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MODELLING OF GROWTH AND DEVELOPMENT OF CEREAL CROPS FOR RESOURCE MANAGEMENT

Published online by Cambridge University Press:  31 May 2012

Richard W. Jones
Richard W. Jones*
Affiliation:
Agriculture Canada Research Station, Kentville, N.S. B4N 1J5
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Abstract

In their simplest form, crop models consist of regressions relating factors such as yield to environmental variables. Explanatory models also exist, with much physiological detail and responsiveness to meteorological and soil factors. Summary models can be derived from such large models, including the influence of pests. Of these major types of models, regression models are increasingly becoming widely used to optimize and integrate the many facets of cereal management in Western Europe. This fact suggests that crop manipulation is evolving toward optimal production management.

Résumé

L'expression la plus simple d'un modèle de culture est une régression reliant des variables comme le rendement aux facteurs du milieu. Les modèles dits explicatifs incorporent quantité de détails physiologiques et de réponses aux facteurs du sol et du milieu. Des modèles particuliers peuvent être dérivés de ces modèles d'ensemble, y compris pour modéliser l'influence des organismes nuisibles. Parmi ces divers types de modèles, les modèles de régression sont de plus en plus utilisés afin d'optimiser et d'intégrer les diverses facettes de la régie des céréales en Europe de l'ouest. Ceci indique que la manipulation des cultures est en train d'évoluer vers une régie optimale de production.

Type
Research Article
Information
The Memoirs of the Entomological Society of Canada , Volume 120 , Supplement S143 , 1988 , pp. 39 - 45
Copyright
Copyright © Entomological Society of Canada 1988

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References

Anonymous. 1982. Farmer's Weekly, March 20, S10–S14.Google Scholar
Baier, W. 1973. Crop-weather analysis model: review and development. J. Appl. Meteorol. 12: 937–947.Google Scholar
Barr, R.O., Cota, P.C., Gage, S.H., Haynes, D.L., Kharkar, A.N., Koenig, H.E., Lee, K.Y., Ruesink, W.G., and Tummala, R.L.. 1972. Ecologically and economically compatible pest control, pp. 241–264 in Geier, P.W., Clark, L.R., Anderson, D.J., and Nix, H.A. (Eds.), Studies in Population Management, 14th International Congress of Entomology, Canberra.Google Scholar
Bennett, D., Downes, P.A., and Jones, A.V.J.. 1978. The 1978 phosphate fertilizer rates. Commonwealth Scientific and Industrial Research Organization, Canberra, Management Rep. 3.Google Scholar
Brockington, N.R. 1978. Simulation models in crop production research. Acta Agric. Scand. 28: 33–44.Google Scholar
Feyerherm, A.M., and Paulsen, G.M.. 1981. Development of a wheat yield prediction model. Agron. J. 73: 277–282.Google Scholar
France, J., and Thornley, J.H.M.. 1984. Mathematical models in agriculture. Butterworths, Toronto.Google Scholar
Hanks, R.J. 1974. Model for predicting plant yield as influenced by water use. Agron. J. 66: 660–665.Google Scholar
Haun, J.R. 1974. Prediction of spring wheat yields from temperature and precipitation data. Agron. J. 66: 405–409.Google Scholar
Hubbard, K.G., and Hanks, R.J.. 1983. Climate model for winter wheat simulation. J. Climate Appl. Meteorol. 22: 698–703.Google Scholar
Jenkins, J.E.E., and Lescar, L.. 1980. Use of foliar fungicides on cereals in Western Europe. Plant Dis. 64: 987–994.Google Scholar
Keulen, van H. 1976. A calculation method for potential rice production. Central Res. Inst. Agric, Bogor, Indonesia, Contribution 21.Google Scholar
Porter, J.R., and Day, W.. 1983. Report. Long Ashton Res. Stn., 144–146.Google Scholar
Rabbinge, R., and Rijsdijk, F.H.. 1983. EPIPRE: a disease and pest management system for winter wheat, taking account of micrometeorological factors. EPPO Bull. 12: 297–305.Google Scholar
Reinink, K., Jorritsma, L., and Darwinkel, A.. 1986. Adaptation of the AFRC wheat phenology model for Dutch conditions. Neth. J. Agric. Sci. 34: 1–13.Google Scholar
Sands, P. 1988. Resource modelling: its nature and use. pp. 5–10 in Cuff, W.R. (Ed.), Modelling in Support of Resource Management, Mem. ent. Soc. Can. 143. 59 pp.Google Scholar
Steyart, L.T., LeDuc, S.K., and McQuigg, J.D.. 1978. Atmospheric pressure and wheat yield modelling. Agric. Meteorol. 18: 23–34.Google Scholar
Vries, de F.W.T.P. 1983. Modelling of growth and production, pp. 117–150in Lange, O.L., Nobel, P.S., Osmond, C.B., and Ziegler, H. (Eds.), Physiological Plant Ecology 4, Encycl. Plant Physiol. vol 12D, Springer-Verlag, NY.Google Scholar
Weir, A.H., Braggs, P.L., Porter, J.R., and Rayner, J.H.. 1984. A winter wheat crop simulation model without water or nutrient limitations. J. Agric. Sci. 102: 371–382.Google Scholar
Wit, de C.T., and Goudriaan, J.. 1978. Simulation of ecological processes. PUDOC, Wageningen, Netherlands, Simulation monograph.Google Scholar