Parametrização e avaliação do modelo DSSAT/Canegro para variedades brasileiras de cana-de-açúcar

O objetivo deste trabalho foi parametrizar e avaliar o modelo DSSAT/Canegro para cinco variedades brasileiras de cana-de-açúcar. A parametrização foi realizada a partir do uso de dados biométricos e de crescimento das variedades CTC 4, CTC 7, CTC 20, RB 86-7515 e RB 83-5486, obtidos em cinco localidades brasileiras. Foi realizada análise de sensibilidade local para os principais parâmetros. A parametrização do modelo foi feita por meio da técnica de estimativa da incerteza de probabilidade generalizada ("generalized likelihood uncertainty estimation", Glue). Para a avaliação das predições, foram utilizados, como indicadores estatísticos, o coeficiente de determinação (R2), o índice D de Willmott e a raiz quadrada do erro-médio (RMSE). As variedades CTC apresentaram índice D entre 0,870 e 0,944, para índice de área foliar, altura de colmo, perfilhamento e teor de sacarose. A variedade RB 83-5486 apresentou resultados similares para teor de sacarose e massa de matéria fresca do colmo, enquanto a variedade RB 86-7515 apresentou valores entre 0,665 e 0,873, para as variáveis avaliadas.

Simulação da produtividade de cana-de-açúcar nas regiões nordeste e sudeste do Brasil, utilizando o modelo DSSAT

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulação da produtividade de cana-de-açúcar (Saccharum officinarum L.) na região nordeste do Brasil, utilizando o modelo DSSAT

The objective of this study was to simulate the potential stem and sugar yield of sugar cane (Saccharum officinarum L.) in the Northeastern Brazil (Petrolina-PE and Teresina-PI) and analyze 4 varieties in different planting seasons in two environments: irrigated and rainfed cultivars. The model of simulation was DSSAT/CANEGRO (Decision Support System for Agrotechnology Transfer) and the four sugar cane varieties were as follows: RB86 7515, CTC 4, CTC 7 and CTC 20 (all in 1.5 year cycle). Analysis of variance was performed on the results and means were compared using the Tukey test with probability level at 5%. March is the recommended month for planting in Teresina, PI. In Petrolina, PE, rainfed planting is not advisable because of the extended water deficit all year long. In an irrigated environment, no difference was found concerning stem yield as a function of planting season, for all varieties in the study regions. The stem and sugar yields were always higher in irrigated environment as compared with those in rainfed environment in all municipalities and study varieties. The simulation model provided good estimate of stem and sugar yields as compared with experimental data in Teresina, PI.

Modelling, nitrogen dynamics in sugarcane systems: Recent advances and applications

Substantial amounts of nitrogen (N) fertiliser are necessary for commercial sugarcane production because of the large biomass produced by sugarcane crops. Since this fertiliser is a substantial input cost and has implications if N is lost to the environment, there are pressing needs to optimise the supply of N to the crops' requirements. The complexity of the N cycle and the strong influence of climate, through its moderation of N transformation processes in the soil and its impact on N uptake by crops, make simulation-based approaches to this N management problem attractive. In this paper we describe the processes to be captured in modelling soil and plant N dynamics in sugarcane systems, and review the capability for modelling these processes. We then illustrate insights gained into improved management of N through simulation-based studies for the issues of crop residue management, irrigation management and greenhouse gas emissions. We conclude by identifying processes not currently represented in the models used for simulating N cycling in sugarcane production systems, and illustrate ways in which these can be partially overcome in the short term. (c) 2005 Elsevier B.V. All rights reserved.