PCR Detection of Phytoplasma from Sweet Potato Witches' Broom Disease
Bibliographic record
Abstract
Using the software of PCRDESN, two pairs of primers, R16mF2/R16mR2 and R16F2/R16R2, were designed based on the 16S rDNA sequence of Phytoplasma from Michigen Aster yellows (MIAY), Elm yellows (EY), Canadian peach X-disease (CX), Jujube witches' broom (JWB) and Cherry lethal yellow (CLY) published in references. DNAs as templates were extracted from sweet potato midrib infected with or without Phytoplasma. Phytoplasma in sweet potato witches' broom was detected using PCR and Nested-PCR. A Phytoplasma-specific 1.5 kb fragment and a 1.2 kb special fragment were amplified with PCR and Nested-PCR, respectively. The minimal amount of DNA extracted from the infected sweet potato for molecular detection using PCR and Nested-PCR were 107.3 pg/μl and 0.01073 pg/μl. It is showed that the methods of PCR and Nested-PCR were very sensitive, rapid and reliable in detecting sweet potato disease associated with Phytoplasma. Furthermore, Nested-PCR based on the PCR was more sensitive than PCR about 10000 times in detecting phytoplasma in sweet potato witches' broom. The conclusion is that the molecular detection of Phytoplasma in sweet potato witches' broom is a better method nowadays.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".