Interactions between <em>Phytophthora cactorum</em>, <em>Armillaria gallica</em> and <em>Betula pendula</em> Seedlings Subjected to Defoliation
Bibliographic record
Abstract
The purpose of this study was to better understand the interactive impact of two soil-borne pathogens, Phytophthora cactorum (as the primary pathogen) and Armillaria gallica (as secondary), on two-year-old seedlings of silver birch (Betula pendula) subjected to stress caused by mechanical defoliation simulating primary insect feeding. One year after treatments, the chlorophyll fluorescence measurement and gas chromatography coupled with mass spectrometry (GC-MS) were used to analyze the photosynthetic activity in leaves, the volatile organic compounds (VOCs) emitted by birch leaves and chemical compounds from roots. Only the infection of roots by P. cactorum increased photosynthetic rates in the leaves, which may suggest its cryptic development in contrast to fungi. The birch leaves in seedlings exposed to 50% defoliation, inoculation with P. cactorum and A. gallica emitted more aromatic carbonyls and alcohols, as well as half as much aliphatic esters, compared to untreated controls. In infected birch roots, the production of phenols, triterpenes and fatty alcohols increased, but fatty acids decreased. This was the first experimental confirmation of the pathogenicity of P. cactorum on silver birch seedlings in Poland. The most severe damage to roots took place only in the case of two-way or three-way interactions. Higher levels of aromatic carbonyls and alcohols in leaves, as well as phenolic compounds in roots of stressed birches (compared to control) suggest an activation of plant systemic acquired resistance (SAR).
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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 | 0.001 |
| 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".