Minimum Daily Respiration of Maize: Relationship to Total Daily Respiratory Carbon Loss, and Effects of Growth Stage and Temperature
Bibliographic record
Abstract
ABSTRACT Since crop respiration can only be measured in darkness, estimating total daily crop respiration (Rt) requires knowledge of the quantitative relationship between daytime and nighttime respiration, including the predicted effect of temperature. We measured minimum daily (early morning) respiration (Rmin) in maize (Zea mays L.) at four different temperatures during the night and at four different growth stages to estimate the respiration response to temperature. In a field experiment, respiration was measured every 2 to 5 h over a 24‐h period at five different growth stages to explore the relationship between Rt and Rmin. The fractional rate change with 10°C temperature increment (Q10) decreased as the temperature increased. A single function was proposed to describe the respiration response to temperature across all growth stages. The minimum respiration of the day was reached between midnight and 6:00 AM, and Rmin represented 89 to 57% of Rt. Modeling maize respiration assuming a constant Q10 is inadvisable, since Q10 varies with temperature. There was no effect of growth stage on Q10 until 26°C; above this temperature, respiration increased only in older plants. The Rt increased over the season as biomass accumulated, but the ratio of Rmin/Rt reached its highest value at silking.
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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 | 0.001 |
| 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".