Investigation of Potential Seed Dormancy Mechanisms in American Burnweed (<i>Erechtites hieraciifolius</i>) Seeds from Wild Blueberry (<i>Vaccinium angustifolium</i>) fields
Bibliographic record
Abstract
American burnweed is an increasingly common annual weed in wild blueberry fields in Atlantic Canada and Maine. Knowledge of seed dormancy characteristics and potential for this species to form persistent seedbanks in wild blueberry soils, however, is lacking. A series of experiments were therefore conducted to investigate potential mechanisms regulating American burnweed seed dormancy in wild blueberry fields. Seeds were dormant at maturity and did not germinate in dark or light under warm conditions. Cold moist stratification (CMS) at 4 C for 90 d followed by exposure to warm conditions (22/15 C day/night) and light caused >90% germination, and germination was generally maximized following 80 d CMS. Exogenous potassium nitrate applied as a 5% solution did not stimulate germination, but nearly all seeds (>95%) germinated following treatment with 200, 400, 600, or 800 ppm (w/v) gibberellic acid (GA3) solution. Physical removal of the seed coat or seed exposure to short durations of dry heat did not increase germination. Seed exposure to 1 s of direct flame increased germination, but germination was low relative to germination following CMS and treatment with GA3. Based on these results, we conclude that American burnweed seeds in wild blueberry fields exhibit non–deep physiological dormancy that is most readily broken by CMS and light or seed treatment with GA3. Seeds will likely be exposed to favorable conditions for breaking dormancy (cold temperatures and light) in wild blueberry fields due to lack of tillage and seed burial, indicating high potential for this weed species to proliferate in wild blueberry fields if not properly managed.
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".