An identified agronomic interpretation for potassium permanganate oxidizable carbon

Abstract

The absence of clear empirical relationships between soil health and agronomic outcomes remains an obstacle to widespread adoption of soil health assessments in row crop systems. The objectives of this research were to (1) determine whether soil health indicators are connected to corn (Zea mays L.) productivity and (2) establish interpretive benchmarks for soil health indicators in Missouri. The objectives were accomplished by collecting corn grain yield at 446 monitoring sites (37 m²) in 84 commercial production fields in 2018–2020. Soil health and soil fertility samples were collected prior to planting at each site. These data, along with site-specific soil and weather data, were modeled using traditional stepwise regression and nonparametric random forest (RF) and conditional inference forest (CIF) approaches. Root-mean-square errors were similar (1.4–1.5 Mg ha⁻¹) with distinct R² improvements over stepwise regression for both CIF (R² = 0.45) and RF (R² = 0.46) algorithms. Only seasonal rainfall and potassium permanganate oxidizable carbon (POXC) were included as top factors governing grain productivity in each model approach, thus demonstrating a regionally robust empirical relationship between POXC and grain productivity. Partial dependency analysis and two decision tree approaches identified 415 mg POXC kg⁻¹ as a threshold for maximum grain productivity, providing a framework for regional interpretation of on-farm soil health assessments. Little evidence was found connecting grain productivity with autoclaved citrate extractable protein and soil respiration. These findings underscore the power of POXC as an emerging soil health indicator to assess and quantify soil management effects on grain productivity.