High-yielding rice Takanari has superior photosynthetic response to a commercial rice Koshihikari under fluctuating light
Bibliographic record
Abstract
Leaves within crop canopies experience variable light over the course of a day, which greatly affects photosynthesis and crop productivity. Little is known about the mechanisms of the photosynthetic response to fluctuating light and their genetic control. Here, we examined gas exchange, metabolite levels, and chlorophyll fluorescence during the photosynthetic induction response in an Oryza sativa indica cultivar with high yield (Takanari) and a japonica cultivar with lower yield (Koshihikari). Takanari had a faster induction response to sudden increases in light intensity than Koshihikari, as demonstrated by faster increases in net CO2 assimilation rate, stomatal conductance, and electron transport rate. In a simulated light regime that mimicked a typical summer day, the faster induction response in Takanari increased daily CO2 assimilation by 10%. The faster response of Takanari was explained in part by its maintenance of a larger pool of Calvin-Benson cycle metabolites. Together, the rapid responses of electron transport rate, metabolic flux, and stomatal conductance in Takanari contributed to the greater daily carbon gain under fluctuating light typical of natural environments.
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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".