Development of a specific PCR assay for the detection of Rhizoctonia solani AG 1-IB using SCAR primers
Bibliographic record
Abstract
AIMS: The aim of this study was to develop a specific and sensitive identification method for Rhizoctonia solani AG 1-IB isolates based on phylogenetic relationships of R. solani AG-1 subgroups using rDNA-internal transcribed spacer (rDNA-ITS) sequence analysis. METHODS AND RESULTS: A neighbour-joining tree analysis of 40 rDNA-ITS sequences demonstrated that R. solani AG-1 isolates cluster separately in six subgroups IA, IB, IC, ID, IE and IF. A molecular marker was generated from a random amplified polymorphic DNA fragment (RAPD). After conversion into a sequence-characterized amplified region (SCAR), a specific primer set for identification of subgroup AG 1-IB was designed for use in a polymerase chain reaction (PCR). The primer pair amplified a single DNA product of 324 bp. CONCLUSIONS: R. solani AG-1 subgroups were discriminated by sequence analysis of the ITS region. The designed SCAR primer pair allowed an unequivocal and rapid detection of R. solani AG 1-IB in plant and soil samples. SIGNIFICANCE AND IMPACT OF THE STUDY: Sequence analysis of the rDNA-ITS region can be used for differentiation of subgroups within AG-1. The use of the developed SCAR primer set allowed a reliable and fast identification of R. solani AG 1-IB and provides a powerful tool for disease diagnosis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".