Genetic structure of <i>Verticillium dahliae</i> isolates infecting olive trees in Tunisia using <scp>AFLP</scp> , pathogenicity and <scp>PCR</scp> markers
Bibliographic record
Abstract
Since 2006, verticillium wilt of olive induced by Verticillium dahliae has caused considerable economic losses in olive orchards in Tunisia. The genetic structure of V. dahliae isolates collected from different olive growing regions was investigated using virulence tests, vegetative compatibility grouping ( VCG ) and amplified fragment length polymorphism ( AFLP ) analyses. In total, 42 isolates of V. dahliae from diseased olive trees were tested. Cluster analysis and principal coordinate analysis revealed that geographic origin was the main factor determining the genetic structure of V. dahliae populations and both methods indicated a genetic separation between the central and coastal isolates. Isolates were divided into two major groups: the AFLP ‐I group included all isolates from Sidi Bouzid, Kairouan, Kasserine and Sfax (centre of the country) and the AFLP ‐ II group included isolates from Monastir, Zaghouane, Sousse, Mahdia (coastal region), and two isolates from Sfax. Analysis of the molecular variance ( amova ) indicated a significant level of genetic differentiation among (76%) and within (23%) the two populations. Analyses of both the defoliating (D) and non‐defoliating ( ND ) pathotypes and VCG markers indicated that most of the isolates belong to VCG 2A and 4B/ ND pathotype. The disease severity was highly variable among the isolates tested ( P < 0·05) with no evidence of association between aggressiveness and geographical origin of the isolates. Overall, results of this study revealed a clear association between the genetic diversity of the isolates and their geographic origin, but not between genetic diversity and virulence patterns.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".