Modeling Growth and Yield of Sunflower (Helianthus annus L.)

Abstract

Sunflower (Helianthus annus L.) is one of the most important oil seed crops in Iran. In spite of very progressing in production mechanization and varieties breeding, weather is still one of the most important determining factors for growth and production crops. Under optimal water and nutrient supply, radiation and temperature are two important factors for determining of production and dry matter accumulation. Quantification of the effect of radiation and effect of temperature on growth and yield of sunflower is important in selecting this crop for different agro-climatic situation. Environmental limitations in production at each regional can be evaluated using a crop simulation model and prolong weather data. The model operates simulation daily and it has four segments include simulation of leaf area index, light interception, dry matter production and seed yield. For testing model, the capability of the model was determined to predicting of leaf area index and accumulated dry matter production. Paired data of observed and simulated for both leaf area index and accumulated dry matter were tested by t test. Between paired data were not significant (α =0.05). Also linear regression between observed and simulated values for leaf area index and accumulated dry matter explained more than 95% of variability.