Photosynthetic responses of muskmelon (<i>Cucumis melo</i> L.) to photon flux density, leaf temperature and CO<sub>2</sub> concentration
Bibliographic record
Abstract
Two cultivars (Huanghemi and Elizabeth) of muskmelon (Cucumis melo L.) were evaluated to determine the effect of photon flux density (PFD), leaf temperature, and CO,2 concentration on the net photosynthetic rate (Pn). The cultivars were evaluated under open field and solar-heated greenhouse conditions in northwest China. The Pn increased as the PFD increased, and then the rate of increase in Pn declined for Huanghemi and decreased for Elizabeth. Elizabeth registered 22 µmol m-2 s-1 for light compensation and 1127 µmol m-2 s-1 for light saturation, which, respectively, were 50 and 70% of those required by Huanghemi. The Pn increased with increasing leaf temperatures in the range of 9.8 to 50.8°C. The optimum temperature for photosynthesis was 35.3°C for muskmelon grown in open field, 2.4°C (7%) greater than that for muskmelon grown in the greenhouse. At optimal temperatures, the field-grown muskmelon had the Pn of 19.8 µmol m-2 s-1, 30% greater than that for the greenhouse-grown muskmelon. Both cultivars responded positively to CO2 concentrations of below the CO2 saturation points, whereas Huanghemi exhibited greater (51%) Pn and higher (49%) carboxylation efficiency than Elizabeth at optimal CO2 level. The two cultivars exhibited greater photosynthesis in open field than when grown in solar-heated greenhouses, while Elizabeth performed better than Huanghemi when light conditions were poor. Selective use of cultivars with low requirements for light and temperatures will enhance the photosynthesis and productivity of muskmelon grown in solar-heated greenhouses of northwest China. Key words: Light compensation, light saturation, photon flux density, transpiration
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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".