Assessment of multiple regression equations for yield estimation of rain-fed wheat and barley in different Iran’s climates

Document Type : Research Paper


1 Assistant Professor, Department of Environment Science and Engineering, Faculty of Agriculture and Environment, Arak University, Iran.

2 Assistant Professor, Department of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Iran.

3 Assistant Professor, Department of Water Engineering, College of Aburaihan, University of Tehran, Tehran, Iran.


Iran is located in the arid and semi-arid area and it is very necessary to assess the conditions of rainfed farming of strategic plants. In order to assessment of wheat and barley yield under rainfed climatic conditions collected data from 44 stations were studied during the period of 1981-2020 (40 years). Weather data after spatial interpolation between stations and converting to daily values were used as inputs of a multiple regression model for estimating wheat and barley yield. In this study, Iran was divided into six coastal wet, mountain, semi mountain, semi desert, desert and, coastal desert. The results showed that the highest and lowest annual rainfall was observed in stations Bandar Anzali (1748 mm y-1) and Zabol (57.7 mm y-1), respectively. The greatest and lowest decrease in rainfall occurred in Bandar-Anzali station (gradient 5.8 percent) and, in Kermanshah station (gradient -0.8 percent) respectively. Only 11.36 percent of the stations were in good condition and, in other stations were in a critical situation (88.64 percent). The results of this study showed that the coefficient of determination of predicted yield for rainfed wheat in humid climates was more accurate than in other climates (R2=0.83). The lowest coefficient of determination predicted yield was obtained for rain-fed wheat (R2=0.71) and rain-fed barley (R2=0.53) in desert climates.


Main Subjects

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