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Influence of Certain Animal Manures on Incidence of Stem Canker and Black Scurf Disease on Potato

2012· article· en· W2317782586 on OpenAlexvenueno aff
Heidi I.G. Abo-Elnaga, Mansour M. El-Fawy, A. M. Amein

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsCankerRhizoctonia solaniBiologySowingGerminationManureHorticultureAgronomyMyceliumStem rotGreen manureSeed treatmentDry rot

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.235
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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