Development of a qPCR Assay for the Detection and Quantification of the Fungal Pathogen <i>Calonectria canadiana</i> on Conifers
Bibliographic record
Abstract
ABSTRACT A real‐time PCR TaqMan assay was developed for the detection of Calonectria canadiana , a fungal pathogen responsible for damping off, root rot and seedling blight in conifer forest nurseries in central and eastern North America. While highly significant in Quebec Forest nurseries, coniferous seedling mortality decreased significantly when nurseries transitioned from bare root to container seedling production. However, over the past few years, this pathogen has re‐emerged as a threat and millions of container white spruce seedlings were culled in two nurseries in eastern Quebec. A sensitive detection and quantification assay for C . canadiana was essential to investigate the biological and environmental factors driving this new epidemic. We designed primers and a TaqMan probe targeting the internal transcribed spacer (ITS) of C . canadiana . The resulting Ccan TaqMan assay successfully differentiated C . canadiana from other soil‐borne pathogens of the Nectriaceae encountered in Quebec Forest nurseries. The limit of detection of the assay was established at eight copies of C . canadiana ITS. The Ccan TaqMan assay quickly identified the presence of the pathogen in both symptomatic and asymptomatic white spruce ( Picea glauca ) seedlings. Furthermore, we demonstrated that the pathogen was more easily detected when DNA was extracted from necrotic needles at the base of the stem rather than from necrotic roots. This molecular tool will greatly aid in understanding the biology and epidemiology of C . canadiana .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".