Development and Evaluation of PCR-Based Diagnostic Assays for the Bacterial Speck and Bacterial Spot Pathogens of Tomato
Bibliographic record
Abstract
Bacterial speck and bacterial spot lesions can easily be confused with each other and with those formed by other tomato pathogens. To facilitate disease diagnosis, we developed and evaluated polymerase chain reaction (PCR)-based lesion assays using crude DNA extracts and primer sets COR1/2 (bacterial speck) and BSX1/2 (bacterial spot). All 29 pathogenic Pseudomonas syringae pv. tomato strains tested produced a 689-bp amplicon with COR1/2; 28 of the 37 geographically diverse bacterial spot-causing xanthomonad (BSX) strains that were tested generated the 579-bp BSX1/2 amplicon. The detection limit with plant samples was 30 to 50 CFU/reaction. In a 6-year study, the COR1/2 PCR assay diverged from the culture-based classical assay for only 3 of 70 bacterial speck lesion samples collected from Ontario greenhouses and tomato fields; the BSX1/2 assay was positive for 112 of the 124 confirmed bacterial spot lesions sampled. The majority (66%) of the BSX strains isolated from these lesions belonged to group D; the 12 strains that were BSX1/2-negative belonged to group C. Group D strains produced a 425-bp PCR product with crude DNA extracts but a 579-bp product with purified DNA; the former was identical to the latter except that it was missing 150 bp from the middle of the 579-bp sequence.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".