Alleviation of Drought Stress and Metabolic Changes in Timothy (Phleum pratense L.) Colonized with Bacillus subtilis B26
Bibliographic record
Abstract
Drought is a major limiting factor of crop productivity worldwide and its incidence is predicted to increase under climate change. Drought adaptation of cool-season grasses is thus a major challenge to secure the agricultural productivity under current and future climate conditions. Endophytes are non-pathogenic plant-associated bacteria that can play an important role in conferring resistance and improving plant tolerance to drought. In this study, the effect of inoculation of the bacterial endophyte Bacillus subtilis strain B26 on growth, water status, photosynthetic activity and metabolism of timothy (Phleum pratense L.) subjected to drought stress was investigated under controlled conditions. Under both drought-stress and non-stressed conditions, strain B26 successfully colonized the internal tissues of timothy and had a positive impact on plant growth. Exposure of inoculated plant to a 8-week drought-stress led to significant increase in shoot and root biomass by 26.6 and 63.8%, and in photosynthesis and stomatal conductance by 55.2 and 214.9% respectively, compared to non-inoculated plants grown under similar conditions. There was a significant effect of the endophyte on plant metabolism; higher levels of several sugars, notably sucrose and fructans and an increase of key amino acids such as, asparagine, glutamic acid and glutamine were recorded in shoots and roots of colonized plants compared to non-colonized ones. The accumulation of the non-protein amino acid GABA in shoots of stressed plants and in roots of stressed and unstressed plants was increased in the presence of the endophyte. Taken together, our results indicate that B. subtilis B26 improves timothy growth under drought stress through the modification of osmolyte accumulation in roots and shoots. These results will contribute to the development of a microbial agent to improve the yield of grass species including forage crops and cereals exposed to environmental stresses.
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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 | 0.001 |
| 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".