A Bacterial Consortium and Synthetic Fertilizer Based Biocontrol Approach Against Potato Rot Disease “Neocosmospora rubicola”
Bibliographic record
Abstract
Conventional management of stem rot disease of potato, caused by Neocosmospora rubicola, through fungicide application is an environmentally unfavorable practice that calls for an alternative biocontrol approach. Plant growth-promoting bacteria (PGPB) are known to not only promote plant growth but also control diseases caused by various fungi. The study was designed to evaluate the potential of three strains of PGPB and synthetic fertilizer to manage stem rot of potatoes. In the first experiment, PGPB strains Azotobacter chroococcum, Azospirillum lipoferum, and Pseudomonas putida and their combinations were evaluated on PDA medium against N. rubicola using the dual culture technique. All three bacterial strains were found effective in reducing the radial growth of the fungus maximum up to 91%. In the second experiment, in the presence of half and full recommended doses of fertilizer nitrogen (N) and phosphorus (P), the potato growing medium was inoculated with N. rubicola alone, and with combinations of N. rubicola and PGPB strains (bacterial formulation; BF). N. rubicola increased stem and tuber rot, and decreased tuber weight by 11% compared to the control. On the other hand, sole inoculation with BF significantly increased tuber weight. In addition, a combined inoculation of N. rubicola and BF, or N. rubicola inoculation a week prior to BF inoculation did not affect tuber weight compared to control. However, inoculation of BF a week prior to N. rubicola, controlled rot symptoms and increased tuber weight by 32%. An increase in P application favored the PGPB strains in controlling rot in tubers. The interaction effect of fertilizer N with the inoculation combinations was non-significant; however, the main impact of N was to increase rot in tubers and decrease in potato stems. Hence a prerequisite application of PGPB formulation proved to be an effective tool against N. rubicola infestation in potatoes.
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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".