Performance of soil quality indicators in estimation and distribution of rapeseed yield.

This research aimed to evaluate the quality of soils for rapeseed crop production by Boolean and fuzzy-analytical hierarchy process (FAHP) approach in northwest of Iran. To this purpose, the physical, chemical, and topography quality indicators of land were selected based on agricultural considerations that were obtained from 83 fields. The spatial distribution of soil quality indicators was prepared using inverse distance weighting (IDW) technique. Also, validation of the developed model was performed using composite operator. The results showed that physical and chemical properties were key deciding parameters for the evaluation of soil quality. In the developed models, clay, sand, silt, soil organic matter, pH, calcium carbonate equivalent, electrical conductivity, and elevation were selected as modeling parameters. AHP technique showed that soil texture and elevation had the strongest and weakest influences on rapeseed yield, respectively. By dividing lands into four suitability categories, FAHP could more easily classify lands into soil quality classes where 36.3% of the study area was permanently unsuitable, 39.7% was marginally suitable, 22.6% was moderately suitable, and 1.4% was suitable. The comparison results of soil quality and rapeseed yield map by composite operator showed that FAHP with 77% agreement provided better results than Boolean approach with 39% agreement. Finally, this research will provide a reasonable record in ensuring crop yield security, agronomic use and management of rapeseed as well as increasing crop income. Hence, FAHP was introduced as an efficient approach.