Effects of NO3--N on growth and photosynthetic characteristics of mulberry seedlings under Na_2CO_3 stress
Bibliographic record
Abstract
The present study analyzed the effects of nitrate nitrogen( NO3--N) on mulberry seedlings growth and photosynthetic characteristics under the alkaline salts( Na2CO3) stress by using solution culture method. Under Na2CO3 stress,stomatal limitation of mulberry seedlings decreased with the increase of NO3--N which improved utilization of carbon dioxide in mesophyll cells in leaves,significantly reduced damages of salt stress on mulberry seedlings,and promoted accumulation of shoot and root biomass. The NO3--N improved actual photochemical efficiency( ФPSⅡ) and electron transfer rate( ETR) of mulberry seedlings,alleviated reduction of PSⅡ photochemical efficiency( Fv/Fm),and reduced the photo inhibition degree of mulberry seedlings leaves under Na2CO3 stress.The increase in NO3--N also reduced the proportion of invalid forms of heat energy dissipation in mulberry seedling leaves under Na2CO3 stress which was useful for leaves to absorbe more lights for photochemical reaction. The synergy between the heat dissipation and xanthophyll cycle effectively protected the normal physiological function of PSⅡ and improved light utilization capacity of the leaves. The NO3--N concentration of 12. 5 mmol·L- 1treatment was greater than other concentrations. Therefore,the increase in NO3--N can improve leaves light use efficiency and biomass of mulberry seedling under Na2CO3 stress.
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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".