The combination of a simulation and an empirical model of crop/weed competition to estimate yield loss from Alopecurus myosuroides in winter wheat

Field Crops Research

Volumn 84, Issue 3, 2003, Pages 291-301

  Storkey, J ^a   Cussans, J W ^a   Lutman, P J W ^a   Blair, A M ^b  

^a ROTHAMSTED RESEARCH   (United Kingdom)

^b ADAS BOXWORTH   (United Kingdom)

Author keywords

Alopecurus myosuroides; Relative damage coefficient; Weed management

Indexed keywords

COMPUTER SIMULATION; LIGHT; WEED CONTROL;

COMPETITION TRIALS;

CROPS;

CROP YIELD; MODELING; WEED CONTROL; YIELD RESPONSE;

ALOPECURUS; ALOPECURUS MYOSUROIDES; TRITICUM AESTIVUM;

EID: 0344304407     PISSN: 03784290     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-4290(03)00096-0     Document Type: Article

References (31)

1. Cousens, R., 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107, 239-252.
2. Cousens, R., Doyle, C.J., Wilson, B.J., Cussans, G.W., 1986. Modelling the economics of controlling avena-fatua in winter-wheat. Pest. Sci. 17, 1-12.
3. Cousens, R., Brain, P., O'Donovan, J.T., O'Sullivan, P.A., 1987. The use of biologically realistic equations to describe the effects of weed density and relative time of emergence on crop yield. Weed Sci. 35, 720-725.
4. Cussans, J.W., Lutman, P.J.W., Storkey, J., Blair, A.M., Corbett, S.J., Green, M., Hill, A.L., McDonald, H., 1996. Inter-site variability in crop-weed interference in winter wheat. In: Streibig, J.C. (Ed.), Proceedings of the Second International Weed Control Congress. Department of Weed Control and Pesticide Ecology, Flakkebjerg, Denmark, pp. 203-208.
5. Doyle, C.J., Cousens, R., Moss, S.R., 1986. A model of the economics of controlling Alopecurus myosurodies Huds. in winter-wheat. Crop Prot. 5, 143-150.
6. Heap, I.M., 1997. The occurrence of herbicide resistant weeds worldwide. Pest. Sci. 51, 235-243.
7. Ingle, S., Blair, A.M., Cussans, J.W., 1997. The use of weed density to predict winter wheat yield. Asp. Appl. Biol. 50, 393-399.
8. Krebbs, J.R., Wilson, J.D., Bradbury, R.B., Siriwardena, G.M., 1999. The second silent spring? Nature 400, 611-612.
9. Kropff, M.J., Spitters, C.J.T., 1991. A simple model of crop loss by weed competition from early observations on relative leaf area of the weeds. Weed Res. 31, 97-105.
10. Kropff, M.J., Spitters, C.J.T., 1992. An eco-physiological model for interspecific competition, applied to the influence of Chenopodium album L. on sugar beet. I. Model description and parameterisation. Weed Res. 32, 437-450.
11. Kropff, M.J., Vossen, F.J.H., Spitters, C.J.T., 1984. Competition between a maize crop and a natural population of Echinochloa crus-galli (L.) P.B. Neth. J. Agric. Sci. 32, 324-327.
12. Kropff, M.J., van Kraalingen, D.W.G., van Laar, H.H., 1993. Program structure of the model INTERCOM. In: Kropff, M.J., van Laar, H.H. (Eds.), Modelling Crop-Weed Interactions. CAB International, Oxon, UK, pp. 201-246.
13. Kropff, M.J., Lotz, L.A.P., Weaver, S.E., Bos, H.J., Wallinga, J., Migo, T., 1995. A two parameter model for prediction of crop yield loss by weed competition by early observations of relative leaf area for weeds. Ann. Appl. Biol. 126, 329-346.
14. Lotz, L.A.P., Christensen, S., Cloutier, D., Fernandez Quintanilla, C., Legere, A., Lemieux, C., Lutman, P.J.W., Pardo Iglesias, A., Salonen, J., Sattin, M., Stigliani, L., Tei, F., 1996. Prediction of the competitive effects of weeds on crop yields based on the relative leaf area of weeds. Weed Res. 36, 93-101.
15. Lundkvist, A., 1997. Weed management models. Swed. J. Agric. Res. 27, 155-166.
16. Lutman, P.J.W., Cussans, J.W., 1995. Potential of alternative methods of assessing weed infestations to predict crop/weed interference. Asp. Appl. Biol. 43, 189-196.
17. Lutman, P.J.W., Risiott, R., Ostermann, H.P., 1996. Investigation into alternative methods to predict the competitive effects of weeds on crop yields. Weed Sci. 44, 290-297.
18. Miller, P.C.H., Paice, M.E.R., 1998. Patch spraying approaches to optimise the use of herbicides applied to arable crops. J. R. Agric. Soc. Engl. 159, 70-81.
19. Payne, R.W., Lane, P.W., Ainsley, A.E., 1987. Genstat 5 Reference Manual. Clarendon Press, Oxford.
20. Penning de Vries, F.W.T., Berge, H.F.M.T., Bakema, A., 1974. Products, requirements and efficiency of biosynthesis: a quantitative approach. J. Theor. Biol. 45, 339-377.
21. Rimmington, G.M., 1984. A model of the effect of interspecies competition for light on dry matter production. Aust. J. Plant Physiol. 11, 277-286.
22. Sim, L.C., 1987. The value and practicality of using weed thresholds in the field. In: Proceedings of the British Crop Protection Conference on Weeds. BCPC, Brighton, pp. 1067-1071.
23. Spitters, C.J.T., 1989. Weeds: population dynamics, germination and competition. In: Rabbinge, R., Ward, S.A., van Laar, H.H. (Eds.), Simulation Monographs. Pudoc, Wageningen.
24. Spitters, C.J.T., Aerts, R., 1983. Simulation of competition for light and water in crop-weed associations. Asp. Appl. Biol. 4, 467-483.
25. Storkey, J., 2001. A physiological approach to understanding weed competition. Ph.D. Thesis. University of Nottingham, Sutton Bonington, 186 pp.
26. Storkey, J., Cussans, J.W., 2000. Relationship between temperature and the early growth of winter Triticum aestivum and three weed species. Weed Sci. 48, 467-473.
27. Storkey, J., Cussans, J.W., Lutman, P.J.W., 1999. The effect of time of assessment on predictions of yield loss from relative vigour. In: Proceedings of the 11th European Weed Research Society (EWRS) Symposium, Basel, 51 pp.
28. Storkey, J., Cussans, J.W., Lutman, P.J.W., 2000. Visual assessment of weed ground cover to predict yield loss. Is this a practical alternative to the measurement of leaf area? In: Proceedings of the XI International Conference on Weed Biology. AFPP, Dijon, France, pp. 281-288.
29. Weaver, S.E., Kropff, M.J., Cousens, R., 1993. A simulation model of Avena fatua (wild oat) growth and development. Ann. Appl. Biol. 122, 537-554.
30. Wilkerson, G.G., Jones, J.W., Coble, H.D., Gunsolus, J.L., 1990. SOYWEED: a simulation model of soybean and common cocklebur growth and competition. Agron. J. 82, 1003-1010.
31. Wilson, B.J., Wright, KJ., Brain, P., Clements, M., Stephens, E., 1995. Predicting the effects of weed and crop density on weed biomass, weed seed production and crop yield in wheat. Weed Res. 35, 265-278.