Yield gap estimation in wheat-grown fields using GIS and RS approach and SSM model (A case study: Qaresso basin, Gorgan, Iran)

Considering rising cereal prices and concern about global food security, researches are increasingly carrying out on the yield gap during recent years. Accurate estimation of the quantity and spatial distribution of the yield gap has many practical applications, such as using in precision farming. This study was aimed to evaluate the yield gap of wheat-grown fields in Qaresoo basin, Gorgan, Iran, using GIS, RS and the SSM model. For this purpose, the SSM model was used to estimate the radiation limited yield; the Landsat 8 to extract crop indices; regression models to relate crop indices and recorded yield in order to provide predicted yield raster layer; received radiation and the radiation-limited yield to provide studied basin’s radiation-limited yield and finally minus function to determine the final yield gap. The radiation-limited yield, predicted yield and yield gap of wheat grown fields, (which were detected using supervised method than other crops-grown fields), varied from 5.42 to 7.94 t.ha-1, 2.27 to 5.39 t.ha-1 and 1.67 to 4.88 t.ha-1 respectively. The results revealed that wheat-grown fields had a remarkable variance with respect to calculated regional yield factor (from 0.32 to 0.76). Considering environmental factors (soil-related, climatic and topographic factors), It is proposed to consider management factors as one of the important determiners of yield gap.