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Record W4210923939 · doi:10.1134/s1022795422010069

Prospect for Incorporation of Ppd-D1a Allele in Russian Spring Bread Wheat Cultivars

2022· article· en· W4210923939 on OpenAlexaboutno aff
С. Б. Лепехов

Bibliographic record

VenueRussian Journal of Genetics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyCultivarSpring (device)AlleleAgronomyBiotechnologyGeneticsGeneEngineering

Abstract

fetched live from OpenAlex

Varieties of spring bread wheat with the Ppd-D1a allele are insensitive to the photoperiod and are widespread in the world. The overwhelming majority of spring bread wheat cultivars in Russia are sensitive to the length of daylight. Incorporation of the Ppd-D1a allele in Russian cultivars of spring soft wheat will make it possible to accelerate breeding, using one to two additional vegetations per year. The aims of this paper are to (1) consider a trend of distribution of the Ppd-D1a allele among spring bread wheat of the Northern Hemisphere, (2) reveal an influence of the Ppd-D1a allele on agronomic traits of spring bread wheat, and (3) designate the main ways of breeding work for creation of Russian spring bread wheat with insensitivity to the photoperiod. The frequency of the Ppd-D1a allele increases from countries at high latitude to those at low latitude. The influence of the Ppd-D1a allele on agronomic traits depends on the geographic latitude where the experiment takes place and leads to a reduction of the period from seedling to heading, plant height, spikelets per spike, and protein content and to an increase in duration of green leaves after heading. The Ppd-D1a allele has a negative effect on wheat yield north of 50° N. The high frequency of the Ppd-D1a allele in Canadian spring bread wheat varieties indicates that this allele can become widespread in some regions of Russia. The negative effects caused by this allele can be compensated by reasonable selection of parents for hybridization.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.190

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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRussian Journal of GeneticsSame topicWheat and Barley Genetics and PathologyFrench-language works237,207