Detection and identification of phytoplasmas affecting blackcurrant and redcurrant
Bibliographic record
Abstract
During October-November/2011, blackcurrant (Ribes nigrum L.) and redcurrant (Ribes rubrum L.) shrubs exhibiting peach symptoms of leaf redness and downward curling in Harrow, Ontario, Canada, were tested for phytoplasma. Total DNA was extracted (Fast DNA Spin kit, MP Biomedicals, USA) and used in a nested PCR assay with universal primers that target the phytoplasma 16S rRNA gene, P1/P7 (Deng and Hiruki, 1991; Smart et al, 1996) followed by either R16F2n/R2 (Gundersen and Lee, 1996) or fU5/rU3 (Lorenz et al, 1995) for the nested reaction. R16F2n/R2 PCR amplicons were obtained for all the symptomatic plants collected, purified (Cycle Pure kit, Omega, USA) and sequenced bi-directionally (University of Health Network, Toronto, Canada). Sequences were compared to those of reference phytoplasmas in GeneBank. BLAST analysis showed a 100% of 16S rDNA sequence identity between the two phytoplasmas detected in both blackcurrant and redcurrant plants, and a 99% of sequence identity to those of members of group 16SrX, subgroup 16SrX-A. Virtual and actual RFLP of the R16F2n/R2 and fU5/rU3 amplicons with AluI, RsaI and MseI restriction endonucleases yielded RFLP patterns similar to those of phytoplasma members of the group 16SrX ‘Apple Proliferation’, subgroup 16SrX-A. Phylogenetic analysis (MEGA version 4.1, USA) based on the 16S rDNA sequences confirmed RFLP and BLAST results. Phytoplasmas of group 16SrX have been previously reported in Harrow, Ontario, affecting Prunus and Pyrus species. However, results represent the first record of a 16SrX-A infecting blackcurrant and redcurrant in Canada, and provide a valuable tool for further epidemiological studies of a 16SrX phytoplasma in these two plant species.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".