Infection of <i>Picea abies</i> clones with a homokaryotic isolate of <i>Heterobasidion parviporum</i> under field conditions
Bibliographic record
Abstract
Heterobasidion parviporum Niemelä & Korhonen is responsible for the majority of decay in conifers in northern Europe, which causes severe economic losses. In nature, heterokaryotic isolates of H. parviporum cause infection in Norway spruce (Picea abies (L.) Karst.). However, little is known on whether homokaryons of H. parviporum can infect trees under field conditions. In this study, 40-year-old clonal Norway spruce stems and roots were inoculated with a homokaryotic isolate of H. parviporum under field conditions. After four months, the infection frequency and necrotic lesion lengths were recorded. The homokaryon caused infection and provoked the development of necrotic lesions. Necrotic lesions were larger in roots than in stems. Among the studied Norway spruce genotypes, a Russian clone had the smallest necrotic lesions, whereas a Finnish clone developed the largest necrotic lesions. Clones with higher growth rates were more sensitive to fungal infection and wound damage. Under microscopic observation, H. parviporum grew adpressed to lumen cell walls, colonized tracheids next to rays, and induced lignification in cell walls close to the point of inoculation. This study provides a starting point for further studies on the ability of homokaryons to cause infection under field conditions and for discussions on factors affecting the resistance of Norway spruce against H. parviporum.
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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".