MétaCan
Menu
Back to cohort

Sources of valuable breeding traits and their use in creation of barley varieties adapted to conditions of Volga-Vyatka region

2017· article· en· W2905070869 on OpenAlexaboutno aff
Л. П. Кокина, Л. М. Щеклеина, A. V. Kunilova

Bibliographic record

VenueAgricultural science Euro-North-East · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsVolga regionBiologyGeographyAgronomyHistoryEthnology

Abstract

fetched live from OpenAlex

Usage of genetic variability is one of the factors of successful breeding of spring barley (Hordeum vulgare L.). Main factors that limits barley productivity in Volga-Vyatka region are duration of growing season and its particular phases, low natural fertility and increased acidity of soils, spring-summer drought, as well as multiple diseases. Four hundred and thirteen collection numbers of different ecological-geographic origins were studied. For breeding work the most interesting were early accessions: Stimul, Acha, Bagan (Russia), Surpriz and Adapt (Ukraine) and other. There are accessions combined productivity and earliness - Dina, Andrey, Belogorsky 90 (Russia), Syabra (Belarus), Druvis, Malva (Latvia), Veslets (Bulgaria), Danuta (German), City (France), and Codac (Canada). Varieties Bionik, Omsky golozerny 1 (Russia), Gonar (Belarus), Malva, Druvis (Latvia), 23007 (Dutch), and Azure (USA) are lodging resistant. Varieties which have complex of valuable breeding trait (productivity, number of productive stems, grain mass per ear and per plant, 1000 grain mass) are: Zavetny, Natali (Russia), Yakub (Belarus), Rodos, Korona Lashego (poland), Jdumeja, Druvis (Latvia), Fillippa, Nue grosse (Sweden), Hja (Finland), 23007 (Dutch), City (France), and other. Varieties Tandem, Chelyabinsky 96, Chelyabinsky 99, Sonet (Russia), Firlbeks Union (Switzerland), Lamba (Dutch), Canasta (Great Britain), Buck (Canada), Bonita (Argentina), and other are resistant to osmotic stress; varieties Dobry, Novichok, Khlynovsky, Vikont, Partner, Priazovsky 9, Zernogradets 770, Signal, Rus', Luka (Russia), Dzivosny (Belarusь), Dzherelo (Ukraine), and other - are resistant to aluminum-acid stress. Varieties Petr, Lel', Munach (Russia), Sultan (Netherlands) have resistance to loose smut in artificial infectious background; varieties Dina, Forward, Medicum 336, Musson (Russia), Edem, Surpriz, Mironovsky 86, Get'man (Ukraine), Margret, Xanadu, Orthega (German), Buck (Canada) and other have complex resistance to some fungi diseases. Combining of disease resistance and high number of productive stems, grain mass per ear and per plant, 1000 grain mass are characteristic for varieties Zevs, Zavetny, Natali (Russia) Ilek 34 (Kazakhstan), Codak (Canada) and other. Lines and varieties created with use of sources of valuable trait are studied in North-East Agricultural Research Institute in all stages of breeding process. Working collection consist of 114 covered and 17 naked accessions of spring barley is used successfully at creation of adaptive varieties.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.221
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAgricultural science Euro-North-EastSame topicAgricultural Productivity and Crop ImprovementFrench-language works237,207