Determination of <i>Festuca filiformis</i> seedbank characteristics, seedling emergence and herbicide susceptibility to aid management in lowbush blueberry (<i>Vaccinium angustifolium</i>)
Bibliographic record
Abstract
Summary Festuca filiformis is a common perennial grass in lowbush blueberry fields, but little is known about the general biology, seedbank characteristics, seedling recruitment or susceptibility of seedlings to currently registered herbicides. The objectives of this research were to determine (i) the presence of F. filiformis seedbanks in lowbush blueberry fields, (ii) whether F. filiformis seedbanks accumulate near the soil surface in lowbush blueberry fields, (iii) the dormancy status of fresh F. filiformis seeds, (iv) the temporal patterns of seedling recruitment in established F. filiformis populations, (v) whether F. filiformis has a vernalisation requirement for flowering in lowbush blueberry and (vi) susceptibility of F. filiformis seedlings to various herbicides currently registered in lowbush blueberry. Festuca filiformis formed a seedbank in lowbush blueberry fields, with an average of 1660 ± 272–5680 ± 1409 seedlings m−2 emerging from soil cores collected from two infested fields. Most seeds were located at the soil surface, providing opportunities for seedbank management through predation or burning. Fresh seeds lacked dormancy and readily germinated, although germination was reduced by dark conditions. New seedlings emerged in spring and autumn and required vernalisation to flower. Seedlings were susceptible to several currently registered herbicides in lowbush blueberry, although mortality rates were highest in plants treated with glufosinate, flumioxazin, glufosinate + flumioxazin and terbacil. Growers should avoid movement of seeds on machinery, and additional research should be conducted to determine the effects of registered herbicides on F. filiformis seedling recruitment under field conditions in lowbush blueberry.
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 | 0.000 | 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".