Evaluation of <i>Ferula assa-foetida</i> L. accessions under different temperature regimes to overcome seed dormancy and different media mixtures to promote seedling growth
Bibliographic record
Abstract
Ferula assa-foetida L., a perennial crop of the Apiaceae family, has internal physical seed dormancy that inhibits its germination ability. Hence, to improve germination capacity and overcome seed dormancy, the present study was conducted using six accessions for assessing seed viability using 1% Tetrazolium test three times every 6 months and grown under three different temperature treatments (5, 15, and 25 °C) during 2018–19 and 2019–20. These accessions were also grown under six different potting mixtures to optimize the best media for its survivability under field conditions. Results from the tetrazolium test indicated an average seed viability of 73.03% and showed an ∼5% reduction during 2018–20. From germination tests, a chilling treatment of 5 °C was found most effective for breaking dormancy. Besides, the seedlings grown under different potting mixtures showed that media mixtures in the combination of soil, sand, farmyard manure, and cocopeat were most appropriate for better germination stand. However, further studies are required to explain the agro-practices to cultivate this endangered plant at field capacity. It was also observed that genotypes EC966538 and EC968470 were best performers for overall germination as well as seedling survival parameters and could be used as base populations in future selection and improvement breeding programs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".