Detection of <i>Xanthomonas translucens</i> pv. <i>undulosa</i>, pv. <i>translucens</i>, and pv. <i>secalis</i> by Quantitative PCR
Bibliographic record
Abstract
A probe-based quantitative PCR (qPCR) protocol was developed for detection and evaluation of the wheat bacterial leaf streak pathogen Xanthomonas translucens pathovar (pv.) undulosa. The protocol can also detect X. translucens pv. translucens and X. translucens pv. secalis but can’t differentiate the three pathovars. When tested on nontarget DNA (i.e., from plant; bacteria other than X. translucens pv. undulosa, X. translucens pv. translucens, and X. translucens pv. secalis; and culture of microorganisms from wheat grains), the qPCR showed a high specificity. On purified X. translucens pv. undulosa DNA, the qPCR was more sensitive than a loop-mediated isothermal amplification assay. When DNA samples from a set of serial dilutions of X. translucens pv. undulosa cells were tested, the qPCR method could repeatedly generate quantification cycle (Cq) values from the dilutions containing ≥1,000 cells. Since 2 µl of the total 50 µl of DNA was used in one reaction, one qPCR reaction could detect the presence of the bacteria in samples containing as few as 40 bacterial cells. The qPCR could detect the bacteria from both infected grain and leaf tissues. For seed testing, a protocol for template preparation was standardized, which allowed one qPCR reaction to test DNA from the surface of one wheat grain. Thus, the qPCR system could detect X. translucens pv. undulosa, X. translucens pv. translucens, and/or X. translucens pv. secalis in samples where the bacteria had an average concentration of ≥40 cells per grain.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.002 |
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".