ACC deaminase in plant growth-promoting bacteria (PGPB): An efficient mechanism to counter salt stress in crops
Bibliographic record
Abstract
Salinity in agricultural soil is a major problem around the world, with negative consequences for the growth and production of a wide range of crops. To counteract these harmful effects, plants sometimes have bacterial partners that contain the enzyme 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, which acts by degrading ACC (the precursor of ethylene in all higher plants). The enzymatic activity of ACC deaminase results in the production of α-ketobutyrate and ammonia, which, by lowering ACC levels, prevents excessive increases in the synthesis of ethylene under various stress conditions and is one of the most efficient mechanisms to induce plant tolerance to salt stress. In the present review, recent works on the role of ACC deaminase are discussed alongside its importance in promoting plant growth under conditions of salt stress in endophytic and rhizospheric bacteria, with some emphasis on Bacillus species. In addition, the toxic effects of soil salinity on plants and microbial biodiversity are analysed. Recent findings on the synergetic functioning of ACC deaminase and other bacterial mechanisms of salt stress tolerance, such as trehalose accumulation, are also summarized. Finally, we discuss the various advantages of ACC deaminase-producing bacilli as bioinoculants to address the problem of salinity in agricultural soils.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".