Utility of Phosphorus Enhancers and Strip-Tillage for Corn Production
Bibliographic record
Abstract
Farmers are seeking ways to diminish phosphorus (P) fertilizer rates and increase plant P uptake by means of enhanced efficiency P treatments. The objectives of this study were to determine the effects of tillage/fertilizer placement [no-till-surface broadcast (NT-BC) or strip-till-deep band (ST-DB)], monoammonium phosphate (MAP) rate (0, 56, and 112 kg ha-1), and the presence or absence of enhanced phosphorus efficiency products (Avail® and P2O5-Max®) on corn (Zea mays L.) production. The field study was conducted in 2010 and 2011 at Novelty and Albany, MO. The two P enhancers had no effect on plant population, silage dry weights, grain moisture, yield, grain protein, grain starch, plant nitrogen (N), potassium (K) uptake, or apparent P recovery efficiency (APRE) at either location (P>0.10). In the NT-BC and ST-DB treatments, the addition of Avail® or P2O5-Max® did not increase plant P uptake over the non-treated controls. ST-DB increased plant populations 3,500 to 15,500 plants ha-1 compared to NT-BC. At Novelty, yields increased 1.57 Mg ha-1 with use of ST-DB over NT-BC, but at Albany yields were affected by tillage/fertilizer placement and MAP rate. Corn grain yields with MAP at 0 kg ha-1 were 0.30 to 0.36 Mg ha-1 more than MAP at 56 or 112 kg P2O5 ha-1, which was probably due to the added ammonium nitrate used to balance the N contribution in MAP. Strip-till is a viable option to increase corn populations and yields on poorly drained soils, but P enhancers are not recommended for similar soil types.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".