|SVEDIN, JEFFERY - University Of Missouri|
|ANDERSON, STEPHEN - University Of Missouri|
Submitted to: Proceedings of Great Plains Soil Fertility Conference
Publication Type: Proceedings
Publication Acceptance Date: 2/1/2022
Publication Date: 3/8/2022
Citation: Svedin, J., Ransom, C.J., Kitchen, N.R., Veum, K.S., Anderson, S. 2022. Can soil health metrics improve soil fertility recommendations in Missouri corn production?. Proceedings of the 2022 Great Plains Soil Fertility Conference, March 8-9, 2022, Denver, Colorado. p. 286-292. Available: https://greatplainssoilfertility.org/files/2022_GPSFC_Proceedings.pdf
Technical Abstract: It is speculated that integrating soil health (SH) with soil fertility (SF) testing would improve fertilizer recommendations. However, impacts of SH properties, specifically soil biological properties, on fertilizer demand are not quantified. The objective of this research was to explore corn (Zea mays L.) yield response to phosphorus (P) and potassium (K) fertilization as influenced by established SF analysis and common SH metrics. From 2018 to 2020, 532 fertilizer response plots (1592 ft^2) were implemented in 84 producer fields across central Missouri. Response plot treatments were 1) an unfertilized control, 2) 100 lbs/ac of K2O, and 3) 100 lbs/ac of P2O5. Each treatment received the same producer-specific nitrogen (N) rates, with an additional 40 lbs N/acre applied near V6 corn growth stage to prevent N deficiencies. Random forest analysis was used to model yield response to P and K fertilization and to investigate the influence of SH and SF analysis on model performance. Two-thirds of established monitoring sites were below established P and K soil-test critical concentrations—with 32% and 36% of the low fertility plots responding to P and K fertilizer application, respectively. The most consistent P and K yield improvements occurred in established “Very Low” and “Low” fertility ratings with yield improvement at 52% and 56% of the sites respectively. However, integrating SH and SF for predicting yield response was only minimally helpful, resulting in R^2 values of 15% and 7% for the P and K treatments, respectively. The low R^2 values are likely due to the variability in P and K availability and crop demand introduced by the diversity of cropping systems, management practices, and soils of the research sites. Assessment of variable importance in the models indicated that the established University of Missouri recommended SF tests best predicted grain yield responsiveness to P and K fertilization. The addition of SH metrics provided minimal additional predictive power. Although improved SH may offer multiple environmental or agronomic benefits, this study indicates that across central and northern Missouri soils, established physiochemical SF analysis remains the most effective tool to guide P and K fertilizer decisions in corn production.