In Vitro Technologies for American Chestnut (Castanea dentata (Marshall) Borkh) Conservation
Bibliographic record
Abstract
), a native species of eastern North America, is an economically important deciduous hardwood tree that has been designated as endangered in Canada. The population of American chestnut trees has dwindled significantly across Southern Ontario due to chestnut blight and many of the surviving trees continue to show blight disease symptoms. American chestnut requires efficient strategies for propagation and preservation for species recovery. The objective of this study was to develop a long-term plant conservation program using micropropagation and cryopreservation protocols. An in vitro technology using a liquid-based temporary immersion system (TIS) was developed for micropropagation of American chestnut. The highest rate of shoot multiplication was observed in cultures grown in the DKW (Driver and Kuniyuki 1984) basal medium supplemented with 2.2 µM 6-benzylaminopurine and 1.0 µM gibberellic acid. More than 95% of proliferated microshoots, about 40-50 mm in size, developed roots after 30 days of culture within bioreactor vessels containing DKW basal medium supplemented with 15 µM 3-Indolebutyric acid. Rooted plantlets transplanted to the greenhouse had a survival efficiency of 82% after one month of growth. The cryopreservation protocol for germplasm preservation was developed through droplet vitrification of shoots. Optimal regeneration of shoot tips occurred from explants precultured on stepwise concentrations of sucrose and subsequent dehydration in PVS3 for 30 min. Cryopreserved shoot tips were regenerated to whole plants using pre-optimized conditions of micropropagation. This study confirms the potential of TIS for micropropagation in ex situ conservation and reintroduction of endangered American chestnuts and possibly other woody 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".