The Profitability of Seeding the F<sub>2</sub> Generation of Hybrid Canola
Bibliographic record
Abstract
The high cost of hybrid (HY) canola (Brassica napus L.) seed has some producers considering F2 generation hybrid farm‐saved seed (HY‐FSS), or open‐pollinated (OP) varieties (both certified and farm‐saved seed). The net return (NR) of different varieties, genetic backgrounds, seeding rates, seed treatments, and seed sizing was evaluated from three experiments over eight site‐years of field data from western Canada. One set of experiments included variety, genetic background and seeding rate, while another included seed treatment, genetic background and seed sizing. The experiments used randomized complete block designs. The NR accounted for yield, green seed price discount, seed costs, and other production costs. Analysis of variance indicated certified F1 hybrid seed (HYC) was more profitable than HY‐FSS (15%, P = 0.0057) and OP (22%, P = 0.0001). With delayed weed control, NR was lower for HYC and not statistically different than HY‐FSS. Higher seeding rates and seed sizing for HY‐FSS did not increase NR compared to HYC. The findings of this study support the use of HYC canola seed, especially at high canola prices. Canola producers will not increase their NR by using HY‐FSS or OP seed to reduce their seed cost because the lost value of production exceeds the higher cost of HYC seed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".