Response of Leaf Photosynthesis during the Grain‐Filling Period of Maize to Duration of Cold Exposure, Acclimation, and Incident PPFD
Bibliographic record
Abstract
Maize (Zea mays L.) leaf photosynthesis during the grain‐filling period is affected by low (≈4°C) night temperatures. Three factors that are potentially involved in this phenomenon were examined: (i) duration of cold exposure, (ii) acclimation prior to exposure to light, and (iii) level of incident photosynthetic photon flux density (PPFD) following cold exposure. Studies were carried out with plants grown hydroponically under both field and controlled‐environment conditions. Three hybrids (‘Pride 5’, ‘Pioneer 3902’, and ‘Cargill 1877’) were used in the field experiments and Pioneer 3902 was used in controlled‐environment experiments. Plants were exposed to 4°C in the dark for either 2 or 16 h and, subsequently, acclimated for either 0 or 1 h in the dark before exposure to high PPFD. Four incident PPFD levels (400, 650, 1200, and 2000 μmol m−2 s−1) after cold exposure were examined. Both duration of cold exposure and acclimation after cold exposure affected the reduction in leaf carbon exchange rate (CER). Leaf CER was reduced by 18.0% after a 2‐h exposure and by 30.4% after a 16‐h exposure to 4°C, and leaf CER was reduced by 20.4 and 28.0% for 1‐ and 0‐h acclimation, respectively. Dark‐adapted Fv/Fm (Fv = variable fluorescence; Fm = maximum chlorophyll fluorescence), that is, maximum quantum efficiency of Photosystem II, was 0.71 after cold exposure during the night compared with 0.81 for the control. The Fv/Fm was affected by duration of cold exposure (0.74 and 0.68 for 2‐ and 16‐h exposure, respectively) but not by acclimation. Reduction in leaf photosynthesis after cold exposure was linearly related to the incident PPFD level. Results support the contention that the reduction in CER due to low night temperature is not associated with photoinhibition.
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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 | 0.001 |
| 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".