Abstract

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.

Highlights

  • Soil is an important natural resource and the carrier of most natural and social environments

  • No definition of soil quality has been universally accepted, but most experts emphasize that soil productivity depends on soil quality, so most research results of soil quality assessments are based on soil nutrient indicators [3,4]

  • The spatial distribution of soil quality was similar to those of SOM and TN throughout the basin as their weights were heavy in the assessment process, and the influence of AP on soil quality was mainly seen in the south of the basin, where the high content of AP led to good soil quality

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Summary

Introduction

Soil is an important natural resource and the carrier of most natural and social environments. There are some unreasonable conditions in the threshold setting processes of indicators and assessment results; for example, most research indicators are often standardized or directly graded according to the indicator values [16], and the grade values are used as evaluation parameters for overlay analysis [17]. This strict grading method has been questioned in term of its reasonability, though there is no recognized classification standard of soil quality [18]

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