Produtividade da soja associada a variáveis agrometeorológicas utilizando estatísticas circular e espacial de área, no estado do Paraná

• Ano de defesa: 2019
• Autor(a) principal: Silva, Edilza Martins da
• Orientador(a): Guedes , Luciana Pagliosa Carvalho
• Banca de defesa: Guedes , Luciana Pagliosa Carvalho , Dalposso , Gustavo Henrique , Mercante , Erivelto
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Oeste do Paraná; Cascavel
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Agrícola
• Departamento: Centro de Ciências Exatas e Tecnológicas
• País: Brasil
• Palavras-chave em Português: Análise temporal; Data do máximo vegetativo; Dados Espaciais
• Palavras-chave em Inglês: Temporal analysis; Spatial data; Maximum vegetative data; 10-day; Seasonality
• Área do conhecimento CNPq: CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://tede.unioeste.br/handle/tede/4468

The productivity of the soybean crop is influenced by several factors, which interfere directly in all the phenological stages of the plant. In this context, agrometeorological variables, such as precipitation (mm), temperature (°C), solar radiation (MJ dia-1), and evapotranspiration (mm), as well as their spatial distribution should be evaluated as to how they interfere with the productivity of a crop. The objective of this study was to analyze and correlate the values and temporal variability of some agrometeorological variables with the soybean yield in the state of Paraná in the 2011/2012 and 2013/2014 crop years. Firstly, a descriptive analysis of the distribution of soybean yield and measures associated with agrometeorological variables was performed. Next, the spatial distribution of these variables was evaluated through the global and local Moran indices, univariate and bivariate, between productivity and agrometeorological variables. In addition, the mean moment of greatest concentration of the agrometeorological variables was analyzed, as well as the presence of their seasonality, employing the circular statistic. The results showed that the productivity and all the measures associated with the agrometeorological variables presented significant spatial autocorrelation. In general, there was a direct and significant spatial association of productivity with precipitation values, as well as an inverse and significant spatial association of productivity with values of temperature, solar radiation, and evapotranspiration. Regarding the seasonality of the agrometeorological variables, precipitation was the only variable that did not show uniformity as to its temporal distribution in the evaluated intervals, occurring, on average, a larger amount of rain in the 10-day of the date of maximum vegetative development, as well as in the one to two 10-day intervals around the date of the maximum vegetative. Thus, it can be concluded that regions of Paraná State with higher or lower soybean yield are correlated with the amount of agrometeorological variables at the time of moment of maximum vegetative development (DMDV) and at close intervals, as well as the occurrence of seasonality in the intervals considered in the two-year study periods.