Operational forecasting of South African sugarcane production: Part 1 - System description

Agricultural Systems

Volumn 92, Issue 1-3, 2007, Pages 23-38

  Bezuidenhout, C N ^a   Singels, A ^a  

^a SOUTH AFRICAN SUGARCANE RESEARCH INSTITUTE   (South Africa)

Author keywords

Canesim; Climate forecast; Crop forecasting; Model; Sugarcane; Yield forecast

Indexed keywords

CLIMATIC REGION; CROP PRODUCTION; FORECASTING METHOD; SIMULATION; SUGAR CANE;

AFRICA; SOUTH AFRICA; SOUTHERN AFRICA; SUB-SAHARAN AFRICA;

EID: 33751261090     PISSN: 0308521X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agsy.2006.02.001     Document Type: Article

References (37)

1. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration - guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56. FAO, Rome, Italy, 301p.
2. Anonymous, 2002. Seasonal Outlook for Southern Africa. Report of the South African Weather Services, Pretoria, South Africa, 2pp.
3. Bannayan M., and Crout N.M.J. A stochastic modelling approach for real-time forecasting of winter wheat yield. Field Crops Research 62 (1999) 85-95
4. Bezuidenhout, C.N., 2001. A proposed framework for operational crop forecasts in the South African sugar industry. In: Proceedings of the Annual Congress of the South African Sugar Technologists' Association, vol. 75. Durban, South Africa, pp. 215-216, ISSN 1028-3781.
5. Bezuidenhout, C.N., Gers, C., 2002. Homogeneous climate zones for the South African sugar industry: preliminary boundaries. In: Proc. S. Afr. Sug. Technol. Ass., vol. 76. Durban, South Africa, pp. 601-605, ISSN 1028-3781.
6. Bezuidenhout, C.N., Singels, A., 2001. The use of simulation crop modelling to forecast sugarcane yield. In: Proceedings of the SASTA Workshop on Burn/Harvest to Crush Delays and Crop Estimating. 8 November 2001, Mt. Edgecombe, South Africa, pp. 20-29.
7. Bezuidenhout, C.N., Singels, A., 2006. Operational forecasting of South African sugarcane production: Part 2 - System Evaluation, Agricultural Systems, in press.
8. Camp, K., 1999. Bioresource classification of KwaZulu-Natal. M.Sc. Dissertation, University of Natal, Pietermaritzburg, South Africa.
9. de Jager J.M., Potgieter A.B., and van den Berg W.J. Framework for forecasting the extent and severity of drought in maize in the Free State Province of South Africa. Agricultural Systems 57 (1998) 351-365
10. de Lange, J., Singels, A., 2003. Using the internet-based Canesim model for crop estimation in the Umfolozi mill supply area. In: Proc. S. Afr. Sug. Technol. Ass., vol. 77. Durban, South Africa, pp. 592-595, ISSN 1028-3781.
11. Engel T., Hoogenboom G., Jones J.W., and Wilkens P.W. AEGIS/Win: a computer program for the application of crop simulation models across geographical areas. Agronomy Journal 89 (1997) 919-928
12. Everingham Y.L., Muchow R.C., Stone R.C., Inman-Bamber N.G., Singels A., and Bezuidenhout C.N. Enhanced risk management and decision-making capability across the sugarcane industry value chain based on seasonal climate forecasts. Agricultural Systems 74 (2002) 459-477
13. Everingham Y.L., Inman-Bamber N.G., Ticehurst C., Barrett D., Lowe K., and McNeill T. Yield forecasting for marketers. Proceedings of the Australian Society of Sugar Cane Technologists 27 (2005) 51-60
14. Gers, C., Schmidt, E.J., Bezuidenhout, C.N., 2001. Validation of the CANESIM sugarcane growth model using GIS within the South African sugar industry. In: Proceedings of the 21st Annual ESRI International User Conference, Paper 416. San Diego, USA, 9-13 July 2001.
15. Hansen J.W., and Jones J.W. Scaling-up crop models for climate variability applications. Agricultural Systems 65 1 (2000) 43-72
16. Hansen J.W., Potgieter A., and Tippett M.K. Using a general circulation model to forecast regional wheat yields in northeast Australia. Agricultural and Forest Meteorology 127 (2004) 77-92
17. Hartkamp A.D., White J.W., and Hoogenboom G. Interfacing geographic information systems with agronomic modeling: a review. Agronomy Journal 91 (1999) 761-772
18. Hildebrand, Q.L., 1998. Maximising profits from sugar through optimising the length of the milling season. In: Proceedings of the Annual General Meeting of the South African Sugar Agronomists Association, 26 November 1998, Mt. Edgecombe, South Africa, pp. 1-6.
19. Horie T., Yajima M., and Nakagawa H. Yield forecasting. Agricultural Systems 40 (1992) 211-236
20. Lumsden, T.G., 2000. Development and evaluation of a sugarcane yield forecasting system. M.Sc. Dissertation. School of Bioresources Engineering and Environmental Hydrology, University of Natal, Pietermaritzburg, South Africa, 134pp.
21. Lumsden, T.G., Lecler, N.L., Schulze, R.E., 1998. Simulation of sugarcane yield at the scale of a mill supply area. In: Proc. S. Afr. Sug. Technol. Ass., vol. 72. Durban, South Africa, pp. 12-17, ISSN 1028-3781.
22. Maas S.J. Using satellite data to improve model estimates of crop yield. Agronomy Journal 80 (1988) 655-662
23. McGlinchey, M.G., Inman-Bamber, N.G., 1996. Predicting sugarcane water use with the Penman-Monteith equation. In: Proceedings of the Evapotranspiration and Irrigation Scheduling, American Society of Agricultural Engineers. San Antonio, USA, pp. 592-597.
24. McGlinchey, M.G., 1999. Computer crop model applications: developments in Swaziland. In: Proc. S. Afr. Sug. Technol. Ass., vol.73. Durban, South Africa, pp. 35-38.
25. Promburom P., Jintrawet A., and Ekasingh M. Estimating sugarcane yields with Oy-Thai interface. Proceedings of the International Society of Sugar Cane Technologists 24 (2001) 81-86
26. Roebeling, R., Rosema, A., Oroda, A., 1999. REFEWS: Regional Famine Early Warning System for the IGAD Regional. BCRS Report NRSP-2, 99-17, pp. 9-22.
27. Schmidt, E.J., 1998. Forecasting the sugarcane crop. Publication of the South African Sugar Association, The Link, vol. 7(4), p. 11.
28. Schulze, R.E., 1997. South African atlas of agrohydrology and climatology. Water Research Commission, Report TT82/96, Pretoria, South Africa.
29. Singels, A., Donaldson, R.A., 2000. A Simple model of unstressed sugarcane canopy development. In: Proc. S. Afr. Sug. Technol. Ass., vol. 74. Durban, South Africa, pp. 151-154, ISSN 1028-3781.
30. Singels, A. Kennedy, A.J., Bezuidenhout, C.N., 1998. IRRICANE: a simple computerised irrigation scheduling method for sugarcane. In: Proc. S. Afr. Sug. Technol. Ass., vol. 72. Durban, South Africa, pp. 117-122, ISSN 1028-3781.
31. Singels A., Bezuidenhout C.N., and Schmidt E.J. Evaluating strategies for scheduling supplementary irrigation of sugarcane in South Africa. Proceedings of the Australian Society of Sugar Cane Technologists, Brisbane 21 (1999) 219-226
32. Singels, A, Kennedy, A.J., Bezuidenhout, C.N., 2000. The effect of water stress on sugarcane biomass accumulation and partitioning. In: Proc S. Afr. Sug Technol. Ass. Congress, vol. 74. Durban, South Africa, pp. 169-172, ISSN 1028-3781.
33. Spitters C.J.T., Toussaint H.A.J.M., and Goudriaan J. Separating the diffuse and direct component of global radiation and its implications for modelling canopy photosynthesis. Part 1 - Components of incoming radiation. Agricultural and Forest Meteorology 38 (1986) 217-229
34. Stephens D.J., Butler D.G., and Hammer G.L. Using seasonal climate forecasts in forecasting the Australian wheat crop. In: Hammer G.L., Nicholls N., and Mitchell C. (Eds). Applications of Seasonal Climate Forecasting in Agrocultural and Natural Ecosystems - The Australian Experience vol. 351-366 (2000), Kluwer Academic, The Netherlands. 0-7923-6270-5 469pp
35. Stephens W., and Middleton T. Tools to support strategic decision making. In: Matthews R.B., and Stephens W. (Eds). Crop-Soil Models: Applications in Developing Countries (2002), CAB International, Wallingford, UK,. 0851995632 304pp
36. Supit I. Predicting national wheat yields using crop simulation and trend models. Agricultural and Forest Meteorology 88 (1997) 199-214
37. Turner M.G., Dale V.H., and Gardner R.H. Predicting across scales: theory development and testing. Landscape Ecology 3 3/4 (1989) 245-252