Optimization of a biolistic transformation system for transfer of antifreeze gene KN2 and the bar herbicide resistance gene in common wheat
Bibliographic record
Abstract
We studied the effects of different media for callus induction and differentiation, and pre-culture period of immature wheat embryo culture on biolistic transformation efficiency for including antifreeze gene KN2 and bar conferring resistance to the herbicide bialaphos. The percentage of plantlets generated from induction and differentiation media without Cu2+ was lower than those cultured on differentiation media with Cu2+ (71.15%) or induction media with Cu2+ (68.45%) and both induction and differentiation media with Cu2+ (52.17%). The combinations of Nor medium for callus induction and Cu2+ medium for regeneration, and Cu2+ medium for induction and R medium for regeneration were superior for biolistic transformation. The calli induced on Cu2+ medium and pre-cultured for 4 d before biolistic transformation, and cultured on R medium after biolistic transformation produced the highest percentage (65%) of transgenic plantlets with the KN2 gene. Overall, about 50% plantlets regenerated from calli pre-cultured 4d before bombardment carried the KN2 gene; 44.7% of the plantlets carried the bar gene, which was higher than for any other treatment, followed by pre-culture 1d with 31.43% transformation rate for the KN2 gene and 20% transformation rate for the bar gene.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".