Pushing canola instead of windrowing can be a viable alternative
Bibliographic record
Abstract
Compared with direct harvesting, windrowing canola (Brassica napus L.) crop reduces maturation time and seed losses caused by shattering; however, windrows are prone to wind damage. While direct harvesting canola may reduce costs and lower green seed content, new technologies are required to effectively reduce shattering losses. Pushing is a potential replacement for swathing where pod movement is restricted by mechanically lodging the crop and letting the crop mature while still attached to the root system. This system purports to limit shattering and improve seed quality. Trials were conducted over a 3-yr period in western Canada to determine the impact of pushing canola relative to windrowing. Field-scale trials showed that yield and oil content typically did not differ between canola pushed and windrowed on the same date. In plot trials conducted at Brandon and Indian Head, crop yields were not decreased nor were green seed numbers increased by early pushing. It was observed that pushing worked best when crop stand and growth were good as well as when canola was pushed at or before 30-40% of the seeds have changed color and therefore are physiologically mature. While further work is required to identify the earliest time at which a crop can be pushed without a negative impact on yield or quality, the current trials indicate that with canola, pushing could occur at the start of seed color change without any negative impacts on grain yield and oil quality. Key words: Canola, windrowing, pushing, harvest, yield, seed size, Brassica napus L.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".