Floral nectary structure, nectar production, and carbohydrate composition in the<i>Lilium</i>Asiatic hybrid ‘Trésor’
Bibliographic record
Abstract
Floral nectary structure, nectar production, and carbohydrate composition were compared from petals (“inner tepals”) and sepals (“outer tepals”) of Lilium Asiatic hybrid ‘Trésor’ (Liliaceae). The six nectaries each occupied a narrow furrow bordered by two convergent ridges extending adaxially from the petal and sepal base. Each sepal nectary furrow was shorter and more concealed. In both nectary types, many vascular bundles comprising xylem and phloem supplied 5.5–8 layers of nectariferous parenchyma cells below the epidermis, which lacked stomata. Transmission electron microscopy of sepal nectaries demonstrated that parts of the outer epidermal wall adhered to an intact but uplifted cuticle in nectar-secreting flowers. Both apoplastic and symplastic routes were continuous from the vascular bundles to the nectary epidermis. Starch breakdown from amyloplasts throughout the nectary likely augmented nectar production. Nectar solute concentration from another Asiatic hybrid, ‘Orange Pixie’, was also significantly higher in petals. In ‘Trésor’, significantly more nectar was available from sepals, possibly reflecting reduced evaporation from multiple nectar droplets within the covered nectary furrow. However, for both hybrids, the same quantity of nectar sugar was produced by petals and sepals. Nectar composition from petals and sepals also was alike, in ‘Orange Pixie’ averaging 67/19/14 (= sucrose/fructose/glucose) and 59/25/17, respectively, and in ‘Trésor’ averaging 68/23/10 and 62/27/12, respectively.
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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) | 0.000 | 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".