Biotic stress alleviation: A sneak peek into the beneficial taxa in rhizosphere
Bibliographic record
Abstract
Biotic stress is a known cause of considerable agricultural loss, and reducing this loss is crucial for enhancing crop productivity and achieving global food security. Although plants are sessile, they have well-equipped beneficial microbial neighbors in the rhizosphere that can be shaped and recruited to meet their needs, especially during periods of stress. Multiple factors stimulate shifts within beneficial microbes, especially the most malleable bacterial groups, to favour their host, and numerous studies have revealed how biotic stress strongly alters the rhizosphere taxa of plants to predominantly Proteobacteria, Firmicutes and Actinomycetes. To this end, the Actinomycetes-members of these bacterial taxa have been applied as beneficial bioinoculants to control diseases in plants with a dearth utilization of their metabolites (including antibiotics) as chemo-control agents against phytopathogens. Therefore, this review examines how biotic stress shapes key bacterial taxa in the rhizosphere and highlights the potential of Actinomycetes-derived antibiotics and other metabolites to mitigate biotic stress through direct antagonism of pathogens as well as inducing plant defense. This chemo-control approach could potentially replace synthetic chemicals in mitigating biotic stress for crop productivity. • Biotic stress alleviation is crucial to achieving food security. • This stress causes a paradigm shift in the rhizosphere microbiome to beneficial taxa that could ensure host resilience. • A member of the taxa is known to be a prolific antibiotic and other metabolite producer for plant sustainability. • These metabolites could be candidate compounds for alleviating biotic stress through chemocontrol.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".