Growth, pathogenicity and infection behaviour, and genetic diversity of <i>Rhexocercosporidium panicis</i> isolates from ginseng roots in British Columbia
Bibliographic record
Abstract
Ginseng roots with reddish-brown to black surface discolourations were collected from eight farms in British Columbia during 2005–2007. Affected tissues predominantly yielded colonies of Fusarium spp. and Rhexocercosporidium panacis when plated onto half-strength PDA. Percentage recovery of these fungi was influenced by root age, with Fusarium species recovered mostly from 1–2-year-old roots and R. panacis from 3- and 4-year-old roots. Roots sampled in July 2007 yielded a higher frequency of Fusarium while those sampled during March and September 2007 yielded a higher frequency of R. panacis. Isolates of R. panacis ranged in pathogenicity from non-pathogenic (29% of total) to weakly aggressive (causing lesions only in the presence of wounds) (54%) to highly aggressive (17%), and infected both ginseng and carrot roots, causing a surface blackening. The optimal temperature range for growth of 10 isolates of R. panacis in culture was 15–20 °C. A nested PCR protocol confirmed the presence of R. panacis in symptomatic ginseng roots as well as in about 20% of non-symptomatic roots. The fungus was also detected by nested PCR in flowers, green and red berries, and non-stratified and stratified seeds. Field applications of propiconazole reduced the frequency of detection by PCR of R. panacis from ginseng berries. Phylogenetic analysis confirmed that most of the isolates recovered in this study were R. panacis, although a few isolates clustered in a separate group.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".