Biodiversity in<i> Lilium </i>: A Review
Bibliographic record
Abstract
Lilium is a subbstantial genus administered throughout temperate and cooler regions of the Northern Hemisphere consisting approximately 110 species. The genus possess a great genetic diversity in many valuable horticultural traits which is manifested in flower colour, forms, shape, size, fragrance, resistance to diseases, and many physiological characteristics. Intensive agricultural practices, climate change and industrialization are having a straight impact on biodiversity. Comprehensive understanding of the species, including levels and form of genetic variation forms the basis for the successful management and safeguarding of populations of rare, endangered or threatened species. The biodiversity become important components of different ecosystems. Use of single new improved varieties of crops for large areas is a big threat for crop biodiversity. This review concentrates to provide species-level information on biodiversity in the genus lilium and their future use in breeding programs. We focus mainly on species used in breeding programme and grown mainly for cut flowers and pot production. For example; trumpet shaped Lilium species showed comparative better prospective for exploitation than other species. We also present a brief summary on research area that needs further development using biotechnological techniques like molecular assisted breeding, QTLs and GISH/FISH and chloroplast genomes for comparative and phylogenetic analyses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".