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Research results of Jerusalem artichoke varieties and hybrids in the forest-steppe of the Omsk region

2021· article· en· W3120725597 on OpenAlexaboutno aff
V. V. Khristich, Yu.V. Frizen, A A Gaivays

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsnot available
Fundersnot available
KeywordsJerusalem artichokeHybridBiologyForest steppeYield (engineering)AgronomyAgricultureProductivityCropPhenologyForageGeographyHorticultureBotanyEcology

Abstract

fetched live from OpenAlex

Abstract The article presents the five-year results of the studying the adaptation of varieties, and hybrids of Jerusalem artichoke in the forest-steppe of the Omsk region. The analysis of biometric indicators and crop yield structure is presented. The dynamics of the accumulation of herbage, as well as the periods of the passage of phenological phases are shown. The chemical composition of plants is determined. The studies show that many hybrids and varieties in Western Siberia do not go through the flowering phase, but at the same time form a full-fledged tuber crop. At the same time, the high yield of the aerial mass of Jerusalem artichoke does not always ensure a high yield of tubers. On average, for five years of research, the French D-5 hybrid, Canadian sample and variety samples’ No. 1 and No. 9 we distinguished in terms of herbage productivity. This indicator was 49.4-58.9 t / ha. In terms of tuber productivity, the best varieties were No. 9 and No. 12, as well as the Sireniki-1 variety (29.1-30.2 t / ha). The distinguished varieties and hybrids of Jerusalem artichoke are recommended for the introduction into production in order to improve the forage base of agricultural enterprises. The research on the selection of varieties and hybrids in order to obtain high-tech tubers (large and aligned) for processing in the food industry will be continued.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.227
Threshold uncertainty score0.996

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 studies0.0000.007
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 head0.029
GPT teacher head0.257
Teacher spread0.229 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Earth and Environmental ScienceSame topicMicrobial Metabolites in Food BiotechnologyFrench-language works237,207