Comparison of techniques for estimation of resting spores of <i>Plasmodiophora brassicae</i> in soil
Bibliographic record
Abstract
Clubroot ( Plasmodiophora brassicae ) is an important disease of canola ( Brassica napus ) and other brassica crops. Accurate estimation of inoculum load in soil is important for evaluating producer risk in planting a susceptible crop, but also for evaluation of management practices such as crop rotation. This study compared five molecular techniques for estimating P. brassicae resting spores in soil: quantitative polymerase chain reaction ( qPCR ), competitive positive internal control PCR ( CPIC ‐ PCR ), propidium monoazide PCR ( PMA ‐ PCR ), droplet digital PCR (dd PCR ) and loop‐mediated isothermal DNA amplification ( LAMP ). For dd PCR and LAMP , calibrations were developed using spiked soil samples. The comparison was carried out using soil samples collected from a long‐term rotation study at Normandin, Québec, with replicated plots representing 0‐, 1‐, 2‐, 3‐, 5‐ and 6‐year breaks following susceptible canola infested with clubroot. CPIC ‐ PCR and dd PCR provided repeatable estimates of resting spore numbers in soil compared with estimates from qPCR or LAMP alone. CPIC ‐ PCR provided the most robust measurement of spore concentration, especially in the 2 years following a crop of susceptible canola, because it corrected for effects of PCR inhibitors. PMA ‐ PCR demonstrated that a large proportion of the DNA of P. brassicae detected in soil after the susceptible canola crop was derived from spores that were immature or otherwise not viable. Each assay provided a similar pattern of spore concentration in soil, which supported the conclusion of a previous study at this site that resting spore numbers declined rapidly in the first 2 years after a susceptible crop, but much more slowly subsequently.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".