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PROSPECTS FOR THE USE OF SOYBEAN COLLECTION MATERIAL USED IN BREEDING STUDIES IN PRIAMURYE (AMUR REGION)

2019· article· en· W4407419125 on OpenAlexaboutno aff
Evgenia M. Fokina, D.R. Razantzvey

Bibliographic record

VenueFar Eastern Agrarian Herald · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGeographyBiotechnology

Abstract

fetched live from OpenAlex

The article presents the findings of investigations on the soybean collection material under the natural and climatic conditions of Priamurye. The experimental part of the work was carried out at the All-Russian Research Institute of Soya Laboratory of Soya Breeding from years 2008 till 2018. The weather conditions during the years of research differed in temperature and moisture conditions, but in general were favorable for soybean cultivation. Field experiments were arranged on the plots of crop rotation intended for breeding (Village of Sadovoye, Tambov district, Amur Region) on meadow chernozem-like soils. Integrated assessment was carried out for more than 500 proved varieties and specimens of soybean from the USA, Algeria, China, Canada, Germany, Romania, Serbia, France, Italy, Japan, Sweden, Poland, Hungary, Austria, Switzerland, Czech Republic, Yugoslavia, former Soviet republics - Ukraine, Moldova, Belorussia and scientific research institutions of the Russian Federation. All varieties and specimens of soybean were studied for 3-5 years, in order to identify sources of economically useful features for their further inclusion in the breeding process. The researches revealed the most promising varieties of the world collection intended for use as starting material (base line) in practical crop breeding. The best varieties were determined in accordance with their usage as follows: ultra early-ripening, early-ripening, highly productive and resistant to the pathogens, prevalent in the region, high-protein forms, etc. More than 320 different combinative crossbreedings were carried out; obtained hybrid progeny in 311 combinations which was successively studied according to the full scheme of the selection process. The hybrid material selected in accordance with various directions of breeding research makes it possible to create highly productive soybean varieties of a new generation, various maturity groups with improved economically useful features.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.128
GPT teacher head0.259
Teacher spread0.132 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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