Enhanced anti-herbivore defense of tomato plants against Spodoptera litura by their rhizosphere bacteria
Bibliographic record
Abstract
BACKGROUND: The use of beneficial microorganisms as an alternative for pest control has gained increasing attention. The objective of this study was to screen beneficial rhizosphere bacteria with the ability to enhance tomato anti-herbivore resistance. RESULTS: Rhizosphere bacteria in tomato field from Fuqing, one of the four locations where rhizosphere bacteria were collected in Fujian, China, enhanced tomato resistance against the tobacco cutworm Spodoptera litura, an important polyphagous pest. Inoculation with the isolate T6-4 obtained from the rhizosphere of tomato field in Fuqing reduced leaf damage and weight gain of S. litura larvae fed on the leaves of inoculated tomato plants by 27% in relative to control. Analysis of 16S rRNA gene sequence identities indicated that the isolate T6-4 was closely related to Stenotrophomonas rhizophila supported with 99.37% sequence similarity. In the presence of S. litura infestation, inoculation with the bacterium led to increases by a 66.9% increase in protease inhibitor activity, 53% in peroxidase activity and 80% in polyphenol oxidase activity in the leaves of inoculated plants as compared to the un-inoculated control. Moreover, the expression levels of defense-related genes encoding allene oxide cyclase (AOC), allene oxide synthase (AOS), lipoxygenase D (LOXD) and proteinase inhibitor (PI-II) in tomato leaves were induced 2.2-, 1.7-, 1.4- and 2.7-fold, respectively by T6-4 inoculation. CONCLUSION: These results showed that the tomato rhizosphere soils harbor beneficial bacteria that can systemically induce jasmonate-dependent anti-herbivore resistance in tomato plants.
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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) | 0.001 | 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 | 0.000 |
| 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".