Regression Models For Saffron Yields in Iran

Saffron is an important crop in social and economical aspects in Khorassan Province (Northeast of Iran). In this research we tried to evaluate trends of saffron yield in recent years and to study the relationship between saffron yield and the climate change. A regression analysis was used to predict saffron yield based on 20 years of yield data in Birjand, Ghaen and Ferdows cities. Climatologically data for the same periods was provided by database of Khorassan Climatology Center. Climatologically data included temperature, rainfall, relative humidity and sunshine hours for Model , and temperature and rainfall for Model . The results showed the coefficients of determination for Birjand, Ferdows and Ghaen for Model were 0.69, 0.50 and 0.81 respectively. Also coefficients of determination for the same cities for model were 0.53, 0.50 and 0.72 respectively. Multiple regression analysis indicated that among weather variables, temperature was the key parameter for variation of saffron yield. It was concluded that increasing temperature at spring was the main cause of declined saffron yield during recent years across the province. Finally, yield trend was predicted for the last 5 years using time series analysis.