Stability of grain yield and leaf photosynthesis in maize
Bibliographic record
Abstract
Genetic yield improvement in maize during the past 7 decades has been associated with increased stress tolerance that has resulted in enhanced yield stability and in the capacity of plants to sustain high leaf photosynthetic rates during the grain-filling period. The objective of this study was to examine possible relationships between the response of leaf carbon exchange rate (CER) during the grain-filling period to low-night temperature and grain-yield stability by identifying quantitative trait loci (QTLs) in a mapping population. During 2004 and 2005, studies on the effect low night temperature on leaf CER were carried out in a field hydroponic system at the Arlkell Research station and yield trials were established at three locations in Ontario. First, three QTLs relating to leaf photosynthesis and five QTLs for grain yield were detected, however, QTLs for tolerance of leaf CER during the grain-filling period to low night temperature were not associated with grain-yield QTLs. Second, significant genotype * environment interactions were apparent for both leaf CER during the grain-filling period and grain yield in the mapping population.
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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".