Silvertop in perennial grass seed production: effects of type and timing of biotic stresses
Bibliographic record
Abstract
Seed production of perennial grasses is an important industry in Canada, but many fields exhibit high proportions of sterile heads with characteristic symptoms in a condition known as silvertop. In a 3-yr field study, biotic stress treatments were applied to caged plots of Kentucky bluegrass (Poa pratensis) and meadow bromegrass (Bromus riparius) to assess their effects on silvertop incidence. Treatments were (1) control, (2) addition of grass-feeding insects, primarily grass plant bugs (Miridae), (3) inoculation with Fusarium poae spores, (4) both insects and spores, and (5) mechanical piercing of seed heads above the last node (in a single year). Additionally, cores of the two grass species were potted and removed from the field in spring in each of 2 years. After 2, 4, and 6 wk intervals in a cold room at 4 °C to stagger plant development stage, the five treatments were applied to caged plants of both grasses, which were maintained in a greenhouse until seed harvest. In both studies, the numbers of healthy seed heads, percentage of heads with silvertop, and seed weights were determined. In the field, stress treatments infrequently and inconsistently affected silvertop levels. Regression showed that the relationship between silvertop and seed yield, although significant, explained little of the variability in yield. Silvertop developed in all treatments in the greenhouse; treatments had no effect on silvertop levels, which were highest in plants treated at the R1 (spikelets visible) growth stage. This suggests that this stage of the two grass species is most vulnerable to silvertop occurrence.
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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 | 0.000 |
| 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".