Corn response to strip‐tillage and phosphorus fertilization in the Northern Great Plains
Bibliographic record
Abstract
Abstract Strip‐tillage is an emerging conservation tillage/residue management system for corn production in the Northern Great Plains. Producers in Manitoba are becoming more interested in strip‐tillage as it may provide many of the soil conservation benefits of no‐tillage production without potential limitations of cold soils in the spring common to this region. A 2‐year study evaluated corn (Zea mays L.) response to phosphorus (P) fertilization in strip‐tillage and conventional tillage systems. Fertilization treatments included a control (no P), two rates of P (30 and 60 kg P2O5 ha−1), applied as monoammonium phosphate (11–52–0) either in the fall with a strip‐tillage unit (as a deep‐band, 10–13 cm deep) or in the spring with a corn planter (as a side‐band, 5 cm beside and 2.5 cm below the seed). Spring side‐banded P treatments increased early‐season biomass at 2 of 4 site‐years by up to 103% compared to the unfertilized controls. At the same 2 site‐years, banded P treatments reduced days to silking by 2–3 days, compared to the unfertilized controls. Across all site‐years, spring side‐banded P treatments increased grain yield by an average of 467 kg ha−1 and decreased grain moisture content by 9 g kg−1 compared to the unfertilized control. Overall, side‐banded P at planting was agronomically superior to precision fall deep‐banding. There was also no agronomic penalty for corn grown with strip‐tillage, compared to conventional tillage, suggesting that strip‐tillage is an agronomically promising practice for corn production in southern Manitoba.
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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".