Vertical Profile of Leaf Senescence during the Grain‐Filling Period in Older and Newer Maize Hybrids
Bibliographic record
Abstract
Grain yield improvement of maize (Zea mays L.) hybrids has been associated with delayed leaf senescence. The objective of this study was to quantify the vertical profile of leaf senescence during the grain‐filling period in an older hybrid (‘Pride 5’) and two more recent maize hybrids (‘Pioneer 3902’ and ‘Pioneer 3893’). Leaf senescence was rated visually from silking to maturity on each individual leaf across the vertical leaf‐area profile along the stem of maize plants growing in the field at 1, 3.5, and 12 plants m−2 near Elora, ON, Canada, during the 1999 to 2001 growing seasons. Maximum leaf area index (LAI) at silking was greater in newer hybrids than in the older hybrid. Rate of leaf senescence across hybrids and plant population densities progressed at a linear rate of 0.44% d−1 during the first half of the grain‐filling period, whereas the rate was 1.87% d−1 during the second half of the grain‐filling period. Rates of leaf senescence were 3.4 and 2.1 times greater in the older hybrid than in the newer hybrids during the first and second half of the grain‐filling period, respectively. During the first half of the grain‐filling period, leaf senescence increased from the medium to the highest plant population density, whereas rates of senescence during the second half of the grain‐filling period declined with an increase in plant population density for the older hybrid and rates were lowest at the medium plant population density for the newer hybrids. A top–bottom profile of leaf senescence was observed during the second half of the grain‐filling period, with leaves in the central section of the canopy being the last leaves to senesce, and this phenomenon was more marked in the newer hybrids.
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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) | 0.000 | 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".