Effect of post-harvest management on seed production of creeping red fescue, tall fescue, and Kentucky bluegrass in the Peace River region of north-western Canada
Bibliographic record
Abstract
A field study in the Peace River region of northwestern Canada evaluated five post-harvest management (PHM) treatments on the seed yield and quality of four grasses, viz. Boreal creeping red fescue (Festuca rubra L. var. rubra), Safari and Tomahawk tall fescue (F. arundinacea Schreber), and Midnight Kentucky bluegrass (Poa pratensis L.). The PHM treatments were: straw removal after seed harvest plus trimming prior to winter; a single propane burn; a double propane burn; power cultivation; and diuron applied in spring. The study was conducted for 3 consecutive harvest years. The grass × harvest year × PHM interaction was not statistically significant (P ≤ 0.05) for any of 10 characteristics, viz. panicle density, time of seed maturity, seed yield (per unit land area and per individual panicle), whole-plant yield, harvest index, seed dockage, 1000-seed weight, specific seed weight, and germination capacity. The grass × harvest year interaction was statistically significant (P ≤ 0.05) for each of the 10 characteristics, primarily because of the differential response of the bluegrass as compared to the fescue grasses. The grass × PHM interaction was statistically significant (P ≤ 0.05) for seed yield of individual panicles, harvest index, seed dockage and 1000-seed weight. The PHM × harvest year interaction was statistically significant (P ≤ 0.05) for specific seed weight only. The main effect of PHM was statistically significant (P ≤ 0.05) for specific seed weight and germination capacity only. The average annual seed yield of the two tall fescue cultivars (1002 and 1171 kg ha–1 for Safari and Tomahawk) was approximately twice that of Boreal creeping red fescue (554 kg ha–1) and four times that of Midnight Kentucky bluegrass (284 kg ha–1). At this northerly latitude (55°N), the effects of any PHM treatment on the seed productivity of these grasses may be limited by the short period of environmental conditions between seed harvest and the onset of winter that are conducive to vegetative and reproductive tiller development. Key words: Post-harvest management, propane burning, mechanical and chemical rejuvenation, grass seed yield, grass seed quality
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".