Elevated efficiency of C<sub>3</sub> photosynthesis in bamboo grasses: A possible consequence of enhanced refixation of photorespired CO<sub>2</sub>
Bibliographic record
Abstract
Abstract Bamboos are productive grasses that currently yield a high‐quality wood and potentially an abundance of lignocellulose for bioenergy. All are C3 grasses of warm habitats, where they are prone to significant photorespiratory inhibition and competitive suppression by C4 grasses. Here, we investigate whether three bamboo species from the Brazilian Cerrado (Dendrocalamus asper, Guadua angustifolia, and Guadua magna) exhibit unique adaptations that suppress photorespiratory costs and enhance photosynthetic efficiency. We evaluated photosynthetic efficiency of the bamboos and rice (Oryza sativa) by measuring C*, the CO2 compensation point in the absence of mitochondrial respiration. At 25℃, C* averaged 2.81 Pa in each of the bamboo species, which is closer to a C2 plant (2.71 Pa) than the C3 plant rice (3.31 Pa). Assuming a chloroplast CO2 concentration of 200 µmol mol−1, this represents an 18% lower cost of apparent photorespiration in bamboo than rice. Light and transmission electronic microscopy of the bamboo leaves exhibited few organelles in the bundle and mestome sheath cells, and mesophyll (M) cells are deeply lobed with 99% of the cell periphery adjacent to intercellular air space covered by chloroplast and stromules. The chloroplast layer in bamboo M cells is thick, with mitochondria adjacent to or engulfed by chloroplasts. This arrangement slows CO2 efflux and facilitates refixation of photorespired CO2, which could explain the low C* in the bamboos. The bamboos also had higher water use efficiency than rice, which may reflect efficient refixation of photorespired CO2.
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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) | 0.000 | 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 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".