Responses of group and individual leaf photosynthetic characteristics of two summer maize (<i>Zea mays</i>L.) to leaf removal under high plant density
Bibliographic record
Abstract
Liu, T.-N., Gu, L.-M., Xu, C.-L. and Dong, S.-T. 2014. Responses of group and individual leaf photosynthetic characteristics of two summer maize (Zea mays L.) to leaf removal under high plant density. Can. J. Plant Sci. 94: 1449–1459. The present experiment was conducted during the growing seasons of 2012 and 2013 using two summer maize (Zea mays L.) cultivars, Zhengdan958 (a compact cultivar) and Jinhai5 (a semi-compact cultivar) grown at a plant density of 105 000 plants ha −1 , to evaluate the influence of leaf removal on canopy apparent photosynthesis (CAP), individual leaf photosynthetic characteristics and grain yield. Plants were subjected to the removal of two (S1), four (S2) or six leaves (S3) from the top of the plant 3 d after anthesis (DAA), with no leaf removal as control (S0). The results of 2 yr indicated that with increased intensity of leaf removal, the transmission of light to lower strata of the canopy increased. With the removal of two leaves (S1), CAP increased and longer durations of CAP and green leaf are index were maintained during grain filling, whereas CAP in S2 and S3 treatments was inhibited and drastically declined. Generally, leaf removal appeared to stimulate an increase in the net photosynthetic rate (P N ), stomatal conductance (g s ) and chlorophyll content of the remaining ear leaves in S2 and S3 treatments prior to 26 DAA. Nevertheless, thereafter, plants in the S1 treatment had an advantage in terms of individual photosynthetic capacity. These results indicate that excising two leaves made plants more tolerant of high plant density due to enhanced photosynthetic capacity in ear leaves as well as a more efficient canopy structure, resulting in a better coordination of groups and individuals, and finally achieved significantly higher grain yield. In addition, relative to Zhengdan958, the effects of leaf removal on Jinhai5 were more apparent.
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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 | 0.001 |
| 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".