Histological and anatomical responses in avocado, <i>Persea americana</i>, induced by the vascular wilt pathogen, <i>Raffaelea lauricola</i>
Bibliographic record
Abstract
Raffaelea lauricola causes laurel wilt of avocado, Persea americana. Host × pathogen interactions were examined with light and scanning electron microscopy. The susceptible avocado cultivar ‘Simmonds’ was inoculated and examined 5 cm above the inoculation site 3, 7, 14, 21, and 42 days after inoculation (dai). No external symptoms were observed at 3 and 7 dai, and there were no anatomical differences when compared with the mock-inoculated plants. By 14 dai, external symptoms were present and dark discoloration had developed in sapwood. Tylose development increased significantly by 14 dai, and was positivity correlated with disease severity (P < 0.05). By 14 dai, gels formed in xylem vessels, fibers, and adjacent parenchyma cells; they were associated with xylem blockage and composed of phenols, pectin, and lipids, as suggested by, respectively, toluidine blue O, ruthenium red, and Sudan III stains. With a chitin-specific stain, fluorescein-conjugated wheat germ agglutinin, infrequent mycelia, and conidia of R. lauricola were visualized within xylem lumena and fibers, regardless of sample date. Understanding how avocado responds to the presence of this pathogen could assist the development of laurel wilt-resistant avocado genotypes and inform efforts to manage this disease with other measures.
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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 | 0.000 | 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) | 0.001 | 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".