Graduate Exit Seminar - Peter Renz

Plan to join Peter Renz's graduate exit seminar on May 21, 2024, at 8:30 am in Kottman Hall 333C or via Zoom. Peter will present, "Development of a Novel Biochemical Soil Health Indicator that is based on a Multivariate Soybean Yield Prediction Model."

Abstract: Soil Health (SH) indicators that can reliably quantify the effects of agricultural management systems are essential for the implementation of sustainable practices in the agricultural sector. If such an SH indicator(s) could be coupled with agronomic productivity it would allow us to provide recommendations to farmers and identify problems much sooner. Unfortunately, recent publications showed that the existing SH tests were limited in their ability to distinguish between agricultural management systems and that they poorly correlated with crop yield. And this is where this dissertation examined the ability of microbial indicators, enzyme assays, and other soil properties to predict soybean yield outcomes. During this process we were able to determine a multivariate soybean prediction model with an R2 value of 0.84. Additionally, the information from the model allowed us to compute a novel biochemical Soil Health Indicator. To our surprise this indicator was significantly more reliable to differentiate between treatment effects on four long-term experimental sites compared to most other soil properties. A separate analysis that involved soil samples that were collected at Ohio farm fields further cement its potential as a possible SH indicator. But it also showed that soil type and climate conditions will need to be considered.

Advisor: Dr. Richard Dick