Genetic Variation in Physiological Discriminators for Cold Tolerance—Early Autotrophic Phase of Maize Development
Bibliographic record
Abstract
ABSTRACT Earlier spring planting to maximize the duration of the growing season has increased the importance of early‐season cold tolerance in maize (Zea mays L.). The objectives of this study were to assess the response of several physiological parameters associated with cold tolerance in maize during early autotrophic development and to quantify variability in the response to cold stress among 49 maize inbred lines. At the 7‐leaf tip stage, maize inbred lines were subjected to two day/night temperature regime treatments, 25/15°C (control) and 15/3°C (cold). Carbon exchange rate (CER), leaf chlorophyll content, quantum efficiency of Photosystem II, leaf conductance, dry weight, root/shoot ratio, and rate of development were measured at the 8‐leaf tip stage for genotypes under both treatments. The cold treatment effects were significant for all parameters except root/shoot ratio. Genetic diversity for most traits investigated was observed for the response of the inbred lines to cold stress. Results of this study show that leaf CER and rate of development are good discriminators of cold tolerance during early phases of development.
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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 | 0.001 | 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) | 0.001 | 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".