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Record W2073650773 · doi:10.1094/pdis-94-5-0504

Interaction of<i>Rhizoctonia solani</i>and<i>Rhizopus stolonifer</i>Causing Root Rot of Sugar Beet

2010· article· en· W2073650773 on OpenAlexfundno aff
Linda E. Hanson

Bibliographic record

VenuePlant Disease · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
FundersReseau canadien de recherche respiratoire
KeywordsRoot rotRhizoctoniaRhizoctonia solaniSugar beetBiologyCrown (dentistry)AgronomyRhizopusHorticultureSugarInoculationFermentationMedicine

Abstract

fetched live from OpenAlex

In recent years, growers in Michigan and other sugar beet (Beta vulgaris) production areas of the United States have reported increasing incidence of root rot with little or no crown or foliar symptoms in sugar beet with Rhizoctonia crown and root rot. In addition, Rhizoctonia-resistant beets have been reported with higher levels of disease than expected. In examining beets with Rhizoctonia root rot in Michigan, over 50% of sampled roots had a second potential root rot pathogen, Rhizopus stolonifer. Growing conditions generally were not conducive to disease production by this pathogen alone, so we investigated the potential for interaction between these two pathogens. In greenhouse tests, four of five sugar beet varieties had more severe root rot symptoms when inoculated with both pathogens than when inoculated with either pathogen alone. This synergism occurred under conditions that were not conducive to disease production by R. stolonifer. Host resistance to Rhizoctonia crown and root rot reduced diseases severity, but was insufficient to control the disease when both pathogens were present. This raises concerns about correct disease diagnosis and management practices and indicates that a root rot complex may be important on sugar beet in Michigan.

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)0.000
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 score0.835
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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