Soil quality assessment of croplands in the black soil zone of Jilin Province, China: Establishing a minimum data set model

Soil quality assessment is an effective way to improve understanding of the heterogeneity of soil quality and to encourage the adoption of proper agricultural practices. The object of this paper is to select the most effective soil quality indices and the minimum data set (MDS) for the black soil zone of Jilin Province, China, and analyze the association between soil quality and the environmental control. Taking the croplands of the black soil zone of Jilin Province, China, as the study area, different combinations of scoring methods, indices, and data set methods were compared. A minimum data set, based on the integrated quality index derived from non-linear scoring methods (MDSIQI-NLS index), was then selected via principal components analysis to assess the soil quality of the study area. The determined minimum data set for the study area included bulk density, cation exchange capacity, soil organic matter, alkali-dissolvable N, total K, extractable Cu, and extractable Fe. The results showed that the soil quality in the study area was of dominantly moderate grades (grades II, III and IV), accounting for approximately 90% of the total as well as the minimum data set, and the soil quality index increased from the northwest to the southeast. Group analysis was applied because different combinations of environmental factors play different roles in different sub-regions. The analysis results showed that the most important factors affecting soil quality in group 1 (in decreasing order of importance) were: mean annual temperature, DEM, amount of straw return, parent material, and topographic wetness index. For group 2 they were: parent material, annual precipitation, mean annual temperature, chemical fertilizer, DEM, amount of straw return. This analysis proves to be an effective way to determine the factors that affect the spatial distribution of soil quality.