Flowering prediction for flood-irrigated rice in the Midwest and North regions of Brazil.
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This study aimed to analyze the influence of climatic and geographic variables on the flowering process of flood-irrigated rice in the Midwest and North regions of Brazil. Agronomic data from the breeding program were related to the following variables: air temperature, relative humidity, global solar radiation, rainfall, degree days, latitude, longitude, and altitude. The analysis was performed using Multiple Linear Regression (MLR) and Generalized Additive (GAM) models. Cross-validation determined the most suitable model. The GAM model showed the best performance for both regions. In the Midwest and North of Brazil, flowering was strongly influenced by climate variables related to temperature. The rise in minimum temperatures tends to advance flowering. Higher minimum accumulated temperatures tend to delay flowering.
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Predictive model, Arroz, Oryza Sativa, Fenologia, Temperatura, Umidade Relativa, Radiação Solar, Clima, Phenology, Climate, Rice, Solar radiation, Relative humidity, Air temperature