Isolation, characterization, and formulation of antagonistic bacteria for the management of seedlings damping-off and root rot disease of cucumber
Bibliographic record
Abstract
Antagonistic bacteria are common soil inhabitants with potential to be developed into biofungicides for the management of seedling damping-off, root rot, and other soil-borne diseases of various crops. In this study, antagonistic bacteria were isolated from a commercial potato field and screened for their growth inhibition of fungal and oomycete pathogens in laboratory tests. The biocontrol potential of the 3 most effective antagonistic bacteria from the in vitro tests was evaluated against seedling damping-off and root rot of cucumber caused by Pythium ultimum. Based on phenotypic characteristics, biochemical tests, and sequence analysis of 16S-23S rDNA gene, the 3 antagonistic bacteria were identified as Pseudomonas fluorescens (isolate 9A-14), Pseudomonas sp. (isolate 8D-45), and Bacillus subtilis (isolate 8B-1). All 3 bacteria promoted plant growth and suppressed Pythium damping-off and root rot of cucumber seedlings in growth-room assays. Both pre- and post-planting application of these bacteria to an infested peat mix significantly increased plant fresh masses by 113%-184% and percentage of healthy seedlings by 100%-290%, and decreased damping-off and root rot severity by 27%-50%. The peat and talc formulations of these antagonistic bacteria applied as seed or amendment treatments to the infested peat mix effectively controlled Pythium damping-off and root rot of cucumber seedlings and enhanced plant growth. The survival of all 3 antagonistic bacteria in peat and talc formulations decreased over time at room temperature, but the populations remained above 10(8) CFU/g during the 180-day storage period. The peat formulation of a mixture of 3 bacteria was the best seed treatment, significantly increasing the plant fresh masses by 245% as compared with the Pythium control, and by 61.4% as compared with the noninfested control. This study suggests that the indigenous bacteria from agricultural soils can be developed and formulated as biofungicides for minimizing the early crop losses caused by seedling damping-off and root rot diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".