: Prediction of winter wheat phenology using meteorological data in three different climatic regions of Iran

Wheat (Triticum aestivum) is one of the major crops in the world and Iran. Any plan for improvement of wheat yield requires sufficient information on different stages of crop life cycle and the effects of meteorological parameters. The purpose of this study was developing suitable regression models for prediction the length of pheonological stage of winter wheat in three different regions of Iran namely; Parsabad، Gharakheil and Hasanabad and using daily maximum، minimum and average temperature، relative humidity and total rainfall in each phenological stages. The models were developed and tested in existing record period (14، 10 and eight years for three stations respectively). The best form of equation between meteorological variables and length of pheonological stage were chosen out of four different types of linear، logarithmic، exponential and power based on the R2، RMSE، MAE statistics at 95 and 99% level of significance. The comparison between simulated and observed dates of phonological events was done using index of agreement. The results showed that in the case of Parsabad station except for tillering and ripening stages، the relation of other stages were significant at 95% level of confidence. In the other stations، less number of equations was significant. Due to complexity of agricultural systems، annual variation of meteorological variables and their interactions، to come to valid conclusions، all the models should be tested at other stations of Iran.