Effect of time and rate of nitrogen, sulfur and boron application on canola growth in southwestern Québec
Bibliographic record
Abstract
Canola (Brassica napusL.) seeds have a high oil content (> 40 %), the lowest saturated fat concentration (6.8%) among the vegetable oils, plus low erucic acid and glucosinolate levels, making this crop highly valuable in the oilseed industry. Québec, a province where little canola is currently produced, has considerable potential to expand canola cultivation and, in doing so, strengthen the provincial agricultural sector. However, at this time there are no well-founded fertility recommendations for canola production in southwestern Québec; there is a lack of sufficient data on canola responses to nitrogen (N), sulfur (S) and boron (B). Therefore, field studies were conducted in 2011 and 2012 to determine the optimum rate and timing of N fertilizer additions, and also the best rates of S and B application under southwestern Québec conditions. In 2011, factorial combinations of four levels of N [0, 50, 100 (or 50 + 50) and 150 (or 50 + 100) kg ha-1], two levels of S (0 and 20 kg ha-1), and three levels of B (0, 0.5 foliar spray at 20% flowering stage, and 2 kg ha-1 soil applied before sowing) were tested. Single doses of N fertilization (50, 100, 150 kg ha-1) were all applied before sowing. Split N fertilization was also evaluated at two levels: 100 kg ha-1 (50 + 50 kg ha-1) and 150 kg ha-1 (50 + 100 kg ha-1), where the first dose of 50 kg N ha-1 was applied before sowing, and the remainder was side-dressed at the 3-4 leaf stage. In 2012, two additional treatments were added, one applied as 20 kg S ha-1, 0.5 kg B ha-1 and 200 kg N ha-1, and the other as 20 kg S ha-1, 0.5 kg B ha-1 and 50 + 150 kg N ha-1. In 2011, N fertilization had positive effects on dry biomass, leaf area, plant height, seeds silique-1, harvest index, yield, and seed protein content, but a negative effect on seed oil content. The optimum N rate was 150 kg N ha-1, resulting in the highest seed yield and good seed quality. In 2012, canola did not respond as strongly to fertilizer additions as in 2011, apparently because of lower established plant densities. Application of fertilizer N affected fewer variables in 2012: 1000-seed weight, and harvest index, seed oil content and seed protein content. Of the four blocks in the 2012 experiment, only block four had a reasonably high average plant population density. For block four, the yield data was curvilinearly and positively correlated with N rate (R² = 0.5702, P < 0.0001), with peak yield occurring at 150 kg N ha-1. Canola growth was often not affected by the time of N application. In 2011, there was a S x B interaction for 1000-seed weight, in that the effect was positive with foliar application of 0.5 B kg ha -1 and negative when 2 kg B ha-1 was soil-applied). Boron alone increased 1000-seed weight in 2012. Our results indicated that S and B levels in the soils used were probably sufficient for canola production. Plant height was decreased (2.9 %) by S application at 20 kg ha-1 in 2011. In conclusion, our data suggest that the best N application regime for canola production in southwestern Québec may be a single application at 150 kg N ha-1; this produced the highest seed yield without sacrifice of seed quality. Sulfur and B additions may not be required for canola production in southwestern Québec.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".