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Comparison of Screening Methods for Resistance to <i>Fusarium</i> Root Rot in Common Beans (<i>Phaseolus vulgaris</i> L.)

2006· article· en· W2063031851 on OpenAlexafffund
S. Chaudhary, Terry Anderson, S. J. Park, Kangfu Yu

Bibliographic record

VenueJournal of Phytopathology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsRoot rotPhaseolusBiologyFusarium solaniFusariumHorticultureHypocotylBotanyAgronomy

Abstract

fetched live from OpenAlex

Abstract Root rot, caused by Fusarium solani f. sp. phaseoli , is one of the main root diseases impacting production of common beans throughout the world. Because resistance of common beans to root rot is a quantitative trait that is strongly influenced by environmental factors, reproducible methods to screen bean plants for resistance to root rot are critical to the selection process. In this study, we adapted the inoculum layer method (ILM) developed for screening soybeans for resistance to Phytophthora rot and compared it with the traditional liquid inoculum method (LIM) for screening common beans for resistance to Fusarium root rot. In addition, two methods of evaluating resistance using the ILM were compared. The most significant Pearson correlation coefficient between trials involving 80 recombinant inbred lines was achieved with the ILM and counting discoloured vascular bundles in the lower stem ( r p = 0.7113***) compared to rating the discoloration on root and hypocotyl ( r p = 0.5555***). The traditional (LIM) screening method and rating the discolouration on roots resulted in a non‐significant correlation between trials ( r p = 0.1084).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.358
Teacher spread0.339 · 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 designBench or experimental
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

Citations19
Published2006
Admission routes2
Has abstractyes

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