Genetic diversity of<i>Verticillium dahliae</i>from olive trees in Tunisia based on RAMS and IGS-RFLP analyses
Bibliographic record
Abstract
Forty-two isolates of Verticillium dahliae were recovered from stem and root samples of olive trees showing symptoms of verticillium wilt in various olive-growing regions in Tunisia. Each isolate was identified based on microscopic observations of morphological and cultural characteristics, pathogenicity tests, as well as PCR amplification using Vd1/Vd2 primers. Genetic diversity among the isolates was investigated using random amplified microsatellites (RAMS) and PCR-RFLP of intergenic spacer region (IGS) of ribosomal DNA (rDNA). A single fragment of approximately 1.7–2.1 kb was amplified from all isolates by PCR using primers CNL12 and CNS1. Digestion of the amplified IGS region with restriction enzyme RsaI produced similar banding patterns (1200 and 800 bp) for 40 isolates while individual and distinctive banding patterns (1100, 850 and 150 bp) were observed for two isolates. Using RAMS primers, nine, eight and four bands were produced when using primers CGA (2200, 1400, 1200, 1100, 1000, 650, 550, 500 and 350 bp), CCA (2000, 1200, 950, 850, 800, 550, 500 and 400 bp) and GT (2500, 2400, 700 and 500), respectively. A total of 21 polymorphic markers were scored when data from the RAMS experiments were combined. Overall, the results of this study revealed associations between the genetic diversity of the isolates and their pathogenicity phenotype, but not between genetic diversity and the geographic origin, suggesting that they are randomly spread across Tunisia.
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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 | 0.000 | 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) | 0.000 | 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".