Molecular Detection of <i>Apiosporina morbosa</i>, Causal Agent of Black Knot in <i>Prunus virginiana</i>
Bibliographic record
Abstract
A specific and sensitive polymerase chain reaction (PCR) assay was developed to detect Apiosporina morbosa, the causal agent of black knot disease on chokecherry, Prunus virginiana (including the cultivar 'Shubert Select'). A pair of A. morbosa-specific forward and reverse primers (AMF and AMR) was designed from the internal transcribed spacer (ITS) regions of A. morbosa, preamplified by universal ITS primers ITS1 and ITS4, and compared with the ITS region sequences of Fusarium, Alternaria, Phoma, and Cladosporium species associated with black knots. The primers were tested for their specificity to A. morbosa detection in the PCR assays using DNA derived from 64 pure cultures, including 42 single-spore isolates of A. morbosa and 22 isolates of other fungi, as well as healthy and diseased plant branches collected from the field. A product of ~400 bp was amplified from DNA of all isolates belonging to A. morbosa. No product was amplified from DNA of other fungal species, confirming the specificity of the newly designed primers. Within plant tissues, the pathogen was detected at further distances from the edges of knots on thicker branches bearing larger knots compared with thinner branches bearing smaller knots. The PCR assay has shown high sensitivity, needing only 100 fg of the A. morbosa DNA for a reliable PCR amplification with the AMF and AMR primers.
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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) | 0.000 | 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".