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Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure
P. M. Kyveryga, T. M. Blackmer
Iowa Soybean Association

Nitrification inhibitors (NI) can be used with animal manure to decrease N losses and increase corn (Zea mays L.) yields. However, data are limited specifying when and where applications of NI can be profitable. The objective was to identify site-specific conditions for using Instinct (an encapsulated form of nitrapyrin) with fall-injected liquid swine manure (LSM). Eleven on-farm trials with Instinct added to LSM were conducted in 2009 and 15 trials in 2010. The manure was applied at optimal manure rates in at least three field-long strips with and without NI. The corn stalk nitrate test (CSNT) and digital aerial imagery of the corn canopy were used to assess the late-season corn N status. Yield responses (YR) to NI were calculated by dividing fields into 50-m long cells, and hierarchical models were used to estimate the probability of economic YR at different field-level factors (rainfall and total N rate) and within-field level factors (soil organic matter and drainage). On average, NI produced no YR in relatively normal 2009 and a 0.15 Mg ha-1 YR in extremely wet 2010. In both treatments, NI did not increase N uptake and ammonia concentrations in the soil, but CSNT showed that about half of samples were deficient in 2009 and about 65% in 2010. In 2010, fields receiving >90 cm of rainfall from March through August were about 65% more likely to have economic YR (> 0.12 Mg ha-1) than fields receiving <90 cm rainfall. In both years, within-field variability in YR was about four times greater than among-field variability, but within field-level factors had no significant effects. These studies suggest that the NI effects may have not lasted long enough to produce economic YR across all fields and its applications may be limited to fields that most likely receive above normal spring and summer rainfalls.

Keyword: nitrification inhibitor, liquid swine manure, late-season digital aerial imagery, the late-season corn stalk nitrate test, and hierarchical statistical models.