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Record W2033538174 · doi:10.2135/cropsci2008.10.0611

Phenotypic and Genotypic Characterization of Purple Kernel Streak in White Food Corn

2009· article· en· W2033538174 on OpenAlexafffundabout
E. A. Lee, Jeffrey A. Young, Farhad Azizi, S. C. Jay, A. W. Schaafsma

Bibliographic record

VenueCrop Science · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Food and AgricultureAgricultural Adaptation CouncilCanada Foundation for Innovation
KeywordsBiologyQuantitative trait locusGermplasmWhite (mutation)Zea maysGenotypePopulationLocus (genetics)HybridTraitInbred strainField cornGeneticsHorticultureAgronomyGene

Abstract

fetched live from OpenAlex

Purple kernel streaking (PKS) in white food corn ( Zea mays L.) is characterized by the accumulation of purple‐pigmented streaks (anthocyanins) in an otherwise colorless pericarp. This paper is the first published report documenting PKS, the prevalence of the trait in commercial white food corn germplasm, and the genetics underlying it. Entries from the Early White Food Corn Performance Trials were grown in Ontario over a three‐year period and rated for incidence of PKS and days to flower. All commercial hybrids entered were genetically predisposed to PKS with severity varying across years and entries, and not consistently related to hybrid maturity. Quantitative trait locus (QTL) mapping was used to identify the genomic regions influencing PKS expression in an F 2:3 population derived from the cross of two white food corn inbred lines, SD79 and SD80. PKS exhibited significant genotype × year interaction. QTLs were identified for each year explaining 64 and 46% of the phenotypic variation, with only one single‐effect and one two‐way interaction common across the two years. Linkage of the main single‐effect QTL with the y1 gene, coupled with the G×E effects, may explain the prevalence of PKS in commercial white food corn hybrids.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.199

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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

Citations4
Published2009
Admission routes3
Has abstractyes

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