Impact of elevated CO<sub>2</sub> on carbohydrate and ureide concentrations in soybean inoculated with different strains of <i>Bradyrhizobium japonicum</i>
Bibliographic record
Abstract
Elevated CO2 increases soybean growth and photosynthesis, and the resulting additional supply of photosynthates stimulates nodule activity. To characterize its biochemical response to both CO2 and bradyrhizobial strains, soybean inoculated with three strains of Bradyrhizobium japonicum was grown in growth chambers under ambient (400 µmol·mol–1) or elevated (800 µmol·mol–1) CO2. Soluble sugars were generally more abundant in leaves and nodules under elevated CO2, while starch and pinitol were depleted, indicating that additional photosynthates were rapidly used, in particular for nodule growth (dry mass increased by 65%). Ureides (allantoin and allantoic acid) increased under elevated CO2 in leaves, while this increase was not significant in nodules. The indigenous strain 12NS14 induced the highest ureides concentration in nodules under elevated CO2 along with the highest nitrogenase activity and increase in shoot dry mass, indicating a positive-feedback stimulation: soybean mobilized energy reserves to support more nodules, and in return nodules synthesized more ureides to support plant growth. In contrast, the commercial strain 532c resulted in the highest ureide concentrations in leaves, coupled with the lowest nitrogenase activity and nodules yield, suggesting a feedback inhibition of nodule activity. Our results show that selection of B. japonicum strains better adapted to elevated CO2 could improve soybean performance.
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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) | 0.001 | 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 | 0.001 |
| 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".