Considering the importance of irrigated rice production in the State of Rio Grande do Sul and that its performance is influenced by the weather conditions, the objective of this study was to estimate the grain yield of this crop as a function of global solar radiation and minimum air temperature using procedures of linear simple and multiple regression. A field experiment was conducted at the district of Capão do Leão, State of Rio Grande do Sul, Brazil, during three growing seasons. Six sowing dates and eight cultivars of distinct groups of cycle lengths were used in each crop season. Ten main culms of each cultivar were marked to determine the main stages of development. The dependent variable (Y) was the average grain yield of four repetitions of each sowing date and the independent variables were: the average of global solar radiation (X¹), the average minimum air temperature (X²) and the average of squared minimum air temperature (X³), computed for four periods of plant development for global solar radiation and for three periods for minimum air temperature. Most of the variables, when tested isolately, presented a significant linear relationship with grain yield, but the coefficients of determination (r²) were higher in multiple linear regressions involving the main variables. Regression models that use global solar radiation and minimum air temperature in distinct physiological periods of plant development as predicting variables, are suitable for estimating grain yields of irrigated rice.
Oryza sativa L.; grain yield; regression model; plant development stage
