1. Comprehensive yield gap analysis and optimizing agronomy practices of soybean in Iran
- Author
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Afshin Soltani, Amir Hajjarpoor, A. Dadrasi, A. Nehbandani, and Farshid Nourbakhsh
- Subjects
0106 biological sciences ,Irrigation ,Food security ,Phosphorus ,fungi ,Yield gap ,food and beverages ,chemistry.chemical_element ,Sowing ,Growing season ,04 agricultural and veterinary sciences ,01 natural sciences ,Crop ,chemistry ,Agronomy ,Yield (wine) ,040103 agronomy & agriculture ,Genetics ,0401 agriculture, forestry, and fisheries ,Animal Science and Zoology ,Agronomy and Crop Science ,010606 plant biology & botany ,Mathematics - Abstract
Soybean is one of the key oil crops in global food security. The objective of the current study was to determine the magnitude of soybean yield and yield gaps (Yg) in the main producing regions in Iran, the main causes and possible solutions to reduce these gaps and improve yields. This study uses an integrated approach of crop simulation and on-farm information. The SSM-iCrop2 model was used to calculate the potential yield (Yp). Furthermore, management information of soybean farms (the number of monitored farms was 224) was collected and analysed with two methods, including stepwise regression (a production model was created and based on it, the yield-limiting factors were determined) and boundary line analysis (show the optimum level of crop management and simultaneously the percentage of farms that were out of the optimal range of a specific management procedure). The results showed a Yp of 4681 kg/ha while actual yield (Ya) was around 2257 kg/ha. The main factors causing Yg of soybean in Iran were irrigation, nitrogen fertilizer, phosphorus fertilizer and sowing date. Altering soybean sowing date to late June or early July, irrigating at least five times during the growing season, applying at least 50 kg/ha nitrogen and 45 kg/ha phosphorus base application are foremost management practices that could shrink the soybean yield gap in Iran. The results presented in this study can bring relevant transferable information to other soybean production areas sharing the same latitudes and climate, and the approach can be used for other crops worldwide.
- Published
- 2020