Development of a SCAR marker for detection of<i>Bipolaris sorokiniana</i>causing spot blotch of wheat
Bibliographic record
Abstract
Spot blotch of wheat caused by Bipolaris sorokiniana is an important disease of wheat, especially in slightly warm (25 ± 1 °C) and humid weather conditions. A quick and reliable PCR-based diagnostic assay has been developed to detect B. sorokiniana using a pathogen-specific marker derived from genomic DNA. A PCR-amplified band of 650 bp obtained in B. sorokiniana isolates using universal rice primer (URP 1F) was cloned in pGEMT easy vector and sequenced. Based on sequences, six primers were designed, out of which a primer pair RABSF1 (GGTCCGAGACAACCAACAA) and RABSR2 (AAAGAAAGCGGTCGACGTAA) amplified a sequence of 600 bp in B. sorokiniana isolates. The specificity of the marker when tested against 40 isolates of B. sorokiniana, seven isolates of other species of Bipolaris, and 27 isolates of other pathogens infecting wheat and other crops showed a specific band of 600 bp only in B. sorokiniana. The detection limit was 50 pg of genomic DNA. The marker could detect the pathogen in soil and wheat leaves at presymptomatic stage. This sequence characterized amplified region (SCAR) marker designated as SCRABS(600) could clearly distinguish B. sorokiniana from other fungal plant pathogens, including Bipolaris spp. The utilization of this diagnostic PCR assay in analysis of field soil and wheat leaves will play a key role in effective management of the disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".