A Standardized Soil Quality Index for Diverse Field Conditions.

Understanding the nexus between soil quality and productivity is constrained by the lack of standard methods and limitations of data and existing models. Here, we use mathematical and statistical models to synthesize soil property information into a soil quality index (SQI) that quantifies the functionality of a soil relative to anticipated potential, under diverse land management scenarios. A range of land uses and management (e.g., natural vegetation (i.e., forest) soil, soil under conventional till, no-till, and no till with cover crops and manure) scenarios were selected from different individually owned farmers’ fields within the state of Ohio, USA. Soils were sampled at similar landscape positions at depth intervals of 0-10, 10-20, 20-40 and 40-60 cm, and analyzed for bulk density (?b), carbon/nitrogen (C/N) ratio, soil organic C (SOC), total N (TN), available water capacity (AWC), pH and electrical conductivity (EC). Four variables (i.e., SOC, ?b, CN and EC) respectively exerted a more dominant influence on the SQI. The data shows that the quality of Pewamo silty clay loam (Pw) soil was higher than for Crosby Celina loams (CtA), Kibbie fine sandy loam (kbA), Glynwood silt loam (GWA) and Crosby silt loam (CrA), respectively. The mean SQI, corn and soybean yields was 42.9 %, 7 and 2 Mg/ha; and the SQI model fit versus corn and soybean yields had an R2 of 0.74, 0.89, respectively.