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 m 2 ) 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 R 2 improvements over stepwise regression for both CIF (R 2 = 0.45) and RF (R 2 = 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.

Addressing within-field and within-season variability of crop water stress is critical for spatially variable irrigation. This study measures interactions between spatially variable soil properties and temporally variable crop water dynamics; and whether modelling soil water depletion is an effective approach to guide variable-rate irrigation (VRI). Energy and water balance equations were used to model crop water stress at 85 locations within a 22 ha field of winter wheat (Triticum aestivum L.) under uniform and spatially variable irrigation. Significant within-field variability of soil water holding capacity (SWHC; 145–360 mm 1.2 m−1), soil electrical conductivity (0.22–49 mS m−1), spring soil water (314–471 mm 1.2 m−1), and the onset of crop water stress were observed. Topographic features and modelled onset of crop water stress were significant predictors of crop yield while soil moisture at spring green-up, elevation, and soil electrical conductivity were significant predictors of the onset of crop water stress. These results show that modelling soil water depletion can be an effective scheduling tool in VRI. Irrigation zones and scheduling efforts should consider expanding to include temporally dynamic factors, including spring soil water content and the onset of crop water stress.

Adjacent fields with contrasting histories present an opportunity to evaluate the legacy of management on soil health (SH) and grain productivity. In 2011, two fields transitioned to no‐till grain production. During the previous 25 yr, one was pasture (pasture‐to‐grain; PTG), whereas the other was annually tilled for grain cropping (long‐term grain; LTG). The study objectives were to contrast these two fields relative to SH and productivity. Yield data was collected from 2011 to 2021 and SH sampled in 2021. The PTG out‐yielded LTG each year, with an average 46% yield increase. 2021 SH metrics demonstrated similar trends, with PTG 62% higher than LTG. Contrasting across fields (2020–2021), SH metrics were related to yield (r2 = .46–.78), but these relationships weakened when assessed within each field. These findings affirm SH indicators are sensitive to the legacy of management and are meaningful indicators of productivity across sites but less informative for within‐field variability.

Soil health benefits are widely acknowledged but empirically-vetted connections to agronomic outcomes remain absent. Therefore, recommendations for on-farm soil health assessments and interpretation remain ambiguous. Empirical connections to two major outcomes remain absent, specifically row crop productivity and fertilizer recommendations. This dissertation investigates potential benefits from incorporating soil health indicators with established phosphorus (P) and potassium (K) fertilizer recommendations, evaluates links between soil health indicators and corn grain productivity, and identifies optimal sampling depths and regional sensitivity to common conservation practices for seven unique soil health indicators. All results and conclusions derive from a dataset collected over three seasons (2018-2020) including 446 sample locations collected from 101 Mid-Missouri commercial row crop systems. Current P and K fertilizer recommendations accurately identified where fertilizer improved yield with 42 and 34 percent accuracy, respectively. No significant or measurable benefit occurred from incorporating soil health indicators with established P and K soil nutrient analysis when identifying nutrient deficiencies. Investigations into general productivity discovered an empirical relationship between potassium permanganate oxidizable carbon (or POXC) and grain yield. This relationship identified a POXC value of [greater than] 415 mg kg soil-1 where corn productivity was optimized. Further, POXC outperformed all other established soil analyses in predicting corn grain yield. Finally, regional sensitivity analysis of soil biological indicators of soil health identified important environmental and soil properties to consider when interpreting soil health assessments in Mid-Missouri. Recommendations were unique for each soil health assessment, with specific conservation practices and optimal sampling depth. In total, these results provide the needed groundwork connecting soil health with agronomic outcomes to support on-farm soil health interpretations.

Integrating soil health (SH) biological properties with soil fertility (SF) evaluations offers a unique opportunity to potentially refine fertilizer recommendations. The objectives of this research included: (a) evaluating current University of Missouri P and K fertilizer recommendations for corn (Zea mays L.) and (b) assess whether SH biological indicators are effective predictors of yield response to P and K fertilization.In Missouri, 446 monitoring sites (148 m 2 ) were implemented on 101 production corn fields over the 2018-2020 growing seasons. For each monitoring site, SH and SF samples were collected prior to planting, followed by application of nonreplicated single-rate fertilizer treatments: (a) unfertilized control; (b) 112 kg ha -1 K 2 O; and (c) 112 kg ha -1 P 2 O 5 . At monitoring sites below recommended critical soil test values, P (n = 152) and K (n = 86) fertilization increased yield at 42 and 36% of the sites respectively, with average yield increasing 10 and 11% for P and K, respectively.At the lowest fertility ratings, P and K fertilization increased yield at 52 and 56% of sites, respectively, highlighting inherent uncertainty within current recommendations. Integrating SH with SF indicators failed to improve random forest algorithms prediction of yield increases from P or K fertilization. Further, variable importance ranking confirmed that current physiochemical SF tests remain the most effective factors identifying when a fertilizer response will likely occur. Although SH metrics may offer insight into other agronomic or environmental benefits, established SF evaluations remain the most effective available tool for guiding P and K fertilizer decisions in Missouri corn production.