Simulação do crescimento, desenvolvimento e produtividade de arroz no Rio Grande do Sul com o modelo simularroz

• Ano de defesa: 2013
• Autor(a) principal: Rosa, Hamilton Telles
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• dARK ID: ark:/26339/0013000012fqc
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Agronomia; UFSM; Programa de Pós-Graduação em Agronomia
• Palavras-chave em Português: Oryza sativa; Modelo agrícola; Modelagem; Fitomassa; Grãos; Aplicativo; Crop model; Modeling; Biomass; Grains; Application; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/3223

The SimulArroz is an ecophysiological dynamic processes-based model for simulating the growth, development and grain yield of rice. In order to have scientific credibility, a simulation model has to be tested and exposed to different cropping conditions. Although this model is in use, constant studies and improvements have to be pursued so that new versions are released and able to accurately describe the complex interactions of factors that influence the growth, development and grain yield of rice. The objectives of this thesis were (i) to develop a generalized response function to atmospheric CO2 concentration [f(CO2)] for radiation use efficiency (EUR) in rice and (ii) to evaluate the performance of the SimulArroz model for simulating biomass of rice crop in the central region of Rio Grande do Sul State and grain yield in different rice production regions of the Rio Grande do Sul State with the original model and if the incorporation of a Radiation Use Efficiency (RUE) response function that varies with crop development. Independent data on RUE and grain yield from the literature were used to develop a RUE response function to CO2 and to test the ability of the model to predict grain yield. To test the biomass production with model, a field experiment was conducted in Santa Maria, RS, during the 2011/2012 and 2012/2013 growing seasons, with four cultivars IRGA 421 (very early cycle), BRS Querencia (early cycle) , IRGA 424 (mid cycle) and SCSBRS Tio Taka (long cycle) and three sowing dates in the first year (October, 17th, November, 18th, and December, 19th of 2011) and one sowing date in the second year (October 19th, 2012). The SimulArroz model is efficient in simulating the growth, development, and grain yiel of rice in the state of Rio Grande do Sul, being able to do it in climate change scenarios.