Assessment of Real-Time PCR Techniques for the Detection of Airborne Fungal Pathogens of Wheat: Role of DNA Extraction on Spore Quantification
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Our research focused on developing a highly sensitive whole-spore real-time immuno-PCR (RT-iPCR) assay for the detection of three wheat fungal pathogens: Pyrenophora tritici-repentis ( Ptr ), Fusarium graminearum ( Fg ), and Puccinia striiformis forma specialis (f. sp.) tritici ( Pst ). RT-iPCR measurements were compared to more well-established quantitative PCR (qPCR) assays to compare their performance. While specificity remained a challenge for RT-iPCR, the direct spore measurements negate the need for DNA extraction, making RT-iPCR a potentially valuable technique that warrants further research. An alternative approach was developed to determine DNA extraction efficiency and quantification of spore numbers by qPCR, which is currently a methodological gap in most qPCR spore measurements. DNA extraction efficiency determined for Fg, Pst, and Ptr spores were 5.0 ± 0.1, 7.0 ± 0.4, and 290 ± 36%, respectively, demonstrating important implications for the accuracy of these techniques when DNA recovery is not considered.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".