HPLC analyses of cultures of <i>Phoma</i> spp.: Differentiation among groups and species through secondary metabolite profiles
Bibliographic record
Abstract
The metabolite profiles of 26 isolates of the blackleg fungus (Leptosphaeria maculans (Desm.) Ces. et de Not., asexual stage Phoma lingam (Tode ex Fr.) Desm.), obtained from diverse parts of the world (part of the International Blackleg Crucifer Network collection), were studied utilizing specific culture conditions, HPLC analysis, and a set of chemical markers. This fungus is the causative agent of blackleg disease of brassica oilseeds; a virulent strain of the pathogen has caused significant rapeseed (Brassica napus L., and B. rapa L.) and canola (B. napus L., and B. rapa L.) losses in Canada, and is also considered a serious agricultural problem worldwide. Effective surveys of blackleg epidemics require simple and reliable analytical methodology to differentiate among the diverse groups of isolates. The chemical analysis of phytotoxins and related secondary metabolites is perhaps one of the most discriminating and the least ambiguous methods for differentiation of Phoma blackleg isolates. Following HPLC analyses, the 26 isolates could be placed in three main groups, irrespective of country of origin: isolates producing phomamide and sirodesmins, isolates producing indolyl dioxopiperazines, and isolates producing polyketides. Discussion of the implications of our findings and suggestions for species reclassification are provided.
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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 | 0.000 |
| 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".