Soil biological and physical measurements did not improve the predictability of corn response to phosphorus fertilization.

Including soil health and physical measurements with traditional soil fertility measurements has the potential to improve corn (Zea mays L.) P fertilizer recommendations. The objectives for this study were to (1) evaluate the accuracy of current South Dakota corn P recommendations in predicting yield increases and (2) determine if the predictability of yield response to P fertilization improves by including selected soil biological, physical, and chemical measurements. This project was conducted in central and eastern South Dakota from 2019 to 2022 at 117 experimental sites that varied in management, landform, and soil type. A treatment of 48.9 kg P2O5‐P ha−1 was compared to a control with no P fertilizer. Soil samples (0–15 cm) collected before fertilization were analyzed for selected soil physical, chemical, and biological parameters. Analysis suggested that the current critical P value of 16 mg Olsen‐P kg−1 was still accurate as it was still within the 68% confidence interval for the linear (12–19 mg kg−1) and quadratic plateau (16–26 mg kg−1) models. Using the critical value of 16 mg Olsen‐P kg−1, we correctly predicted P responsiveness 70% of the time. The accuracy of predicting P responsiveness was not further improved by considering selected enzymes, permanganate oxidizable C, soil respiration, total C, or total N, but was improved by considering pH, soil organic matter, and apparent cation exchange capacity. Therefore, the use of typical soil fertility measurements without soil physical and biological measurements is currently the best option for predicting the responsiveness of corn to P fertilization in South Dakota. Core Ideas: South Dakota's corn Olsen soil test phosphorus (STP) critical value should remain at 16 mg kg−1.Below 16 mg kg−1 STP, corn yields increased 10% at 78% of the sites with P application.P response predictions were not improved by considering biological and physical indicators.Using STP in making P response predictions in South Dakota remains the best method. [ABSTRACT FROM AUTHOR]