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Record W3027205249 · doi:10.36461/np.2020.54.1.006

ОЦЕНКА СОРТООБРАЗЦОВ КРАМБЕ В ЗАВИСИМОСТИ ОТ ГИДРОТЕРМАЛЬНЫХ УСЛОВИЙ

2020· article· ru· W3027205249 on OpenAlexaboutno aff
Т. Ya. Prakhova, E.L. Turina

Bibliographic record

VenueNiva Povolzh`ia · 2020
Typearticle
Languageru
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptabilityProductivityYield (engineering)Research ObjectAnimal scienceAgronomyMathematicsBiologyHorticultureGeographyEcologyPhysics

Abstract

fetched live from OpenAlex

Целью исследований являлась оценка сортообразцов крамбе абиссинской по продуктивности и адаптивности в зависимости от гидротермальных условий. Объектом исследований являлись сортообразцы различного эколого-географического происхождения. Изучение проводилось в контрастных климатических условиях Среднего Поволжья и степного Крыма в 2017-2019 годах. Продуктивность сортообразцов крамбе абиссинской варьирует в пределах 1,54-2,04 т/га, в среднем по двум регионам. В среднем за три года более высокий урожай отмечен у образцов к-39 (США) и к-35 (Германия), продуктивность которых составила 2,01-2,04 т/га, что превышает сорт-стандарт Деметра на 0,22 и 0,25 т/га. Данные номера отличались высокими значениями коэффициента адаптивности, который составил 1,04-1,13 и показывает их большую приспособленность к различным условиям возделывания. Сортообразцы из Канады (к-25) и из Чехословакии (к-34) сформировали урожайность 1,82 и 1,87 т/га, что несущественно превышает стандарт по урожайности. Прибавка здесь составила 0,03 и 0,08 т/га. Содержание жира в плодиках колебалась в пределах 29,68-32,20. По результатам данного признака выделился номер из Германии к-35, масличность которого составила 32,20. Наиболее стабильными по урожайности были образцы к-35, к-34 и к-10, параметры стабильности которых составили 22,8 26,1 и 29,0. Высоким значением показателя уровня стабильности сорта (ПУСС) отличались сортообразцы к-39 и к-10, значения данного признака составили 0,47 и 0,52 соответственно. При этом у данных номеров отмечена высокая экологическая устойчивость (0,49 и 0,53), что показывает более широкий диапазон их приспособленности к различным условиям произрастания. The aim of the research was to evaluate the productivity and adaptability of varieties of crambe abyssinica depending on hydrothermal conditions. The object of the research was varieties of various ecological and geographical origin. The study was conducted in contrasting climatic conditions of the Middle Volga and steppe Crimea in 2017-2019. The productivity of varieties of crambe abyssinica varied between 1.542.04 t/ha, on average in two regions. On average, for three years a higher yield was observed for samples k-39 (USA) and k-35 (Germany), which productivity was 2.01-2.04 t/ha, which exceeded the standard variety Demetra by 0.22 and 0.25 t/ha. These samples were distinguished by high values of adaptability coefficient, which amounted to 1.04-1.13 and showed their great adaptability to various cultivation conditions. Varieties from Canada (k-25) and Czechoslovakia (k-34) formed yields of 1.82 and 1.87 t/ha, which was slightly higher than the standard for yields. The increase there was 0.03 and 0.08 t/ha. The fat content in fruitlets ranged from 29.68-32.20. According to the results of this feature, the number k-35 from Germany was distinguished, the oil content was 32.20. The most stable yields had the samples k-35, k-34 and k-10, which stability parameters were 22.8 26.1 and 29.0. The varieties k-39 and k-10 were distinguished by a high value of the indicator of the variety stability level (IVSL), the values of this trait were 0.47 and 0.52, respectively. Moreover, these varieties had a high environmental sustainability (0.49 and 0.53), which showed a wider range of their adaptability to different growing conditions.

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)0.003
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.038
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0040.005
Scholarly communication0.0110.005
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0380.018

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 head0.034
GPT teacher head0.236
Teacher spread0.202 · 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".

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Citations0
Published2020
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