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Record W7079708530 · doi:10.15159/ar.25.082

Assessing the yield potential of soybean maturity groups in different Ukrainian climatic zones

2025· article· en· W7079708530 on OpenAlexaboutno aff

Bibliographic record

VenueEesti Maaülikool. EMU Dspace · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarYield (engineering)Context (archaeology)AgricultureMaturity (psychological)UkrainianProductivity

Abstract

fetched live from OpenAlex

In the context of global climate change, increasing demands for food security, and the need to expand sources of plant-based protein, soybean is gaining particular importance as a highly productive and valuable agricultural crop. Purpose. The study aimed to evaluate the yield potential of soybean cultivars from different maturity groups under various agro-climatic conditions of Ukraine by analysing their adaptability, productivity, and stability. The objective was to justify the selection of maturity groups best suited for specific regions to ensure sustainable soybean production. Methods. Field experiments were conducted in 2023–2024 across three agro-climatic zones: Odesa (Steppe), Cherkasy (Forest-Steppe), and Zhytomyr (Polissia). A total of 26 early- and mid-maturing soybean cultivars of Ukrainian and foreign origin were evaluated. Adaptive variability was assessed using standard statistical methods. Results. Among early-maturing cultivars, Taverna, Eri, and Calgary showed superior individual productivity, surpassing the standard by 9–13% in seed weight per plant and reaching yields up to 3.15 t ha⁻¹ in Polissia. These cultivars demonstrated high plasticity and stability across environments. Among mid-maturing cultivars, ES Visitor and ES Collector delivered consistently high yields across all zones, exceeding the standard by 0.09–0.26 t ha⁻¹. Alicia also showed high productivity in the Forest-Steppe and Polissia, making it suitable for regions with moderate moisture. The highest average yield for early-maturing cultivars was recorded in Polissia (2.50 t ha⁻¹), and for mid-maturing ones - in the Forest-Steppe (2.68 t ha⁻¹). Regardless of the zone, Taverna, Eri, Calgary, ES Visitor, and ES Collector demonstrated stable and high productivity. Conclusions. The findings provide a basis for optimising cultivar selection and soybean production technologies, tailored to regional climatic conditions and challenges posed by climate change.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.017
GPT teacher head0.266
Teacher spread0.248 · 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
Published2025
Admission routes1
Has abstractyes

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