Analyzing the rainfed wheat yield gap in Northwest Iran

Abstract

Wheat is one of the major crops in Iran, covering more than 36% of the total croplands and more than 70% of rainfed farmlands. However, the trend of crop yield in the past decades does not show promising performance and the average yield of rainfed wheat in Iran is as low as 1250 ​kg ​ha⁻¹. Therefore, quantifying the rainfed wheat yield gap, and determining its causes and importance could help wheat self-sufficiency in Iran. Boundary line analysis (BLA) and regression tree (RT) models were employed to analyze the yield gap and find out the influencing factors. For this purpose, an on-farm survey was conducted in 210 rainfed winter wheat fields in East Azerbaijan province during the 2020–21 cropping season. Data were collected from local experts and farmers concerning crop yield and related management practices. Actual farmers’ yields were 1095 ​kg ​ha⁻¹. BLA showed a significant yield gap ranging from 1755 to 2186 ​kg ​ha⁻¹ (61.5–66.6% of attainable yield) and determined the attainable yield of 3072 ​kg ​ha⁻¹. The BLA indicated that, among the quantitative independent variables, nitrogen fertilizer and planting density management were the important managerial practices responsible for the yield gaps. Additionally, the pronounced differences in crop yield across various rotation systems and varieties highlight their critical role in realizing crop attainable yield as the qualitative independent variables. By the regression tree (RT) model, the yield gap was determined about 65%. Crop rotation, crop variety, and sowing date were determined as key factors influencing the rainfed wheat yield gap. Findings showed that the combination of BLA and RT methods can be used effectively to quantify the crop yield gap and its influencing factors. Regarding the large yield gap, there is a good opportunity to obtain higher yields by optimizing managerial practices/inputs.