MétaCan
Menu
Back to cohort
Record W2086370812 · doi:10.1094/pdis.2003.87.12.1522

Genetic Analysis of Adult-Plant Resistance to Leaf Rust in Five Spring Wheat Genotypes

2003· article· en· W2086370812 on OpenAlexaff
Alireza Navabi, Ravi P. Singh, J. P. Tewari, K. G. Briggs

Bibliographic record

VenuePlant Disease · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDiallel crossBiologyHeritabilityRust (programming language)Transgressive segregationResistance (ecology)AgronomyGenotypeGenetic analysisPoaceaeHorticultureBotanyGeneQuantitative trait locusGeneticsHybrid

Abstract

fetched live from OpenAlex

Inheritance of adult-plant resistance to leaf rust, caused by Puccinia triticina, was studied in the progeny of a one-way diallel cross involving five CIMMYT-derived adult-plant resistant wheat (Triticum aestivum) genotypes and a susceptible wheat ‘Avocet-YrA’. F 1 progenies, F 2 populations, F 2 -derived F 3 , and F 4 -derived F 5 lines were field evaluated under artificial epidemics with leaf rust race MCJ/SP. Adult-plant resistance to leaf rust was incompletely dominant in crosses with the susceptible parent and was found to be controlled by additive interactions of Lr34 with at least two to three additional genes. Transgressive segregation giving rise to plants or lines with higher and lower levels of resistance than the parents was observed in all F 2 and F 5 derivatives of the resistant-parent intercrosses and suggested that, apart from Lr34, some of the other additive genes were nonallelic. Although specific combining ability was significant in some generations, general combining ability was found to be the major component of variation. Among generations, the estimates of the narrow-sense heritability of adult-plant resistance to leaf rust ranged from 0.67 to 0.97.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.714

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 head0.200
Teacher spread0.189 · 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

Citations38
Published2003
Admission routes1
Has abstractyes

Explore more

Same venuePlant DiseaseSame topicWheat and Barley Genetics and PathologyFrench-language works237,207