Phenotypic and genetic characterization of <i>Paecilomyces</i> <i>lilacinus</i> strains with biocontrol activity against root-knot nematodes
Bibliographic record
Abstract
Efficient selection of fungi for biological control of nematodes requires a series of screening assays. Assessment of genetic diversity in the candidate species maximizes the variety of the isolates tested and permits the assignment of a particular genotype with high nematophagous potential using a rapid novel assay. Molecular analyses also facilitate separation between isolates, allowing the identification of proprietary strains and trace biocontrol strains in the environment. The resistance of propagules to UV radiation is an important factor in the survival of a biocontrol agent. We have analyzed 15 strains of the nematophagous fungus Paecilomyces lilacinus using these principles. Arbitrarily primed DNA and allozyme assays were applied to place the isolates into genetic clusters, and demonstrated that some genetically related P. lilacinus strains exhibit widespread geographic distributions. When exposed to UV radiation, some weakly nematophagous strains were generally more susceptible than effective isolates. A microtitre tray-based assay used to screen the pathogenic activity of each isolate to Meloidogyne javanica egg masses revealed that the nematophagous ability varied between 37%-100%. However, there was no clear relationship between nematophagous ability and genetic clusters. Molecular characterizations revealed sufficient diversity to allow tracking of strains released into the environment.
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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 | 0.001 |
| 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".