Corn Production as Affected by Phosphorus Enhancers, Phosphorus Source and Lime
Bibliographic record
Abstract
Prompted by high cost of fertilizer, farmers are investigating ways to enhance the efficiency of phosphorus (P) fertilizers. This study examined the effects of liming application (0 Mg ha-1 and recommended rate), P source [non-treated control and a broadcast application of diammonium phosphate (DAP) or triple superphosphate (TSP)], and the presence or absence of two commercial enhanced efficiency P products (Avail? and P2O5-Max?) on corn (Zea mays L.) production. The study was conducted at Novelty in northeastern Missouri and Portageville in southeastern Missouri. The P enhancers did not affect plant population, silage dry weights, grain moisture, yield, protein, oil, or starch concentrations at either location. At Portageville, P enhancers did not affect plant N, P, K uptake and apparent P recovery efficiency (APRE). At Novelty, neither P enhancer paired with DAP increased P uptake over the non-treated control. TSP treated with Avail? increased P uptake 8.6 kg ha-1 compared to the non-treated control and 7.1 kg ha-1 compared to P2O5-Max?. In 2010 at Novelty, TSP treated with Avail? increased K uptake 150 kg ha-1 compared to the non-treated TSP and 100 kg ha-1 compared to P2O5-Max?. At Novelty, plant population was 4,800 plants ha-1 greater in the non-limed control compared to the recommended rate in 2011, although plant population at Portageville was not affected. At Portageville, the recommended amount of lime increased grain yields 0.77 Mg ha-1, but there was no effect at Novelty. At Novelty, plant P uptake increased 3.4 kg ha-1with the application of lime, but at Portageville there was no effect. Grain yield increased 0.34 Mg ha-1 with TSP compared to the non-treated control.
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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 | 0.001 | 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".