Development of an Efficient Plant Regeneration System for the Selenium-hyperaccumulator Astragalus racemosus and the Nonaccumulator Astragalus canadensis
Bibliographic record
Abstract
A method of in vitro plant regeneration for both the selenium-hyperaccumulator Astragalus racemosus ‘Cream Milkvetch’ and the nonaccumulator Astragalus canadensis ‘Canadian Milkvetch’ was developed with two induction media, M1 and M2. The M1 and M2 contain Murashige and Skoog basal medium plus vitamins, 8.07 μ m N -(2-chloro-4-pyridyl)- N′ -phenylurea, 2.5% (w·v −1 ) sucrose, 0.7% (w·v −1 ) agar (pH 5.7), and 0.89 μ m or 3.12 μ m a-naphthaleneacetic acid, respectively. In vitro cultures were initiated on these two types of media with three types of explants: cotyledons, hypocotyls, and roots. More than 93% of cultured explants from both species could form calli or calli with shoots. With regard to shoot formation, A. canadensis could produce multiple shoots from all types of explants more efficiently than A. racemosus . The highest shoot induction was approximately three shoots per explant in A. racemosus , whereas A. canadensis could reach ≈10 shoots per explant. M1 could induce more shoots than M2 no matter what type of explant was used, but the overall induction rates were no significant difference. Among the three types of explants used, the cotyledons were the best explants for shoot induction in A. canadensis , whereas hypocotyls were the best in A. racemosus . In A. racemosus , shoots could also be obtained from calli on the rooting medium containing Murashige and Skoog basal plus vitamins, 2.84 μ m indole-3 acetic acid, 2.5% (w·v −1 ) sucrose, and 0.7% (w·v −1 ) agar (pH 5.7). Approximately 43% of A. canadensis shoots and 19% of A. racemosus shoots could be rooted on the rooting medium.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".