Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-28T00:31:26.011Z Has data issue: false hasContentIssue false
  • English
  • Français

WEEDING: A Weed Ecology and Economic Decision Making INstructional Game

Published online by Cambridge University Press:  12 June 2017

Lori J. Wiles ,
Gail G. Wilkerson  and
Harold D. Coble
Lori J. Wiles
Affiliation:
Dept. Crop Sci., Box 7620, N.C. State University, NC 27695-7620
Gail G. Wilkerson
Affiliation:
Dept. Crop Sci., Box 7620, N.C. State University, NC 27695-7620
Harold D. Coble
Affiliation:
Dept. Crop Sci., Box 7620, N.C. State University, NC 27695-7620
Get access Rights & Permissions [Opens in a new window]

Abstract

Process-level simulation models can be a unique and effective medium for teaching concepts of crop biology and management which can usually only be studied in the field. WEEDING was developed from several research models to demonstrate concepts of weed ecology, herbicide efficacy and selectivity, and economic thresholds for weed control decisions. Users of WEEDING interactively grow a soybean crop, making management decisions throughout the seaason. The program includes real weather data and a realistic assortment of soybean varieties, soil types, weed species, and weed control options. Production costs and profit are calculated at the end of a simulated season. The structure of a process-level model driven by real weather data simulates the risk involved in management decisions.

Keywords

Soybean, Glycine max (L.) Merr.Simulation modelintegrated weed managementinstructional modelGlycine max
Type
Education
Information
Weed Technology , Volume 5 , Issue 4 , December 1991 , pp. 887 - 893
Copyright
Copyright © 1990 by the 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

1. Coble, H. D. 1986. Development and implementation of economic thresholds for soybean. p. 295–307 in Frisbie, R. E. and Adkisson, P. L., eds. CIPM: Integrated pest management on major agricultural systems. Texas A&M Univ. Google Scholar
2. D'alemda, D. J., Lynne, G. D., and Smajstrla, A. G. 1982. A users manual for the farm systems lab irrigation cost generator. Univ. of Fla., Econ. Inf. Rep. No. 157. 44 p.Google Scholar
3. Danneberger, T. K. 1988. TURFBLIGHT: An interactive turfgrass management model for teaching. J. Agron. Educ. 17:73–76.CrossRefGoogle Scholar
4. Danneberger, T. K., and Rieke, P. E. 1985. TURFGATION: A computer simulated water management game for turf. J. Agron. Educ. 14:35–37.CrossRefGoogle Scholar
5. Dunphy, E. J., and Neuman, D. F. 1987. North Carolina Farm Enterprise Budgets, Budget 73–2, Soybeans (Piedmont), 1/87.Google Scholar
6. Holt, D. A., Miles, G. E., Bula, R. J., Schreiber, M. M., and Peart, R. M. 1976. SIMED, a crop simulation model as a tool for teaching crop physiology. J. Agron. Educ. 5:53–56.CrossRefGoogle Scholar
7. Ingram, K. T., McCloud, D. E., Campbell, I. S., Duncan, W. G., McGraw, R. L., and Sibale, P. K. 1981. PNUTMOD: An educational model of crop growth and development simulated in a hand-held calculator. J. Agron. Educ. 10:36–42.CrossRefGoogle Scholar
8. Jones, J. W., Boote, K. J., Jagtap, S. S., Hoogenboom, G., and Wilkerson, G. G. 1988. SOYGRO V5.41: Soybean crop growth simulation model user's guide. Agric. Eng. Dep. and Agron. Dep., Univ. of Fla., Gainesville. Fla. Agric. Exp. Stn. J. No. 8304.Google Scholar
9. Mishoe, J. W., Chang, V. K., Jones, J. W., and Wilkerson, G. G. 1984. SOYGAME: Soybean management gaming model. Fla. Ext. Serv. Circ. No. 622. 29 p.Google Scholar
10. Mortensen, D. A., Coble, H. D., Smart, J. R., and Bauer, T. A. 1990. Use of an expert system for integrating weed control strategies in a weed science laboratory. J. Agron. Educ. 19:181–183.CrossRefGoogle Scholar
11. Pieters, E. P., Akbay, K. S., Brown, L. G., and McClendon, R. W. 1981. Use of computer game COTGAME in teaching entomology. Environ. Entomol. 10:256–261.CrossRefGoogle Scholar
12. Wiles, L. J., and Wilkerson, G. G. 1991. Modeling competition for light between soybean and broadleaf weeds. Agric. Systems. 35:37–51.CrossRefGoogle Scholar
13. Wilkerson, G. G., Modena, S. A., and Coble, H. D. 1991. HERB: Decision Model for postemergence weed control in soybeans. Agron. J. 83:413–417.CrossRefGoogle Scholar
14. Wilkerson, G. G., Jones, J. W., Boote, K. J., Ingram, K. T., and Mishoe, J. W. 1983. Modeling soybean growth for crop management. Trans. ASAE 26:63–73.CrossRefGoogle Scholar
15. Wilkerson, G. G., Jones, J. W., Coble, H. D., and Gunsolus, J. L. 1990. SOYWEED: A simulation model of soybean and cocklebur growth and competition. Agron. J. 82:1003–1010.CrossRefGoogle Scholar