Nouvelle méthode de suivi au champ de la sénescence des feuilles de maïs
Bibliographic record
Abstract
A new method was developed to describe and quantify leaf senescence in a field-grown maize canopy with the purpose of future crop modelling. Leaf shape was analysed using the outlines of over 500 adult leaves from plants grown under diverse culture conditions. Leaf width (λ) taken at regular distances from the ligule (L) allowed the development of leaf-shape equations. These are third-degree polynomials. Thus, four leaf measurements are needed for characterizing leaf shape: maximum width (λm), total length (Lt), width at ligule level (λo), and distance from ligule to the point of maximum width (Lx). Assuming y = (λ/λm) and x = (L/Lt), the shape equation can be written as y = (1 x)(ax 2 + bx + y o ). Coefficients a and b were estimated from (λo/λm) = y o and (Lx/Lt) = x m . The leaf area between the ligule and any point on the midrib can be obtained by analytically integrating the leaf shape equation. In the present work, degreening was used as the indicator of senescence. Thus, once the shape equation was been defined, easily taken measurements of “green colour” allowed me to calculate the remaining green area by leaf. The vertical profile of the green area on the whole plant could then be described. The time course of green leaf area in a field-grown maize canopy was analysed from silking up to harvest. The farther the leaves were from the ear and the lower they were in the plant, the earlier they lost their green colour. The smallest leaves fully changed colour in 1 week, while this process took 2 weeks for the largest ones. A whole plant lost its green colour in about 5 weeks. Drought caused earlier but not faster leaf degreening. Low plant densities delayed discoloration of the leaves close to the ear, even under drought conditions. The start of senescence in leaves 716 was almost simultaneous in all crop conditions, but it could not be determined whether this was due to a threshold effect of the source/sink ratio or to another factor. This method was easy to set up for field studies with maize, but it could be also used for studies on other graminaceous species and some broad-leaved species. It could be extended to describe the physiological functioning over the leaf length and across the vertical profile of the whole plant. Key words: leaf shape, leaf area, leaf senescence, leaf color, maize, plant density, drought.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".