Quantifying Phenology and Maturity in Crisphead Lettuce
Bibliographic record
Abstract
The Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) identification key was adapted for crisphead lettuce ( Lactuca sativa ) to facilitate identification of phenological stages and decisions regarding field operations from seeding to harvest maturity. The original system described leaf development based on leaf count from stage 11 (1 leaf) to stage 19 (9 leaf), and head development based on percentage of expected head size reached at maturity from stage 41 to 49. The new coding leaf development stages range from 11 to 29, corresponding to the 1-leaf to 19-leaf stages. The head development stages also ranged from 41 to 49, but phenological stages near commercial maturity from 43 to 49 are now described as a function of head firmness. The important maturity traits of crisphead lettuce include head size and density. Head volume can be estimated from three diameters by using Currence's equation, which takes into account head geometry. The firmness index obtained by hand compression gave a more precise estimate of head density than the density estimate derived from Currence's equation or the sphere equation. Crisphead lettuce development stages and maturity traits can be easily quantified in the field for use in planning field operations and for experimental purposes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".