Viability Testing of Orchid Seed and the Promotion of Colouration and Germination
Bibliographic record
Abstract
This study reports the ability of Fusarium to induce orchid seed colouration and germination. The in vitro bioassay germination test, using a Fusarium isolate from the protocorm of Cypripedium reginae , was compared with standard chemical procedures of triphenyl tetrazolium chloride (TTC) and acid fuchsin (AC) for testing seed viability. With Cypripedium reginae , Cypripedium parviflorum and Platanthera grandiflora , the efficiency of the bioassay was similar to that of the TTC and AC procedures. However, the bioassay was more appropriate for estimating embryo viability after a prolonged seed pretreatment (more than 2 h) in 10% sodium hypochlorite, a surface sterilant often used to enhance germination of terrestrial species. We also obtained in vitro Cypripedium reginae seed germination induction and protocorm formation by the same Fusarium isolate. This is the first confirmation of Bernard's early reports that orchid fusaria could stimulate seed germination (Bernard N. 1990. Révue Générale de Botanique12 : 108–120). However, the importance of the non-mycorrhizal Fusarium fungus in promoting germination seems to be relatively minor compared to that of specific Rhizoctonia orchid mycorrhizas. Our results are discussed in light of the current North American strategy on orchid conservation methods which proposes the use of symbiotic germination. Copyright 2000 Annals of Botany Company
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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) | 0.000 | 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) | 0.001 | 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".