Inoculum prevalence, host infection and biological control of <i>Colletotrichum acutatum</i> : causal agent of blueberry anthracnose in British Columbia
Bibliographic record
Abstract
To identify the causal organism of anthracnose (ripe‐rot), which reduces yield and postharvest quality of blueberries grown in British Columbia, Canada, 80 isolates were recovered from diseased fruits collected from commercial blueberry fields during 2002–04 and identified as Colletotrichum acutatum using colony morphology, growth rate and species‐specific PCR primers. In vitro incubation of replicated sets of inoculated detached berries at various temperatures produced infection at temperatures of 7–30°C, with an optimum at 20°C. Colletotrichum acutatum could not survive on the soil surface as mummified berries but the pathogen was detected mostly within flower buds and less so in blueberry twigs and fruit trusses. Infection of developing flower buds in May–June of the preceding growing season gave the highest inoculum recovery in the following year. Two commercial fungal biocontrol agents, Prestop ( Gliocladium catenulatum ) and PlantShield ( Trichoderma harzianum ), each reduced anthracnose development in 2003 and 2004 by up to 45% when sprayed three times onto plants between flowering and fruit ripening.
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 | 0.001 | 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".