Photoperiod regulates elicitation of growth promotion but not induced resistance by plant growth-promoting rhizobacteria
Bibliographic record
Abstract
For several years, we have noticed that plant growth-promoting rhizobacteria (PGPR), which consistently promote plant growth in greenhouse tests during spring, summer, and fall, fail to elicit plant growth promotion during the midwinter under ambient light conditions. This report tests the hypothesis that photoperiod regulates elicitation of growth promotion and induced systemic resistance (ISR) by PGPR. A commercially available formulation of PGPR strains Bacillus subtilis GB03 and Bacillus amyloliquefaciens IN937a (BioYield) was used to grow tomato and pepper transplants under short-day (8 h of light) (SD) and long-day (12 h of light) (LD) conditions. Results of many experiments indicated that under LD conditions, BioYield consistently elicited significant increases in root and shoot mass as well as in several parameters of root architecture. However, under SD conditions, such increases were not elicited. Differential root colonization of plants grown under LD and SD conditions and changes in leachate quality partially account for these results. BioYield elicited ISR in tomato and pepper under both LD and SD conditions, indicating that although growth promotion was not elicited under SD conditions, induced resistance was. Overall, the results indicate that PGPR-mediated growth promotion is regulated by photoperiod, while ISR is not.
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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".