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Priority technologies for developing new highly productive varieties of spring bread wheat in the Middle Urals

2022· article· en· W4312176674 on OpenAlex
Н. Н. Зезин, V. A. Vorobiev, A. V. Vorobiev, Z. R. Nikolaeva

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGrain Economy of Russia · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
FundersRussian Academy of SciencesUral Branch, Russian Academy of Sciences
KeywordsVariety (cybernetics)ProductivityAgricultural scienceAgricultureNew VarietyBiologyGeographyMathematicsAgronomyCultivarStatisticsEcologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

The study has been carried out at the FSBSI «Ural Federal Agrarian Research Center of the Ural Branch of the Russian Academy of Sciences» on the fields of the Krasnoufimsk Breeding Center in 2019–2021. The purpose was to develop new highly productive varieties of spring bread wheat adapted to the climatic conditions of the Middle Urals using parental forms with high breeding indices in hybridization. There has been given a characteristic of the earlymaturing variety ‘Ekstra’ and middle-early maturing ‘Nitsa’ and their parents, namely, ‘Omskaya 35’ and ‘Iren’, ‘Ekaterina’ and ‘Krasnoufimskaya 100’, according to such breeding indices as Mexican, Canadian, Poltava, attraction, productivity, potential head productivity, intensity, micro-distribution, linear head density, grain filling. There has been shown that the productivity advantage of the variety ‘Ekstra’ over the variety ‘Iren’ was 0.37 t/ha (11.1 %) and over thevariety ‘Omskaya 35’ it was 0.31 t/ha (9.1 %). The variety ‘Ekstra’ has combined the high values of six breeding indices from the middle maturing variety ‘Omskaya 35’ and exceeded both parents in the studied indices. The productivity advantage of the variety ‘Nitsa’ was 0.52 t/ha (19.2 %) over the variety ‘Ekaterina’ and over the variety ‘Krasnoufimskaya 100’ it was 0.40 t/ha (14.2 %). It has combined the high values of four indices from the variety ‘Ekaterina’, six from the variety ‘Krasnoufimskaya 100’ and significantly exceeded the parental varieties according to such indices as Poltava, Mexican, microdistribution, attraction, grain filling, intensity. There has been identified a high positive correlation between grain productivity and attraction indices (r = 0.761) and Mexican (r = 0.864), an average positive correlation between indices of intensity (r = 0.601), potential head productivity (r = 0.507), grain filling (r = 0.333). The results have showed that involving parents with high values of breeding indices into hybridization could contribute to the development of new highly productive varieties of spring wheat.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.036
GPT teacher head0.212
Teacher spread0.176 · 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