design of sampling regimes. Pages 73–84 in Keith, L. H. ed. Principles of Environmental Sampling. Washington DC: American Chemical Society.Google Scholar
Gerhards, R., Wyse-Pester, D. Y., Mortensen, D. A., and Johnson, G. 1997. Characterizing spatial stability of weed populations using interpolated maps. Weed Sci 45:108–119.Google Scholar
Gold, H. J., Bay, J., and Wilkerson, G. G. 1996. Scouting for weeds based on the negative binomial distribution. Weed Sci 44:504–510.Google Scholar
Gotway, C. A., Ferguson, R. B., and Hergert, G. W. 1996. The effects of mapping and scale on variable-rate fertilizer recommendations for corn. Pages 321–330 in Robert, P. C., Rust, R. H., and Larson, W. E. eds. Precision Agriculture. Minneapolis, MN: American Society of Agronomy.Google Scholar
Goudy, H. J., Bennett, K. A., Brown, R. B., and Tardif, F. J. 2001. Evaluation of site-specific weed management using a direct-injection sprayer. Weed Sci 49:359–366.Google Scholar
Hausler, A. and Nordmeyer, H. 1999. Characterizing spatial and temporal dynamics of weed seedling populations. Pages 463–472 in Stafford, J. V. ed. Proceedings of the 2nd European Conference on Precision Agriculture, Odense, Denmark. London: SCI.Google Scholar
Heisel, T., Andreasen, C., and Ersboll, A. K. 1996. Annual weed distributions can be mapped with kriging. Weed Res 36:325–337.Google Scholar
Heisel, T., Ersboll, A. K., and Andreasen, C. 1999. Weed mapping with co-kriging using soil properties. Precision Agric 1:39–52.Google Scholar
Isaaks, E. H. and Srivastava, R. M. 1989. An Introduction to Applied Geostatistics. New York: Oxford University Press. Pp. 249–322.Google Scholar
Ives, P. M. and Moon, R. D. 1987. Sampling theory and protocol for insects. Pages 49–75 in Teng, P. S. ed. Crop Loss Assessment and Pest Management. St. Paul, MN: APS.Google Scholar
Johnson, G. A., Cardina, J., and Mortensen, D. A. 1997. Site-specific weed management: Current and future directions. Pages 131–147 in Robert, P. C., Rust, R. H., and Larson, W. E. eds. Site-specific Management for Agricultural Systems. Minneapolis, MN: American Society of Agronomy.Google Scholar
Johnson, G. A., Mortensen, D. A., and Gotway, C. A. 1996a. Spatial and temporal analysis of weed seedling populations using geostatistics. Weed Sci 44:704–710.Google Scholar
Johnson, G. A., Mortensen, D. A., Young, L. J., and Martin, A. R. 1996b. Parametric sequential sampling based on multistage estimation of the negative binomial parameter k . Weed Sci 44:555–559.Google Scholar
Krueger, D. W., Wilkerson, G. G., and Gold, H. J. 2000. An economic analysis of binomial sampling for weed scouting. Weed Sci 48:53–60.Google Scholar
Lamb, D. W. and Weedon, M. 1998. Evaluating the accuracy of mapping weeds in fallow fields using airborne digital imaging: Panicum effusum in oilseed rape stubble. Weed Res 38:443–451.Google Scholar
Medlin, C. R., Shaw, D. R., Cox, M. S., Gerard, P. D., Abshire, M. J., and Wardlaw, M. C. III. 2001. Using soil parameters to predict weed infestations. Weed Sci 49:367–374.Google Scholar
Nyrop, J. P., Foster, R. E., and Onstad, D. W. 1986. Value of sample information in pest control decision making. J. Econ. Entomol 79:1421–1429.CrossRefGoogle Scholar
Oliver, M. A. 1999. Exploring soil spatial variation geostatistically. Pages 463–472 in Proceedings of the 2nd European Conference on Precision Agriculture, Odense, Denmark. London: SCI.Google Scholar
Oliver, M. A., Frogbrook, Z., Webster, R., and Dawson, C. J. 1997. A rational strategy for determining the number of cores for bulked soil samples. Pages 155–162 in Stafford, J. V. eds. Precision Agriculture '97. Oxford, UK: Bios Scientific.Google Scholar
Oriade, C. A., King, R. P., Forcella, F., and Gunsolus, J. L. 1996. A bioeconomic analysis of site-specific management for weed control. Rev. Agric. Econ 18:523–535.Google Scholar
Pedigo, L. 1993. Introduction to sampling arthropod populations. Pages 1–11 in Pedigo, L. P. and Buntin, G. D. eds. Handbook of Sampling Methods for Arthropods in Agriculture. Boca Raton, FL: CRC.Google Scholar
Rew, L. J. 1997. The importance of patch mapping resolution for sprayer control. Asp. Appl. Biol 48:49–55.Google Scholar
Rew, L. J. and Cousens, R. 2000. Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate? Weed Res 41:1–18.CrossRefGoogle Scholar
Rew, L. J., Whelan, B., and McBratney, A. B. 2001. Does kriging predict weed distributions accurately enough for site-specific weed control? Weed Res 41:245–263.Google Scholar
Rossi, R. E., Borth, P. W., and Tollefson, J. J. 1993. Stochastic simulation for characterizing ecological spatial patterns and appraising risk. Ecol. Appl 3:719–735.CrossRefGoogle ScholarPubMed
Rossi, R. R., Mulla, D. J., Journel, A. G., and Franz, E. H. 1992. Geostatistical tools for modeling and interpreting ecological spatial dependence. Ecol. Monogr 62:277–314.Google 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 14:235–247.CrossRefGoogle Scholar
Walter, A. M., Christensen, S., and Simmelsgaard, S. E. 2002. Spatial correlation between weed species and soil properties. Weed Res 42:26–38.Google Scholar
Walter, A. M., Heisel, T., and Christensen, S. 1997. Shortcuts in weed mapping. Pages 777–784 in Stafford, J. V. ed. Precision Agriculture '97. Oxford, UK: Bios Scientific.Google Scholar
Weisz, R., Fleischer, S., and Smilowitz, Z. 1995. Site-specific integrated pest management for high value crops: sample units for map generation using the Colorado potato beetle (Coleoptera: Chrysomelidae) as a model system. J. Econ. Entomol 88:1069–1080.CrossRefGoogle ScholarPubMed
Wiles, L. J. and Brodahl, M. 2004. Exploratory data analysis to identify factors influencing spatial distributions of weed seed banks. Weed Sci. 52:936–947.Google Scholar
Wiles, L. J., Canner, S. R., and Bosley, D. B. 1998. Talking about weed pressure: an interview survey of farmer and crop consultant descriptions of weed density level. Proc. West. Weed Sci. Soc 51:117.Google Scholar
Wiles, L. J. and Schweizer, E. E. 2002. Spatial dependence of weed seed banks and strategies for sampling. Weed Sci 50:595–606.Google Scholar
Wyse-Pester, D. Y., Wiles, L. J., and Westra, P. 2002. Infestation and spatial dependence of weed seedling and mature weed populations in corn. Weed Sci 50:54–63.Google Scholar
Zanin, G., Berti, A., and Riello, L. 1998. Incorporation of weeds spatial variability into the weed control decision-making process. Weed Res 38:107–118.CrossRefGoogle Scholar