Development of a qPCR assay and a LAMP assay for <i>Verticillium longisporum</i> detection and a triplex qPCR assay for simultaneous detection of <i>V. longisporum</i> , <i>Leptosphaeria biglobosa</i> and <i>L. maculans</i> from canola samples
Bibliographic record
Abstract
Abstract Verticillium wilt, Verticillium stem striping, and Verticillium stripe, are common disease names that all denote infection caused by Verticillium longisporum , on canola, or other Brassica crops. In this study, a quantitative PCR (qPCR) assay and a loop-mediated isothermal amplification (LAMP) assay were developed for the detection of V. longisporum from canola stem samples. Both assays are specific to V. longisporum at the species level and ubiquitous at the strain level. The low limit for positive detection of the two assays is 1 pg fungal DNA in a 20-µ L reaction or 1,400 fungal cells in 100-mg plant tissue. The qPCR assay was combined with the duplex qPCR assay for the two blackleg pathogens, Leptosphaeria biglobosa and L. maculans to constitute a triplex qPCR system for simultaneous detection of all three pathogens. The usefulness of this triplex qPCR system was verified on canola samples collected from various locations in Alberta, Canada. Using this triplex qPCR system, V. longisporum was detected from one sample, while the two blackleg pathogens were detected at higher frequencies. Since it is sometimes difficult to differentiate Verticillium stripe and blackleg on Alberta canola samples based on visual symptoms, the triplex qPCR system is an important tool for the detection of V. longisporum , especially when its presence is masked or obscured by symptoms of blackleg.
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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 | 0.002 | 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 | 0.000 |
| 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".