(430) Leaf Gas Exchange of Carrots in Response to Increasing Leaf Temperatures
Bibliographic record
Abstract
Increasing temperature as a result of global climate change is expected to exert a great influence on agricultural crops, possibly through effects on photosynthesis. Response to temperature of leaf gas exchange parameters of carrot ( Daucus carota L. var. sativus ) cultivars Cascade, Carson, Oranza, and Red Core Chantenay (RCC) were examined in a controlled growth room experiment. Leaf net photosynthetic rate (P N ), stomatal conductance (g s ), and transpiration rate (E) were measured at temperatures ranging from 15 to 35 °C at 370 μmol·mol -1 (CO 2 ) and 450±20 μmol·m -2 ·s -1 PAR. The cultivars responded similarly to increasing temperature and did not differ in most photosynthetic parameters except g s . The P N increased between 20 and 30 °C, thereafter increasing only slightly to 35 °C. On average, increasing temperature from 20 to 30 °C increased P N by 69%. Carboxylation efficiencies (Ca/Ci ratio) ranged from 1.12–2.33 mmol·mol -1 while maximum P N were 3.25, 3.90, 5.49, 4.19 μmol·m -2 ·s -1 for Carson, RCC, Cascade, and Oranza, respectively. The E did not reach maximum at 35 °C while g s peaked at 30 °C and then decreased by 93% at 35 °C. The water use efficiency (WUE) decreased with an increase in temperature due to increases in both P N and E. The results indicate that increasing temperatures above the seasonal average (<20 °C) increases both P N and E up to 30–35 °C. An increase in photosynthesis due to an increase in temperature is expected to hasten growth. Carrots may be able to withstand a moderate increase in temperature.
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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) | 0.001 | 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".