The Functional Anatomy of Rice Leaves: Implications for Refixation of Photorespiratory CO2 and Efforts to Engineer C4 Photosynthesis into Rice
Bibliographic record
Abstract
One mechanism to enhance global food stocks radically is to introduce C4 photosynthesis into C3 crops from warm climates, notably rice. To accomplish this, an understanding of leaf structure and function is essential. The chlorenchyma structure of rice and related warm-climate C3 grasses is distinct from that of cool temperate C3 grasses. In temperate C3 grasses, vacuoles occupy the majority of the cell, while chloroplasts, peroxisomes and mitochondria are pressed against the cell periphery. In rice, 66% of protoplast volume is occupied by chloroplasts, and chloroplasts/stromules cover >95% of the cell periphery. Mitochondria and peroxisomes occur in the cell interior and are intimately associated with chloroplasts/stromules. We hypothesize that the chlorenchyma architecture of rice enhances diffusive CO(2) conductance and maximizes scavenging of photorespired CO2. The extensive chloroplast/stromule sheath forces photorespired CO(2) to exit cells via the stroma, where it can be refixed by Rubisco. Deep cell lobing and small cell size, coupled with chloroplast sheaths, creates high surface area exposure of stroma to intercellular spaces, thereby enhancing mesophyll transfer conductance. In support of this, rice exhibits higher mesophyll transfer conductance, greater stromal CO2 content, lower CO2 compensation points at warm temperature and less oxygen sensitivity of photosynthesis than cool temperate grasses. Rice vein length per leaf, mesophyll thickness and intercellular space volume are intermediate between those of most C3 and C4 grasses, indicating that the introduction of Kranz anatomy into rice may not require radical changes in leaf anatomy; however, deep lobing of chlorenchyma cells may constrain efforts to engineer C4 photosynthesis into rice.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".