EFFECTIVENESS OF BANDING VERSUS BROADCASTING OF ESTABLISHMENT-TIME AND ANNUAL PHOSPHORUS APPLICATIONS ON YIELD, PROTEIN, AND PHOSPHORUS UPTAKE OF BROMEGRASS
Bibliographic record
Abstract
A field experiment was conducted from 1993 to 1995 on a phosphorus (P)-deficient Black Chernozemic (Typic Boroll) soil near Ponoka, Alberta, Canada to compare the effectiveness of broadcasting (spread on the soil surface) versus banding (1.5 cm wide band placed 5 cm deep and 15 cm apart, using a coulter-type disc drill) of P fertilizer applied annually (10, 20, 30, and 40 kg P ha−1) or at time of forage establishment (50, 100, 150, and 200 kg P ha−1) on dry matter yield (DMY), protein yield (PY) and P uptake (PU) of bromegrass (Bromus inermis Leyss) managed as hay. Fertilizer P markedly increased DMY, PY, and PU in all the three years. Annual broadcasting of P fertilizer produced greater increase in DMY, PY, and PU than banding (by 921 kg DMY ha−1, 71 kg PY ha−1, and 1.51 kg PU ha−1). On the contrary, banding P fertilizer at establishment produced higher increases in DMY, PY, and PU than broadcasting (by 3136 kg DMY ha−1, 331 kg PY ha−1, and 7.42 kg PU ha−1). The differences in DMY, PY, and PU between banding and broadcasting were not influenced by P rate. The increase in DMY, PY, and PU tended to increase with P rate, except for the establishment-time broadcasting treatments. Broadcast P fertilizer was much more effective with annual than establishment time application, whereas banded P fertilizer was almost equally effective with establishment-time and annual applications. Overall, annual broadcasting was most effective, establishment-time broadcasting was least effective and effectiveness of annual or establishment-time banding was intermediate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".