An integrated statistical and optimisation approach to increasing sugar production within a mill region

Computers and Electronics in Agriculture

Volumn 48, Issue 2, 2005, Pages 170-181

  Jiao, Zhaorong ^a   Higgins, Andrew J ^a   Prestwidge, Diane B ^a  

^a CSIRO   (Australia)

Author keywords

CCS; CCS trend group; Harvesting scheduling; Linear programming; Polynomial regression; Sugar cane

Indexed keywords

COMPUTER SOFTWARE; CROPS; HARVESTING; LINEAR PROGRAMMING; MATHEMATICAL MODELS; OPTIMIZATION; PARAMETER ESTIMATION; POLYNOMIALS; STATISTICAL METHODS;

MILL CRUSHING; SECOND-ORDER POLYNOMIALS; SUGAR CONTENT OF CANE (CCS);

SUGAR INDUSTRY;

SUGAR CANE;

FARM CROPS; HARVESTING; LINEAR PROGRAMING; MATHEMATICAL MODELS; OPTIMIZATION; STATISTICAL ANALYSIS;

SACCHARUM; SACCHARUM HYBRID CULTIVAR;

EID: 22444433823     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2005.03.004     Document Type: Article

References (14)

1. J. Alvarez, D.R. Crane, T.H. Spreen, and G. Kidder A yield prediction model for Florida sugarcane Agric. Syst. 9 1982 161 179
2. A. Brooke, D. Kendrick, A. Meeraus, and R.E. Raman GAMS: A User's Guide, GAMS Development Corporation 2003 GAMS Development Corporation Washington, DC, USA
3. R.N. Ellis, K.E. Basford, M. Cooper, J.K. Leslie, and D.E. Byth Analysis of sugarcane yield productivity trends in the wet tropics at a district level Proceedings of the Australian Society of Sugarcane Technologists, vol. 22 2000 283 289
4. J.W.B. Guise, and G.J. Ryland Production scheduling and allocation: a normative decision model for sugar milling Aust. J. Agric. Econ. 13 1969 8 24
5. A.J. Higgins, R.C. Muchow, A.V. Rudd, and A.W. Ford Optimising harvest date in sugar production: a case study for the Mossman mill region in Australia Field Crop Res. 57 1998 153 162
6. A.J. Higgins Optimising cane supply decisions within a sugar mill region J. Sched. 2 1999 229 244
7. A.J. Higgins, M.A. Haynes, R.C. Muchow, and D.B. Prestwidge Developing and implementing optimised harvest schedules through participatory research Aust. J. Agric. Res. 55 2002 297 306
8. N.G. Inman-Bamber Some physiological factors affecting the optimum age and season for harvesting sugarcane Proceedings of the South African Sugar Technologists' Association, June 10-12, vol. 65 Durban and Mount Edgecombe, South Africa 1991 pp. 103-107
9. N.G. Inman-Bamber Effect of age and season on components of yield of sugarcane in South Africa Proceedings of the South African Sugar Technologists' Association, June 6-9, vol. 68 Durban and Mount Edgecombe, South Africa 1994 pp. 23-26
10. R.A. Lawes, M.K. Wegener, K.E. Basford, and R.J. Lawn Commercial cane sugar trends in the Tully sugar district Aust. J. Exp. Agric. 40 2000 969 973
11. McDonald, L.M., Wood, A.W., 2001. Pre-harvest season productivity of sugarcane in different regions of Queensland, In: Hogarth, D.M. (Ed.), Proceedings of the Australian Society of Sugarcane Technologists, May 1-4, vol. 23, Mackay, Queensland, pp. 90-96.
12. H. Rostron The effects of age and time of harvest on the productivity of irrigated sugar cane Proceedings of the South African Sugar Technologists' Association, June 5-9, vol. 46 Mount Edgecombe, South Africa 1972 pp. 142-150
13. M.E. Salassi, J.B. Breaux, and C.J. Naquin Modelling with-in sugarcane growth for optimal harvest system selection Agric. Syst. 73 2002 261 278
14. B.M. Whan, C.H. Scott, and T.R. Jefferson Scheduling sugar cane plant and ratoon crops and fallow - a constrained Markov model J. Agric. Eng. Res. 21 1976 281 289