Simulation of biomass and sugar accumulation in sugarcane using a process-based model

A crop simulation model (QCANE) was developed to simulate growth and sugar accumulation in sugarcane. QCANE is based on crop growth and development pr ocesses including canopy development, photosynthesis, respiration, and the partitioning of carbohydrates to plant organs for growth and respiration as dictated by phenological development and changing environments. Seasonal t emperature changes and shading in lower layers of the canopy are used to de termine leaf senescence and canopy development. Photosynthesis is simulated by incorporating diurnal light variation and canopy light attenuation into the rectangular hyperbolic relationship between leaf-photosynthesis and li ght intensity. Simulation of respiration is related to temperature and biom ass accumulation. Partitioning of carbohydrates into leaf, non-millable, to p, cane and root components of the crop uses temperature related functions which differ for different stages of crop development. A smoothing spline t echnique was used to account for the autocorrelation over time of sequentia l observations used for validation of the model. Root mean squared error (R MSE) and 'performance efficiency' (PE) were used for assessing the model pe rformance. Validation of the model against data from an independent experim ent at Bundaberg (a sub-tropical environment) resulted in RMSE values of 0. 64 m(2) m(-2), 231 g m(-2), 279 g m(-2) and 124 g m(-2), respectively for l eaf area index (L), cane dry matter accumulation (W-c), sugar accumulation (S-c) and fabre accumulation (F-c). PE values indicated that model accounte d for 86, 98, 91 and 95% of variance observed in L, W-c, S-c, and F-c, resp ectively. The validation was extended to a tropical environment for an expe riment conducted at Ingham. The result was RMSE values of 1.15 m(2) m(-2), 722 g m(-2), and 254 g m(-2) and the simulation accounted for 48, 86 and 92 % of variance observed in L, W-c, and S-c, respectively. The flexibility an d capacity of model to be applied to the simulation of climate changes are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.