Evaluation of nitrogen use efficiency and contributions of soil- and fertilizer-derived nitrogen uptake in a diverse set of canola lines
Bibliographic record
Abstract
Canola is a major field crop in Western Canada, requiring substantial nitrogen (N) fertilization for optimal yields. However, high application rates of fertilizer N to agricultural soils can lead to environmental N losses and represent wasted inputs and costs. Improvement of canola N use efficiency (NUE) can reduce N inputs while satisfying crop N demand minimizing costly N losses. This thesis evaluated a range of commonly used NUE metrics in a diverse set of canola lines. Additionally, 15N isotope tracing in microplots was used to understand fertilizer and soil N contributions to plant N uptake and yield. This research intended to identify specific lines with superior NUE traits that could support the development of canola varieties with improved NUE. Plant samples collected throughout the growing season provided insight into understanding plant N partitioning and final recovery of fertilizer- and soil-derived N. All site-years, yields and measured NUE indices varied between canola lines. Variation between canola lines for recovery efficiency of fertilizer (15NRE) added at a rate of 100 kg N ha-1 was observed at Saskatoon-2022 and Saskatoon-2023 at harvest maturity. Few and inconsistent differences between canola lines were found for total N derived from fertilizer (TNdfF) and total N derived from the soil (TNdfS) at the Saskatoon sites. However, no significant patterns amongst canola lines could be discerned, limiting attribution to a specific line. Despite low levels of residual inorganic soil N and adequate N fertilization, soil N was the primary contributor to canola N uptake contributing 30 – 79% of total N in the mature plant. 15N-labelled fertilizer was a small proportion of total plant N, yet post-harvest soil samples revealed a large portion of unaccounted 15N fertilizer averaging 61 kg N ha-1 at Outlook-2022, 54 kg N ha-1 at Saskatoon-2022, and 51 kg N ha-1 at Saskatoon-2023. Our findings showed inefficient use of fertilizer N by all canola lines and the substantial contributions of soil N to plant N.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".