When do I want to know and why? Different demands on sugarcane yield predictions

Abdel-Rahman, 2008, The application of remote-sensing techniques to sugarcane (Saccharum spp. hybrid) production: a review of the literature, Int. J. Remote Sens, 29, 3753, 10.1080/01431160701874603 Ahumada, 2009, Application of planning models in the agri-food supply chain: a review, Eur. J. Oper. Res, 195, 1, 10.1016/j.ejor.2008.02.014 Bégué, 2010, Spatio-temporal variability of sugarcane fields and recommendations for yield forecasting using NDVI, Int. J. Remote Sens, 31, 5391, 10.1080/01431160903349057 Bezuidenhout, 2011, An evaluation of the literature on integrated sugarcane production systems – a scientometrical approach, Outlook Agric, 40, 79, 10.5367/oa.2011.0025 Bezuidenhout, 2007, Operational forecasting of South African sugarcane production: part 1 – System description, Agric. Syst, 92, 23, 10.1016/j.agsy.2006.02.001 Bezuidenhout, 2007, Operational forecasting of South African sugarcane production: part 2 – System evaluation, Agric. Syst, 92, 39, 10.1016/j.agsy.2006.03.002 Brüggemann, E., Klug, J., Greenfield, P., Dicks, H., 2001. Empirical modelling and prediction of sugarcane yields from field records, In: Proc. S. Afr. Sug. Technol. Ass. p. 75. Danese, 2011, The role of the forecasting process in improving forecast accuracy and operational performance, Int. J. Prod. Econ, 131, 204, 10.1016/j.ijpe.2010.09.006 El Hachemi, 2011, A hybrid constraint programming approach to the log-truck scheduling problem, Ann. Oper. Res, 184, 163, 10.1007/s10479-010-0698-x Everingham, 2002, Enhanced risk management and decision-making capability across the sugarcane industry value chain based on seasonal climate forecasts, Agric. Syst, 74, 459, 10.1016/S0308-521X(02)00050-1 Everingham, 2009, Ensemble data mining approaches to forecast regional sugarcane crop production, Agric. Forest Meteorol, 149, 689, 10.1016/j.agrformet.2008.10.018 Fleischmann, 2003, Planning hierarchy, modeling and advanced planning systems, 455, 10.1016/S0927-0507(03)11009-2 Franco, 2011, Nitrogen in sugarcane derived from fertilizer under Brazilian field conditions, Field Crops Res, 121, 29, 10.1016/j.fcr.2010.11.011 Grunow, 2007, Supply optimization for the production of raw sugar, Int. J. Prod. Econ, 110, 224, 10.1016/j.ijpe.2007.02.019 Higgins, 2002, Australian sugar mills optimize harvester rosters to improve production, Interfaces, 32, 15, 10.1287/inte.32.3.15.41 Higgins, 2007, Opportunities for value chain research in sugar industries, Agric. Syst, 94, 611, 10.1016/j.agsy.2007.02.011 Hoekstra, R.G., 1976. Analysis of when to plough a sugarcane field, In: Proc. S. Afr. Sug. Technol. Ass. pp. 103–113. Hoogenboom, 2000, Contribution of agrometeorology to the simulation of crop production and its applications, Agric. Forest Meteorol, 103, 137, 10.1016/S0168-1923(00)00108-8 Inman-Bamber, 2005, Water relations in sugarcane and response to water deficits, Field Crops Res, 92, 185, 10.1016/j.fcr.2005.01.023 Jena, 2013, Harvest planning in the Brazilian sugar cane industry via mixed-integer programming, Eur. J. Oper. Res, 230, 374, 10.1016/j.ejor.2013.04.011 Jiao, 2005, An integrated statistical and optimisation approach to increasing sugar production within a mill region, Comput. Electron. Agric, 48, 170, 10.1016/j.compag.2005.03.004 Jones, 2003, The DSSAT cropping system model, Eur. J. Agron, 18, 235, 10.1016/S1161-0301(02)00107-7 Keating, 2003, An overview of APSIM, a model designed for farming systems simulation, Eur. J. Agron, 18, 267, 10.1016/S1161-0301(02)00108-9 Keerthipala, A., Dharmawardene, N., 2001. Determining optimal replanting cycles of sugarcane, In: Proc. Int. Soc. Sugar Cane Technol. pp. 65–69. Kreipl, 2004, Planning and scheduling in supply chains: an overview of issues in practice, Prod. Oper. Manag, 13, 77, 10.1111/j.1937-5956.2004.tb00146.x Lawes, 2005, Applications of industry information in sugarcane production systems, Field Crops Res, 92, 353, 10.1016/j.fcr.2005.01.033 Le Gal, 2009, Coupled modelling of sugarcane supply planning and logistics as a management tool, Comput. Electron. Agric, 68, 168, 10.1016/j.compag.2009.05.006 Lisson, 2005, The historical and future contributions of crop physiology and modelling research to sugarcane production systems, Field Crops Res, 92, 321, 10.1016/j.fcr.2005.01.010 Lustig, 2001, Program does not equal program: constraint programming and its relationship to mathematical programming, Interfaces, 31, 29, 10.1287/inte.31.6.29.9647 Masoud, 2011, A job-shop scheduling approach for optimising sugarcane rail operations, Flex. Serv. Manuf. J., 23, 181, 10.1007/s10696-011-9092-5 Meinke, 2005, Seasonal and inter-annual climate forecasting: the new tool for increasing preparedness to climate variability and change in agricultural planning and operations, Clim. Change, 70, 221, 10.1007/s10584-005-5948-6 Mutanga, 2013, Determining the best optimum time for predicting sugarcane yield using hyper-temporal satellite imagery, Adv. Remote Sens, 2, 269, 10.4236/ars.2013.23029 Peidro, 2009, Quantitative models for supply-chain planning under uncertainty: a review, Int. J. Adv. Manuf. Technol, 43, 400, 10.1007/s00170-008-1715-y Piewthongngam, 2009, Application of crop-growth simulation and mathematical modeling to supply chain management in the Thai sugar industry, Agric. Syst, 102, 58, 10.1016/j.agsy.2009.07.002 Ramburan, 2011, Interpretation of genotype × environment interactions of sugarcane: identifying significant environmental factors, Field Crops Res, 124, 392, 10.1016/j.fcr.2011.07.008 Rudorff, 1990, Yield estimation of sugarcane based on agrometeorological-spectral models, Remote Sens. Environ, 33, 183, 10.1016/0034-4257(90)90029-L Salassi, 2002, Economically optimal crop cycle length for major sugarcane varieties in Louisiana, J. Am. Soc. Sugarcane Technol, 22, 53 Spiertz, 2013, Challenges for crop production research in improving land use, productivity and sustainability, Sustainability, 5, 1632, 10.3390/su5041632 Stadler, 2012, Introduction, 1 Stadtler, 2005, Supply chain management and advanced planning – basics, overview and challenges, Eur. J. Oper. Res, 163, 575, 10.1016/j.ejor.2004.03.001 Stadtler, 2009, A framework for collaborative planning and state-of-the-art, OR Spectr, 31, 5, 10.1007/s00291-007-0104-5 Stray, 2012, An optimisation-based seasonal sugarcane harvest scheduling decision-support system for commercial growers in South Africa, Comput. Electron. Agric, 83, 21, 10.1016/j.compag.2012.01.009 Tonta, 1996, Determination of optimum number of ratoons in sugarcane by the discounted cash flow technique, Int. Soc. Sug. Cane Technol, 22, 8 van Ittersum, 2003, On approaches and applications of the Wageningen crop models, Eur. J. Agron, 18, 201, 10.1016/S1161-0301(02)00106-5 Weintraub, 2006, Operations research models and the management of agricultural and forestry resources: a review and comparison, Interfaces, 36, 446, 10.1287/inte.1060.0222 Wiedenfeld, 1995, Effects of irrigation and N fertilizer application on sugarcane yield and quality, Field Crops Res, 43, 101, 10.1016/0378-4290(95)00043-P