Response to side-banded phosphorus and zinc fertilizer for corn grown after canola or soybean in southern Manitoba
Bibliographic record
Abstract
A 2-year crop rotation study in southern Manitoba assessed the effects of starter fertilizer on grain corn ( Zea mays L.) production when corn followed canola ( Brassica napus L.) versus soybean ( Glycine max L. Merr.). Treatments included a control (no starter) and two rates of phosphorus (P) (30 and 60 kg P2O5 ha−1) as monoammonium phosphate (MAP, 11–52–0) or MicroEssentials® SZ (MESZn, 12–40–0–10–1) side-banded at planting. The preceding crop did not have any influence on mycorrhizal colonization of corn roots at the V4 corn growth stage. However, side-banded fertilizer increased early-season biomass by as much as 111% compared to the unfertilized control, averaged across all site-years, with the largest increases occurring where corn followed canola. P concentration and uptake in early-season biomass increased as the P rate increased. Zinc (Zn) concentrations in early-season biomass were the greatest for the unfertilized control and MESZn treatments, while Zn uptake was significantly greater with the application of starter fertilizer compared to the unfertilized control. Starter P advanced silking date by 2–7 days relative to the unfertilized control. At maturity, starter P reduced grain moisture by 21–27 g kg−1 in corn only after canola. The high rate of MAP increased grain yield by an average of 770 kg ha−1 compared to the unfertilized control, regardless of the preceding crop. The negative influence of the preceding canola crop on early-season growth and mid-season development of corn can be managed with starter fertilization to provide adequate P and Zn to the corn crop and maintain successful production in 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 | 0.001 | 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".