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Record W2012674628 · doi:10.2135/cropsci2005.0371

Identification, Mapping, and Economic Evaluation of QTLs Encoding Root Maggot Resistance in <i>Brassica</i>

2005· article· en· W2012674628 on OpenAlexaffabout
U. Ekuere, Lloyd M. Dosdall, Melissa J. Hills, B. A. Keddie, L. S. Kott, Allen G. Good

Bibliographic record

VenueCrop Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversity of GuelphUniversity of Alberta
Fundersnot available
KeywordsBiologyBrassicaIdentification (biology)Resistance (ecology)Root (linguistics)MaggotQuantitative trait locusBotanyGeneticsAgronomyGene

Abstract

fetched live from OpenAlex

Commercial varieties of canola ( Brassica napus L. and B rapa L.) are susceptible to infestations by the root maggots Delia radicum (L.) and Delia floralis (Fallén) (Diptera: Anthomyiidae) in western Canada. Although cultural strategies can ameliorate crop damage from root maggot infestations, these methods are not sufficiently effective to prevent substantial economic losses. In this paper we report the development of germplasm for resistance to root maggot infestations and the introgression of genes from a resistant relative ( Sinapis alba L.) to susceptible B napus The effectiveness of the conferred resistance to root maggot damage was validated by comparing different genotypes for pest damage and yield loss with and without insecticide applications. Yield of B napus plants, susceptible to root maggot infestations, increased when insecticide was applied (by up to 24%), but no significant yield differences were observed among resistant intergeneric hybrids that were treated or not treated with insecticide. One hundred and thirty‐five restriction fragment length polymorphisms (RFLPs) were used to construct a B. napus genetic linkage map and to identify quantitative trait loci (QTLs) associated with resistance to root maggot damage. Two QTLs, RM‐G8 and RM‐G4, were found to be associated with resistance to root maggot damage. Together, these two QTLs explain 54.6% of the total variation observed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.222

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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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

Citations21
Published2005
Admission routes2
Has abstractyes

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