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Record W2108365259 · doi:10.1139/g2012-013

Identification and phenotypic description of new wheat – six-rowed winter barley disomic additions

2012· article· en· W2108365259 on OpenAlexvenueno aff
Márta Molnár‐Láng, Klaudia Kruppa, András Cseh, Julianna Bucsi, Gabriella Linc

Bibliographic record

VenueGenome · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
FundersHungarian Scientific Research FundFonds National de la Recherche Luxembourg
KeywordsBiologyBackcrossingHybridIntrogressionCultivarGlumeCommon wheatHordeum vulgarePhytotronAgronomyPloidyPoaceaeBotanyGeneticsChromosomeGene

Abstract

fetched live from OpenAlex

To increase the allelic variation in wheat-barley introgressions, new wheat-barley disomic addition lines were developed containing the 2H, 3H, 4H, 6H, and 7H chromosomes of the six-rowed Ukrainian winter barley 'Manas'. This cultivar is agronomically much better adapted to Central European environmental conditions than the two-rowed spring barley 'Betzes' previously used. A single 'Asakaze' × 'Manas' wheat × barley hybrid plant was multiplied in vitro and one backcross plant was obtained after pollinating 354 regenerant hybrids with wheat. The addition lines were selected from the self-fertilized seeds of the 16 BC(2) plants using genomic in situ hybridization. The addition lines were identified by fluorescence in situ hybridization using repetitive DNA probes (HvT01, GAA, pTa71, and Afa family), followed by confirmation with barley SSR markers. The addition lines were grown in the phytotron and in the field, and morphological parameters (plant height, fertility, tillering, and spike characteristics) were measured. The production of the disomic additions will make it possible to incorporate the DNA of six-rowed winter barley into the wheat genome. Addition lines are useful for genetic studies on the traits of six-rowed winter barley and for producing new barley dissection lines.

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 score0.979
Threshold uncertainty score0.665

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)0.0010.000

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 head0.028
GPT teacher head0.218
Teacher spread0.190 · 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

Citations31
Published2012
Admission routes1
Has abstractyes

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