Probabilidade de ocorrência de excesso hídrico para a cultura da soja em planossolos da região central do Rio Grande do Sul

• Ano de defesa: 2014
• Autor(a) principal: Bortoluzzi, Mateus Possebon
• Orientador(a): Heldwein, Arno Bernardo
• Banca de defesa: Lago, Isabel , Trentin, Gustavo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria
• Programa de Pós-Graduação: Programa de Pós-Graduação em Agronomia
• Departamento: Agronomia
• País: BR
• Palavras-chave em Português: Glycine max; Balanço hídrico; Datas de semeadura; Risco agroclimático; Análise numérica; Função densidade de probabilidade
• Palavras-chave em Inglês: Glycine max (L.) Merrill; Water balance; Sowing dates; Climate risk; Numerical analysis; Historical series; Probability density function
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/5129

The expansion of soybean production area in Planosols is rather limited by the high frequency of occurrence of excess water, leading to reduced availability of oxygen in the root zone, reduced photosynthesis, as well as productivity, depending on its duration and developmental phase of plants it occurs. The aim of this study was to identify sowing dates with smaller risk of excess water to the subperiods and crop cycle, taking into account three relative maturity groups of soybean cultivars and water storage capacity of Planosols in the central region of Rio Grande do Sul State. The simulation of soybean development and the calculation of crop daily sequential water balance were performed at different sowing dates in each year from August 1968 to July 2012. Thus, the change of soil water storage and the water surpluses in the different soybean developmental phases were quantified for each sowing date. Data from days with excess water were submitted to analysis of variance and Scott-Knott test at 5% probability, and the sources of variation were sowing dates, soils and their interaction. These data also were submitted to the probability distribution analysis, using the chi-square and Kolmogorov-Smirnov tests to verify the probability density function that best fit the data distribution. The greatest number of fittings for the development cycle and subperiods were obtained by the Gamma and Weibull functions, respectively. October's sowings have the highest risk of excess water during the crop cycle. Subperiod sowing-emergence shows up as the most limiting to define the sowing date. Due to the lowest risk of excess water in this sub-period, the sowing carried out after November 1st are the most favorable for soybean sowing in Planosols.