Determination of Minimum Data Set for Soil Health Assessment of Farmlands under Wheat–Maize Crop System in Yanting County, Sichuan, China

Abstract

The assessment of soil health through a robust index system having a sufficient number of indicators is an important step toward sustainable crop production. The present study aimed at establishing a minimum data set (MDS) from soil functional and nutritional attributes using a dual index system to evaluate the soil health of farmlands under wheat (Triticum aestivum)–maize (Zea mays) crop rotation in Yanting County, Sichuan, China. Farms from 10 villages in the study area were selected, out of which three sites were considered healthy/ideal sites and used as a reference for the remaining seven targeted sites, and soil samples were collected at depth of 20 cm from these farms. The MDS indicators were selected by using principal component analysis (PCA) followed by Pearson’s correlation on 25 attributes. Based on significant values, eight attributes were retained in the final MDS, including the sucrase level, pH, wilting coefficient, water holding capacity, organic matter, NK ratio, total potassium, and available phosphorus. Based on the results, most of the farmland soils in Yanting County were in a healthy condition, accounting for 61.71% of the surveyed samples, followed by sub-healthy, degraded, and weak soils, accounting for 19.64%, 9.71%, and 8.93%, respectively. The values of most of the indicators at the targeted sites were significantly lower than those at ideal sites. Thus, specific steps should be taken by adding soil organic matter, combined with other fertilizers, to enhance the microbial biomass, enzymatic activities, and other biological activities in the soil.

Keywords

• minimum data set
• soil health
• soil health index
• Yanting County
• PCA