In vitro propagation of <i>Vaccinium floribundum</i> Kunth from seeds: promissory technology for mortiño accelerated production
Bibliographic record
Abstract
The Andean mortiño (Vaccinium floribundum Kunth) grows wild in the northern paramos of South América. The berries present potential opportunities for agribusiness, but an efficient technology for the production of plants and berries is required. On the other hand, the development of plant production methods from mortiño seeds will allow the plants’ accessibility and its potential use in breeding programs. The objective of this study was to develop an efficient in vitro protocol for accelerated production using seeds. We carried out the research in four phases: seed germination, plant multiplication, rooting, and acclimatization in the greenhouse. For in vitro seed germination, we studied the effect of two culture media [woody plant medium (WPM) and Murashige and Skoog medium (MS], two photoperiods (16 and 24 hours of light), and two temperatures (18 and 28 °C). The best treatment was found to be WPM + 24 h light + 18 °C. In the micropropagation of seedlings, the effect of two concentrations of three cytokinines [(trans-zeatin riboside (TZR), zeatin (ZEA), and 2-isopentenyl adenine (2iP)], and two photoperiods (16 and 0 h light) was evaluated, whereby the concentration of 0.5 mg L−1 of TZR was the best treatment. For rooting, two doses of three auxins [indole-3-butyric acid (IBA), 1-naphthaleneacetic acid (NAA), and indole-3-acetic acid (IAA)] were evaluated, resulting in the 2 mg·L−1 concentration of IBA giving the best root induction. Finally, the in vitro rooted plants were acclimatized in a greenhouse. We found that peat was the best substrate. These results show that the technology developed here is useful for in vitro production of V. floribundum using seeds.
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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 | 0.000 |
| 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 | 0.000 | 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".