Yield Gap Analysis Using Remote Sensing and Modelling Approaches: Wheat in the Northwest of Iran

• Published in: International journal of plant production 2020-09, Vol.14 (3), p.443-452
• Main Authors: Dehkordi, Parisa Alizadeh, Nehbandani, Alireza, Hassanpour-bourkheili, Saeid, Kamkar, Behnam
• Format: Article
• Language: English
• Subjects: Agriculture; Biomedical and Life Sciences; Life Sciences; Plant Ecology; Plant Physiology
• ISSN: 1735-8043; 1735-8043; 1735-6814
• DOI: 10.1007/s42106-020-00095-4

The reduction of the yield gap is one of the strategies implemented for the improvement of food security. In this research, the yield gap of wheat in the west of Golestan province, Iran, was estimated using a two-step methodology. In the first step, the potential yield was evaluated using the SSM-iCrop2 model and in the following, the yield gap was determined by the difference between the actual yield and potential yield. In the second step, the NDVI-actual yield regression in parallel with boundary-line analysis was used to assess the attainable yield. The estimated attainable yield varied from 3.0 to 5.8 t ha −1 . Accordingly, the attainable yield gap in the studied region was 2.6 t ha −1 on average, which could be obtained via improved management. Also, based on model outputs, the potential yield varied from 5.4 to 7.2 t ha −1 which suggests a high possibility to improve wheat yield in the west parts of Golestan province. The results of the study provided basic information to quantify the yield gap and yield optimization options. Our results revealed that remote sensing in combination with crop simulation models is a powerful tool in regional assessments and removes the limitations of working with point data.