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Features of the Ukrainian soybean market

2018· article· en· W2907747128 on OpenAlexaboutno aff
С. В. Васьківська, Н. С. Орленко, С. О. Ткачик, Л. В. Худолій

Bibliographic record

VenuePlant varieties studying and protection · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianDistribution (mathematics)GeographyYield (engineering)Production (economics)CropChinaAgronomyAgricultural scienceBiologyMathematicsEconomics

Abstract

fetched live from OpenAlex

Purpose. Analyze the trends of soy bean production in the world and identify their impact on the soybean market in Ukraine. Identify the dynamics of submission and registration of applications for inclusion in the State Register of Plant Varieties, suitable for distribution in Ukraine. Compare soybean yields to the leaders of the global soybean market with the yield of soybeans in Ukraine. To highlight information on the best yields of new soybean varieties that are included in the State Register of Plant Varieties, suitable for distribution in Ukraine.Methods. Analytical, mathematical, statistical, graphic.Results The significant influence of trends on the global soybean market on the dynamics of this crop production in Ukraine and the reduction in the backlog of soybean production in Ukraine in dozens of times in comparison with the leaders in this field (USA, Brazil, Argentina, China and India) was discovered. Trends in production growth coincide with the trends of the global soybean market leaders in the USA, Brazil and Argentina. In the period from 2000 to 2014, the trend of the dynamics of production growth is of an expositional nature. The influence of production growth on the process of registration of soybeans new cultivars in the Re­gister of Plant Varieties of Ukraine was revealed. The growth trend in the number of submitted applications is positive. The largest number of soy bean varieties that passed the qualification examination was of Ukrainian descent. Among the varieties of foreign origin are varieties from Canada, France, Austria, USA, Germany, Argentina, Cyprus, Poland, Republic of Serbia, Romania, Croatia, Czech Republic, Switzerland. The new soybean varieties showed the highest yield during the period of qualifying examination in the period from 2010 to 2018.Conclusions. The growth rates of soybean production inUkraine have a similar tendency to growth rates among the leaders of this crop production. The Ukrainian varieties register is dominated by varieties of Ukrainian origin. The average level of yield of soybean cultivars in 2010–2011 corresponds to the average global yield of this crop in the world. The highest yields among the varieties that passed the qualifying exa­mination of plant varieties in the period from 2010 to 2018 were: ‘Silesia’ of French origin, ‘Relay’, ‘Terek’, ‘Avanturine’ of Ukrainian and a Canadian variety of ‘Kofu’.

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 score0.842
Threshold uncertainty score0.492

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 studies0.0010.000
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 head0.028
GPT teacher head0.188
Teacher spread0.160 · 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
Published2018
Admission routes1
Has abstractyes

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