Species Diversity of <i>Dickeya</i> and <i>Pectobacterium</i> Causing Potato Blackleg Disease in Pakistan
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
Potato blackleg is caused by a diverse species of pectinolytic bacteria. In Pakistan, approximately 90% of the pathogens involved belong to Pectobacterium atrosepticum. Survey (2014 to 2017), sampling, and isolation from different potato growing areas of Punjab, Pakistan depicted an overall disease incidence of approximately 15%. Thirty-six pectinolytic strains confirmed through biochemical and pathogenicity testing were characterized via gapA gene to identify them at the species level. To further validate the identification, one strain from each species SS26 (P. atrosepticum), SS28 (Pectobacterium polaris), SS70 (Dickeya dianthicola), SS90 (Pectobacterium parmentieri), SS95 (Pectobacterium punjabense), and SS96 (Pectobacterium versatile) were selected for draft genome sequencing and multilocus sequence analysis of 13 housekeeping genes (fusA, rpoD, acnA, purA, gyrB, recA, mdh, mtlD, groEL, secY, glyA, gapA, and rplB). Phylogenetic analysis revealed considerable genetic diversity in the genus Pectobacterium. In silico DNA–DNA hybridization and average nucleotide identity values of the strains selected for genome sequencing were determined with other reference Pectobacterium and Dickeya strains. Moreover, all six representative strains were also phenotypically characterized on the basis of metabolism of different carbon sources. Overall, on the basis of genotypic and phenotypic characteristics, these 36 isolates were grouped into six species: P. atrosepticum, P. versatile, P. parmentieri, P. polaris, P. punjabense, and D. dianthicola.
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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 | 0.000 |
| 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) | 0.000 | 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