Placement, rate and source of N, seedrow opener and seeding depth effects on canola production
Bibliographic record
Abstract
Seedrow-placement of N fertilizer can save money and time, but it can cause reduced emergence and yield. From 1998 to 2000, a field experiment was conducted on a silty clay loam (Black Chernozem) soil at Melfort, Saskatchewan. The objectives were to determine the influence of placement, rate and source of N, seedrow opener and seeding depth on the emergence, yield, N uptake, and seed protein and oil content of canola (Brassica napus L. ‘Quest’). The treatments were optimum (1.5 cm) and deep (4.5 cm) seeding depths in two main plots with 17 subplots of different combinations of N sources [urea and ammonium nitrate (AN)], rates (0, 40, 80 and 120 kg N ha -1 ) and placements (sideband and seedrow) using two seedrow openers (knives – 2 cm spread, and shovels – 20 cm spread). Sidebanding of 40, 80 and 120 kg N ha -1 and seedrow placement of 40 kg N ha -1 increased yield, N uptake and seed protein content, had no detrimental effect on emergence, and reduced seed oil content. Compared to sidebanding, seedrow placement of 80 and 120 kg N ha -1 generally reduced emergence, yield and N uptake, with relatively severe effect at higher N rate, but had no effect on seed protein and oil content. The yield and N uptake of canola responded up to 120 kg N ha -1 with sidebanding compared to 40 kg N ha -1 for yield and 80 kg N ha -1 for N uptake with seedrow placement. Deep seeding reduced emergence, yield and N uptake in many cases, had no effect on seed protein content and reduced oil content in some treatments. At low rates of N, emergence was generally better with knives, while shovels tended to be superior at higher rates of seedrow-placed N. In general, the negative impact of seedrow placement compared to sideband placement of N was more severe with deeper seeding, higher N rate and narrower width of seedrow placement band. In summary, the findings indicated that practices that placed seed and fertilizer in a way that maximized canola emergence and minimized seedling damage from fertilizer, consistently optimized seed yield response to N fertilizer. Key words: Canola, N placement, N rate, N source, seeding depth, seedrow opener
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".