RESPONSE OF N2O TO NITROGEN MANAGEMENT AND BREEDING FOR SEED OIL IN BIODIESEL DEDICATED CANOLA
Bibliographic record
Abstract
While breeding for increased oil yield has generated new lines of spring canola (Brassica napus L.) for biodiesel production, emissions of N2O from fertilized canola fields threaten to undermine the climate change mitigation benefits of canola as a biodiesel alternative to conventional diesel. This study determined the response of N2O emissions to canola line and N treatment in a maritime setting (Truro, Nova Scotia). Tissue N uptake was measured to determine whether differences in N uptake between the lines could explain any observed effect of canola line. Nitrate Exposure (the summation of daily soil NO3- concentrations over a growing season, serving as an integrated measure of the exposure of soil biomass to nitrate over the growing season) was determined to investigate its potential as a predictor of N2O emissions. Four spring canola lines (‘Topaz’, ‘Sentry’, ‘Polo’, and 04C204, in order of increasing seed oil content) were paired with five N treatments (40, 60, 80, 100, and 120 kg N ha-1) in an incomplete two-factor factorial design over two growing seasons (2008 and 2009). N2O emissions were determined using a non-steady state vented chamber method. N2O emissions peaks closely followed increases in soil water content in both years, indicating that limited aerobicity was the trigger for N2O emissions events, and suggesting that denitrification was the predominant microbial process responsible for N2O emissions. The magnitude of average N2O emissions both years was considerably low when compared to other studies (0.55 and 0.56 kg N2O ha-1 in 2008 and 2009 respectively). Increasing N treatment resulted in significantly increased N2O emissions in 2008. Though the same trend was observed in 2009, it was not found to be significant. Differences in weed cover, soil C, soil N supplying capacity, and elevation between the sites may have contributed to the inability to detect an N2O emissions response to N treatment in 2009. Canola line had no effect on N2O emissions in either study year, though heavy competition by weeds significantly affected canola plant health and survival in 2009. Tissue N uptake increased with increasing N treatment, but did not change with choice of line, which is consistent with the observation of no N2O emissions response to line. Nitrate Exposure was found to be strongly correlated with N2O emissions in a linear relationship, supporting the conclusion that Nitrate Exposure can be a promising indicator of N2O emissions when they are limited by soil N. Finally, FluxPerOil, the ratio of N2O emissions per unit oil yield (kg N2O kg-1 oil) was found to decrease with decreased N treatment in 2008, though only very little, indicating a marginal abatement of N2O emissions at a significant cost of oil. FluxPerOil was unreliable in 2009 due to weeds compromising the line effect and therefore oil yield.
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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 | 0.001 |
| 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".