Pathogenicity and Vegetative Compatibility of <i>Verticillium dahliae</i> Kleb. Isolates from Olive in Morocco
Bibliographic record
Abstract
Abstract Thirty‐eight strains of Verticillium dahliae Kleb. from diseased olive stems originating from the most important regions of olive in Morocco, were tested by vegetative compatibility analysis to investigate their genetic diversity. Two media, water agar chlorate (WAC) and minimal medium chlorate (MMC) were used to induce the nit‐mutants. The WAC medium generated a higher frequency of nit‐mutants than MMC medium. Based on complementarity of nit‐mutants, 47% of isolates were assigned to VCG4B, 32% in VCG2 (A or B) and the 18% remaining isolates could not be grouped to any VCGs tested. These latter belonged to southern regions. Pathogenicity and aggressivity of twelve isolates from this population were assessed on four plant species which are frequently intercropped with olives. These were tomato, eggplant, cotton and pepper. All isolates were pathogenic and highly aggressive on cotton and eggplant. On cotton, the isolates from southern regions induced more severe symptoms than those from northern regions. Weak to moderate symptoms were induced by all isolates on tomato and they differed in aggressivity. No isolate was pathogenic on pepper, while four isolates from northern regions were recovered from basal stems of inoculated plants. The cor‐ relation between VCGs and pathogenicity on the intercropped species is discussed with regard to the regional distribution of V. dahliae population from olive.
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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) | 0.000 | 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".