Application of plant growth-promoting rhizobacteria (PGPR) in combination with a mild strain of<i>Cucumber mosaic virus</i>(CMV) associated with viral satellite RNAs to enhance growth and protection against a virulent strain of CMV in tomato
Bibliographic record
Abstract
An indigenous strain of Cucumber mosaic virus (CMV) associated with a naturally occurring benign viral satellite RNA (345 bp long), referred to as CMV-KU1, although effective as a protective biocontrol agent against the damaging effects of the virulent CMV-16 strain, produced negative side-effects such as mild stunting, vigour reduction and about 20% yield loss in tomato (Solanum lycopersicon L.) plants. The efficacy of using a mixture of two plant growth-promoting rhizobacteria (PGPR) strains, Pseudomonas aeruginosa and Stenotrophomonas rhizophilia, to compensate for vegetative and yield loss caused by CMV-KU1 in tomato plants, was evaluated in greenhouse experiments. In addition to promoting plant growth, PGPRs are known to enhance systemic defences in plants against foliar pathogens such as viruses that attack tissues distant to PGPR sphere of activity. The use of PGPR and CMV-KU1 together successfully promoted vegetative growth and fruit yield in tomato plants to values equivalent to that of the healthy controls. The combination used also enhanced overall protection of the plants against the severe CMV-16 virus with about 91.3% disease prevention. Serological analysis using enzyme-linked immunosorbent assay (ELISA) also indicated a lower incidence of CMV-16 infection in protected test 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 | 0.001 |
| 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".