Interaction of Ginseng with Ilyonectria Root Rot Pathogens
Bibliographic record
Abstract
The Ilyonectria radicicola species complex (A.A. Hildebr.) A. Cabral and Crous 2011 contains species of soilborne necrotrophic plant pathogens. The most aggressive to ginseng roots is I. mors-panacis, whereas I. robusta, I. crassa, I. panacis and I. radicicola are less aggressive. Infected ginseng roots show orange-red to black-brown lesions that can expand into a severe root rot, known as disappearing root rot, where only epidermal root tissue remains. Leaves become red-brown with wilting, and stems can have vascular discoloration with black-brown lesions at the base. Less aggressive Ilyonectria species trigger jasmonic acid (JA)-related defenses inducing host ginsenosides, pathogenesis-related (PR) proteins, wound periderm, and cell wall thickening. In contrast, I. mors-panacis triggers reactive oxygen species (ROS) and salicylic acid (SA) production but suppresses JA-related defenses and ginsenoside accumulation. It is also able to suppress SA-related PR protein production. Virulence factors include potential effectors that may suppress PAMP (Pathogen Associated Molecular Patterns) triggered immunity (PTI), polyphenoloxidases, Hsp90 inhibitors, siderophores and cell-wall-degrading enzymes, such as pectinases. Overall, I. mors-panacis appears to be more aggressive because it can suppress JA and SA-related PTI allowing for more extensive colonization of ginseng roots. While many possible mechanisms of host resistance and pathogen virulence mechanisms have been examined, there is a need for using genetic approaches, such as RNAi silencing of genes of Panax or Ilyonectria, to determine their importance in the interaction.
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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".