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The Mun River basin is one of the main grain-producing areas of Thailand, and the rainy season is the main period for crop planting after being idle during the dry season. However, the soil conditions are variable, so an assessment of soil quality during the rainy season is necessary for improving soil condition and crop production. The aim of this study was to conduct a soil quality assessment based on soil samples. To attain that, a minimum data set theory was used to screen evaluation indicators and geographically weighted regression was performed to obtain spatial interpolations of indicators, while the fuzzy logic model was used to determine the soil quality results. The results showed that the contents of indicators had similar spatial trends as their contents declined from the western to the eastern region of the basin. The soil quality results showed that the poor soil was in the middle of the basin, where the main land use is paddy fields, and the good soil was in the southwest of the basin, where forests and dry fields are widely distributed. The results indicated that the soil quality in the Mun River basin varied greatly, especially for farmland, so these findings will be helpful for improving soil conditions and grain production in the Mun River basin.

A Study of the Spatial Difference of the Soil Quality of The Mun River Basin during the Rainy Season