Pronitridine and Nitrapyrin With Anhydrous Ammonia for Corn
Bibliographic record
Abstract
Nitrogen (N) losses due to leaching, denitrification and/or ammonia volatilization are of utmost concerns since they reduce farm profitability and adversely affect environmental quality. To combat these N losses, a new nitrification inhibitor (NI), pronitridine, can be used to slow down the nitrification process. A two-year (2014, 2015) field experiment was conducted to evaluate the effectiveness of pronitridine at different rates (9.4, 18.7, and 28.1 L ha-1) with anhydrous ammonia (AA) at 112 kg N ha-1 when applied in the fall or pre-plant on claypan soils in northeast Missouri. Using pronitridine at 9.4 L ha-1 with AA in the fall during a low yielding year (2015) increased corn grain yield 7% compared to AA + nitrapyrin (2.3 L ha-1). Agronomic efficiency and yields were greatest with pronitridine at 9.4 L ha-1 than AA + nitrapyrin. Grain N removal was highest for AA + pronitridine at 18.7 L ha-1 compared to AA + nitrapyrin. Pre-plant application of AA + pronitridine at 9.4 L ha-1 increased grain starch content compared to AA without NI, but it was not significantly different from AA + nitrapyrin. Results indicated that pronitridine was effective in increasing yields when applied in the fall and was similar to other NI’s when applied pre-plant in the spring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".