Response of growth, photosynthetic electron transfer, and chloroplast ultrastructure to different <scp>LED</scp> light combination in green onion (<scp><i>Allium fistulosum</i></scp> L.)
Bibliographic record
Abstract
Abstract With the rapid development of facility agriculture, it has become popular to study the influences of different light qualities on the growth, material metabolism, and morphology of horticultural crops. Last several years, green onions cultivation models have undergone major changes, and facility cultivation has developed rapidly. To determine the impact of light quality on the green onions, we studied the parameters connected to photosynthesis, incorporating growth, and development, photosynthetic rate ( P n ), chlorophyll fluorescence, light response curve, photosynthetic electron transfer, and chloroplast ultrastructure. We roundly analyzed the influences of different LED light combination (white: W, white‐blue combination 3:1:WB, white‐green combination 3:1:WG, white‐yellow combination 3:1:WY, and white‐red combination 3:1:WR, light intensity: 500 ± 10 μmol photons m −2 s −1 ) on the photosynthetic performance of green onions. The WB light led to better results than those of the WR, WG, and WY. There were significant performance improvements in leaf area, plant height, stem thickness, relative growth rate (RGR), pigment content, photosynthetic capacity, photosynthetic electron transfer efficiency, and chloroplast ultrastructure integrity. In contrast, plants treated with WG and WY were exposed to appreciably blocked light, but they effectively formed a light protection mechanism. The results of this research not only provided insight into the response mechanism of crop photosynthesis to different light qualities, but they also provided a scientific foundation for better planting green onions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".