Characterization and control of endophytic bacterial contaminants in in vitro cultures of<i>Piper</i>spp.,<i>Taxus baccata</i>subsp.<i>wallichiana</i>, and<i>Withania somnifera</i>
Bibliographic record
Abstract
Bacterial contamination is a serious problem that causes severe loss of in vitro grown cultures of a number of plants. This problem becomes even more acute if the bacterial contamination is of endophytic origin. In such cases, identification and characterization of the contaminants is essential for achieving specific control of the contaminants through selective use of antibiotic agents, especially if the routinely used contamination control methods practiced elsewhere in tissue culture studies are ineffective. Such is the case with the bacterial contamination observed in the present study. The five endophytic bacteria associated with Piper nigrum and Piper colubrinum, four endophytic bacteria associated with Taxus baccata subsp. wallichiana, two endophytic bacteria associated with Withania somnifera, and two bacteria common to all these plant species were isolated and characterized based on morphological and biochemical tests. Their taxonomic positions based on similarity indices were determined. A control strategy against these bacteria has been developed based on bacteriostatic or bactericidal actions of 12 antibiotics at three different concentrations by solid and liquid antibiogramme assays.
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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) | 0.001 | 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 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".