The Response of Leaf Photosynthesis and Dry Matter Accumulation to Nitrogen Supply in an Older and a Newer Maize Hybrid
Bibliographic record
Abstract
Nitrogen use efficiency is higher in newer than in older maize (Zea mays L.) hybrids, but the physiological mechanisms underlying differences in N‐use efficiency are unknown. The objective of this study was to quantify differences between an older and a newer maize hybrid in their response to N availability throughout the life cycle at both the leaf and the whole‐plant level. An older and a newer maize hybrid were grown in a field hydroponic system located near Guelph, ON, in 2005 at a high and a low N level. Leaf carbon exchange rate (CER), chlorophyll index, and the thylakoid electron transport rate (ETR) were measured weekly from 2 wk presilking to 8 wk postsilking. Plant‐component dry matter and N content were determined from 1 wk presilking to maturity. At the leaf level, leaf CER declined during the grain‐filling period, and the decline was greater under low than high N availability. The decline in leaf CER during the grain‐filling period was less in the newer than in the older hybrid under both high and low N availability, and differences in leaf CER were associated most strongly with a reduction in leaf CER per unit absorbed photosynthetic photon flux density. At the whole‐plant level, reduction in grain yield in low vs. high N was greater in the older than in the newer hybrid. The hybrid × N interaction for grain yield was attributable predominantly to a greater decline in the proportion of dry matter allocated to the grain in the older hybrid.
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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".