A Specific and Sensitive Method for the Detection of <i>Colletotrichum lindemuthianum</i> in Dry Bean Tissue
Bibliographic record
Abstract
To facilitate early diagnosis and improve control of bean anthracnose, a rapid, specific, and sensitive polymerase chain reaction (PCR)-based method was developed to detect the causal agent, Colletotrichum lindemuthianum, in bean (Phaseolus vulgaris) seed. Based on sequence data of the rDNA region consisting of the 5.8S gene and internal transcribed spacers (ITS) 1 and 2 of four C. lindemuthianum races and 17 Colletotrichum species downloaded from GenBank, five forward primers were designed and evaluated for their specificity. Among them, one forward primer was selected for use in combination with ITS4 to specifically detect C. lindemuthianum. A 461-bp specific band was amplified from the genomic DNA template of 16 representative isolates of C. lindemuthianum, but not from 58 representative isolates of 17 other Colletotrichum species or 10 bean pathogens. Moreover, to enhance the sensitivity of detection, nested PCR was applied, which allowed the detection of as little as 10 fg of C. lindemuthianum genomic DNA and 1% infected seed powder, which was mixed with 99% healthy seed powder. The diagnostic analysis can be completed within 24 h, compared with about 2 weeks required for culturing. Furthermore, this method can be performed and interpreted by personnel with no specialized taxonomic expertise.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".