Influence of Certain Animal Manures on Incidence of Stem Canker and Black Scurf Disease on Potato
Bibliographic record
Abstract
Rhizoctonia solani (Kuhn) is the causal pathogen of stem canker and black scurf disease on potato. Under open greenhouse conditions two isolates of R. solani (AG-3) were used to infect Nicola potato cultivar and caused typical symptoms of stem canker and black scurf disease with different disease severities ranged from strong to weak. In vitro Addition of chickens, pigeons and cows manure extracts to the media at different concentrations 0-50% (vol/vol) reduced the growth of the tested isolates of the pathogen. The highest reduction of mycelial growth of the pathogen isolates was obtained when pigeons manure extract was added to the growing media at a concentration of 50 % (vol/vol) followed by another concentrations. Under open greenhouse conditions during two growing seasons 2010 and 2011 addition of manures to the soil at 0.5 and 1% weight of the soil before sowing significantly decreased incidence of stem canker and black scurf disease. Generally, cow manure showed the highest effect on controlling the disease followed by pigeons and chickens. On the other hand, concentration 1 % of all manures was more effective on the reducing of disease incidence than the concentration 0.5 %. On the other hand, cow manure was more effective in increasing the eyes germination followed by pigeons and chicken manure and decreased the dead of sprouts, stem canker and black scurf. Treatment with all the kinds of tested manures increased eyes germination of tubers and reduced sclerotia formation on the surface of tubers and hence disease incidence.
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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 | 0.001 |
| 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 | 0.001 | 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".