Study of the performance sourban Plains of Parsabad considering temperature using linear regression model

Abstract: Soy products such as strategic and important and revenue to different areas respectively. According to statistics, 20.8% of the land under cultivation of this crop Ardebil province that nearly all production in the province Parsabad area due to unique climatic characteristics, do not lie. This study was conducted to study the effect of climatic parameters on the yield of soybean in the city Parsabad to come and multivariate regression model was used to do it. The data used in this study include: total monthly rainfall, mean daily temperature, mean minimum temperature, mean maximum temperature, average temperature absolute minimum, mean absolute maximum temperature, average moisture, humidity, average minimum, average, maximum moisture and Statistics Jihad during the period 2000 to 2015 is agriculture. The relationship between climatic variables and crop yield of soybean in three regression models Enter, stepwise, Backward on soybean growth period studied. Fitted equations to estimate indicated that the soybean yield, precipitation variables, June, July, August and May and June temperatures, moderate humidity and maximum humidity of October and minimum humidity of July, the best results were shown to express functional changes The importance of these elements is climate soybean plants during the growing season. Also according to the index R- Square regression equation was found that over 99 percent dependent variable (soybean) are explained by the independent variables used in the regression model. Finally, of the three models to predict crop yield model as the optimal model Backward Seville was chosen in Parsabad. Keywords: Pars Abad, multiple regression, climatic parameters, yield of soybea