Evaluating soil quality indices in an agricultural region of Jiangsu Province, China

Agricultural soil quality evaluation is essential for economic success and environmental stability in rapidly developing regions. At present, a wide variety of methods are used to evaluate soil quality using vastly different indicators. A universally accepted method of soil quality evaluation would assist agriculture managers, scientists, and policy makers to better understand the soil quality conditions of various agricultural systems. This study analyzes the soil quality of Zhangjiagang County, a rapidly developing region of China (n = 431), using the Integrated Quality Index (IQI) and Nemero Quality Index (NQI) in combination with three indicator selection methods: Total Data Set (TDS), Minimum Data Set (MDS), and Delphi Data Set (DDS). A total of 22 soil parameters were used with the TDS method. These six combinations of soil quality evaluation methods were then analyzed to determine which is best suited for soil quality evaluation in the county. All evaluation methods revealed that the county has fair to favorable soil quality with Anthrosols (Inceptisols) generally having higher quality than Cambosols (Entisols). Regression and correlation analysis all showed that the IQI preformed better than the NQI, in three indicator selection methods and IQI match analysis was 9% higher than NQI. Though the TDS method is the most accurate, it was concluded that using the IQI index and the MDS method can adequately represent the TDS method (r2 = 0.65) and thus save time and money.