Detection of interactions between the pea root rot pathogens <i>Aphanomyces euteiches</i> and <i>Fusarium</i> spp. using a multiplex <scp>qPCR</scp> assay
Why this work is in the frame
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Bibliographic record
Abstract
Pea root rot complex ( PRRC ) describes a group of closely associated soilborne pathogens that cause root rot disease in field pea. Aphanomyces euteiches and several Fusarium spp. are the most prevalent and damaging microorganisms within this complex, although the impact of interspecific interactions on disease progression remains largely unexplored. Furthermore, a fast and reliable method of detecting and quantifying these pathogens is not currently available. The objectives of this experiment were to: (i) investigate the effect of microbial interactions on root rot severity in pea under greenhouse conditions; and (ii) characterize changes in colonization rates when multiple pathogens are present using qPCR . Seeds were exposed to three species of Fusarium and were planted into A. euteiches ‐infested soil in varying combinations. For each experimental treatment, an index of disease severity was used to visually rate disease symptoms. Additionally, two triplex quantitative PCR ( qPCR ) assays were designed to detect and quantify changes in pathogen population dynamics on the roots. Both assays demonstrated a high degree of sensitivity and efficiency. Results from two independent greenhouse trials indicated an increase in disease severity in the presence of multiple pathogen species compared to single inoculations. Specifically, roots infected with A. euteiches were more susceptible to fusarium root rot than those exposed only to Fusarium spp. These observations were confirmed by qPCR results, which revealed significant changes in colonization rates when multiple species were present. These findings suggest an increased risk of yield loss in regions where A. euteiches and Fusarium spp. co‐occur.
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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 it