Detection and Quantification of <i>Pythium tracheiphilum</i> in Soil by Multiplex Real-Time qPCR
Bibliographic record
Abstract
In Canada, head lettuce (Lactuca sativa capitata) is extensively produced in the muck soils of southwestern Québec. However, yields are increasingly affected by various soilborne pathogens, including Pythium spp., which cause wilt and damping off. In a survey conducted in Québec muck soils in 2010 and 2011, Pythium tracheiphilum Matta was identified as the predominant Pythium sp. in the root of head lettuce showing Pythium stunt symptoms. Therefore, to improve risk assessment and help further understanding of disease epidemiology, a specific and sensitive real-time quantitative polymerase chain reaction (qPCR) assay based on TaqMan-minor groove binder (MGB) technology was developed for P. tracheiphilum. The PCR primers along with a TaqMan-MGB probe were designed from the ribosomal internal transcribed spacer 2 region. A 100-bp product was amplified by PCR from all P. tracheiphilum isolates tested while no PCR product was obtained from 38 other Pythium spp. or from a selection of additional lettuce pathogens tested. In addition to P. tracheiphilum, the assay was multiplexed with an internal control allowing for the individual validation of each PCR. In artificially infested soils, the sensitivity of the qPCR assay was established as 10 oospores/g of dry soil. P. tracheiphilum was not detected in soils in which lettuce has never been grown; however, inoculum ranged from 0 to more than 200,000 oospores/g of dry soil in commercial lettuce fields. Also, disease incidence was positively correlated with inoculum concentration (r = 0.764). The results suggest that inoculum concentration should be considered when making Pythium stunt management decisions. The developed qPCR assay will facilitate reliable detection and quantification of P. tracheiphilum from field soil.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".