Diversity Among Bacteria Causing Blotch Disease on the Commercial Mushroom,
Bibliographic record
Abstract
A total of 251 bacterial isolates were isolated from blotched mushroom samples obtained from various mushroom farms in Canada. Out of 251 stored isolates, 170 isolates were tested for pathogenicity on Agaricus bisporus through mushroom rapid pitting test with three distinct pathotypes observed: dark brown, brovm and yellow/yellow-brown blotch. Phenotypic analysis of 83 isolates showed two distinct proteinase K resistant peptide profiles. Profile group A isolates exhibited peptides with masses of 45, 18, 16 and 14 kDa and fiirther biochemical tests identified them as Pseudomonasfluorescens III and V. Profile group B isolates lacked the 16-kDa peptide and the blotch causing bacterial isolates of this group was identified as Serratia liquefaciens and Cedecea davisae. Comparative genetic analysis using Amplified Fragment Length Polymorphism (AFLP) on 50 Pseudomonas sp. isolates (Group A) showed that various blotch symptoms were caused by isolates distributed throughout the Pseudomonas sp. clusters with the exception of the Pseudomonas tolaasii group and one non-pathogenic Pseudomonas fluorescens cluster. These results show that seven distinct Pseudomonas sp. genotypes (genetic clusters) have the ability to cause various symptoms of blotch and that AFLP can discriminate blotch causing from non-blotch causing Pseudomonasfluorescens. Therefore, a complex of diverse bacterial organisms causes bacterial blotch disease.
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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 | 0.001 | 0.001 |
| 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".