Rhizosphere bacteria containing 1‐aminocyclopropane‐1‐carboxylate deaminase increase yield of plants grown in drying soil via both local and systemic hormone signalling
Bibliographic record
Abstract
Decreased soil water availability can stimulate production of the plant hormone ethylene and inhibit plant growth. Strategies aimed at decreasing stress ethylene evolution might attenuate its negative effects. An environmentally benign (nonchemical) method of modifying crop ethylene relations - soil inoculation with a natural root-associated bacterium Variovorax paradoxus 5C-2 (containing the enzyme 1-aminocyclopropane-1-carboxylate (ACC) deaminase that degrades the ethylene precursor ACC), was assessed with pea (Pisum sativum) plants grown in drying soil. Inoculation with V. paradoxus 5C-2, but not with a transposome mutant with massively decreased ACC deaminase activity, improved growth, yield and water-use efficiency of droughted peas. Systemic effects of V. paradoxus 5C-2 included an amplified soil drying-induced increase of xylem abscisic acid (ABA) concentration, but an attenuated soil drying-induced increase of xylem ACC concentration. A local bacterial effect was increased nodulation by symbiotic nitrogen-fixing bacteria, which prevented a drought-induced decrease in nodulation and seed nitrogen content. Successfully deploying a single bacterial gene in the rhizosphere increased yield and nutritive value of plants grown in drying soil, via both local and systemic hormone signalling. Such bacteria may provide an easily realized, economic means of sustaining crop yields and using irrigation water more efficiently in dryland agriculture.
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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".