What is the best way to maintain embryogenic capacity of embryogenic lines initiated from Douglas-fir immature embryos?
Bibliographic record
Abstract
Douglas-fir (Pseudotsuga menziesii (Mirb) Franco) is a native conifer from the Pacific North-West of the US and Canada, and is one of the most important timber species used in the world. Douglas-fir is highly productive in a range of climatic conditions and has valuable wood properties (quality) as well as a strong tolerance to diseases and insects. In Europe, Douglas-fir is a major species for reforestation with increasing demand for its wood. Adaptation of new varieties to climate change and associated stresses is one challenging question for ongoing breeding programs. Efficient selection and vegetative propagation of improved varieties are key issues to maintain productivity in plantation forestry (Lelu-Walter et al. 2013), however, as in many other conifers, early maturation is preventing clonal forestry through conventional multiplication methods in Douglas-fir (Bastien et al. 2013). Somatic embryogenesis from immature seeds, coupled with cryopreservation, is a promising retroactive clonal propagation system of selected trees. This technology has been developed for an increasing number of conifer species (Klimaszewska et al. 2016). Excluding patents, there are only a few published studies on Douglas-fir somatic embryogenesis (Durzan and Gupta 1987; Pullman et al. 2005, 2009). One recurrent problem is the sustainable multiplication of initiated embryogenic material, i.e., embryonal masses (EMs). Yellowish, non-embryogenic cells (NEC), which are interspersed with EM, is frequently observed during this process. In this work, we describe EM morphology and cytology (light and confocal microscopy) of different embryogenic lines. A suggested method to reduce the formation of NEC and sustain EM proliferation is presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".