Quantification of endophyte Serendipita indica in Brassica napus roots by qPCR
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Context The fungal endophyte Serendipita indica enhances plant growth and plant resistance to biotic and abiotic stresses. Inoculum concentration greatly impacts the endophyte–plant interaction from mutualism to antagonism. Aims and methods We used both microscopy and qPCR to examine the effect of inoculum concentrations on the extent (%) and density of Brassica napus L. root colonisation by S. indica. B. napus seeds were inoculated with the fungus at five different inoculum concentrations (1–10% w/w basis). Key results Standard curves were constructed using the mean threshold cycle (Ct) and serially diluted gDNA ranging between 4.14 × 102 and 2.65 × 105 colony forming units (CFU). The result indicated a linear relationship between Ct and the log of input DNA. Variation in inoculum concentration significantly affected the root colonisation density by the fungus shown by qPCR. However, the percent root colonisation (PRC) measure was not affected and remained the same across all the treatments. Conclusions Our findings show that the qPCR assay developed will determine the colonisation density whereas PRC gives a measure of the incidence of infected roots. Also, we suggest that the optimum quantity of inoculum is a key factor for a successful interaction that impacts the plant–S. indica interaction. Implications To our knowledge, this is the first study that quantitative qPCR has been used to investigate the correlation between inoculum quantities and the corresponding density of root colonisation in S. indica.
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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 | 0.001 |
| 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) | 0.001 | 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