Mitigation of drought or a combination of heat and drought stress effects on canola by Thuricin 17, a PGPR-produced compound
Bibliographic record
Abstract
Plant growth-promoting microorganisms (PGPMs) and the specific compounds they produce have the capacity to mitigate the adverse effects of stressors on plants. An example in this regard is Thuricin 17 (Th17), a signal molecule produced by Bacillus thuringiensis NEB17 (Bt NEB17), a plant growth-promoting rhizobacterium. In this study, we aimed to determine the efficacy of Th17 in mitigating drought and the combination of drought and heat stress in canola [Brassica napus (L.)]. Two of the best Th17 concentrations, 10−9 (Th1) M and 10−11 (Th2) M, were used either as seed treatment plus root drenching or foliar spray. Leaf area and biomass accumulation was increased by both application methods of Th1 under moderate and severe drought stress, whereas more promising results were seen from Th2-treated plants under the combination of stressors. Additionally, root length, root surface, and root volume were increased by 21%, 22%, and 23%, respectively, for plants grown from Th1 seed treatment plus root drenching compared to controls under severe drought conditions. Moreover, SOD, POD, and CAT contents were increased by spraying Th1 and Th2 under individual stresses and the combination of heat and drought, respectively. Accordingly, increases in physiological variables were observed for sprayed plants, which also had higher antioxidant contents. These results indicated that plant responses to the compound varied with concentration of Th17 and plant growth conditions. Specifically, when plants were grown under an individual stress condition, either drought or heat, the higher level of Th17 was more effective, whereas the lower dose demonstrated higher positive impacts under the combination of heat and drought. Regarding application method, both seed treatment plus root drenching and foliar spray had the ability to assist plants in alleviating stresses through growth stimulatory mechanisms. Therefore, Th17 has potential to become an environmentally friendly biostimulant, particularly under stressful environmental conditions.
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) | 0.000 | 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".