Effects of nitrogen on photosynthetic characteristics of leaves from two different stay-green corn (<i>Zea mays</i> L.) varieties at the grain-filling stage
Bibliographic record
Abstract
Li, G., Zhang, Z.-S., Gao, H.-Y., Liu, P., Dong, S.-T., Zhang, J.-W. and Zhao, B. 2012. Effects of nitrogen on photosynthetic characteristics of leaves from two different stay-green corn ( Zea mays L.) varieties at the grain-filling stage. Can. J. Plant Sci. 92: 671–680. The effects of nitrogen on the photosynthetic characteristics of two different stay-green corn (Zea mays L.) at the grain-filling stage were studied. Using a stay-green inbred line (Q319) and a non-stay-green inbred line (HZ4) as materials, using fast chlorophyll fluorescence-induction kinetics and 820 nm light-absorption curves, we analyzed the influences of nitrogen supplementation on photosystem I (PS I) and photosystem II (PS II). The results show that nitrogen fertilization has significant effects on promoting the net photosynthetic rate (P n ) in leaves at the grain-filling stage and on single-plant grain yield at the harvest stage (P<0.05) in Q319, whereas there is no significant effect in HZ4. Analyses performed using JIP-Test showed that nitrogen fertilization significantly increased electron donor and acceptor performance in the reaction center of PS II (P<0.05). The increased performance of the electron transport chain at a point after the electron acceptor in the PS II reaction center was greater in Q319 than in HZ4, reducing excessive excitation energy production in PS II and significantly improving the coordination between PS II and PS I. Although the performance of the electron transport chain after the electron acceptor in the PS II reaction center was increased in HZ4, the increase was not substantial enough to improve the coordination between PS II and PS I; therefore, P n and grain yield were still significantly lower than those of Q319.
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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 | 0.001 | 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 | 0.001 | 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".