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Seed productivity and adaptability parameters of the alfalfa samples in the south of the Rostov region

2021· article· en· W3199038979 on OpenAlex
S. А. Ignatiev, А. А. Регидин, Н. С. Кравченко

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aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGrain Economy of Russia · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptabilityForageProductivityAgronomyTraitCropBiologyEnvironmental scienceEcology

Abstract

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The general climate change in the south of Russia makes the development of new varieties of grain crops, including forage grasses, with high resistance and adaptability to climatic stress factors extremely necessary. The breeding process of forage plant adapted to changing environmental conditions is seen as an effective way to allow crop production to cope with unexpected possible climate changes with the least possible losses. The specific reaction of plants to environmental conditions is of particular interest when studying collection plant samples of different gen[1]otypes, as well as when choosing varieties for cultivation in specific conditions. Studying the stability and adaptability of collection samples of forage grasses can also make it possible to use them in different regions. The purpose of the current study was to estimate alfalfa samples by the parameters of ecological adaptability and stability according to the trait ‘seed productivity’. The objects of study were 30 samples of the VIR collection from the USA, Canada, France and Peru. There has been identified a large group of samples with bi < 1. These samples were important as genotypes with a weak responsiveness of seed productivity to worse conditions. They are to be used in hybrids to obtain an initial material that is adaptive according to the trait ‘seed productivity’ in stressful conditions. The smallest bi coefficient was found in the samples ‘K-42694’ (0.20), ‘K-32783’ (0.22) and ‘K-47804’ (0.29). The stability coefficient σd 2 , which reflects the correlation between the growing conditions and seed productivity of the samples through the years of study and was calculated on the basis of the theoretical productivity and the deviation of the theoretical value from the actual one, varied from 0.01 to 74.70. This range of variation indicates that the set of samples contains such samples whose stability of productivity is genetically determined and significantly exceeds the variability of the average productivity of the entire set. Estimation of differences according to stability of seed productivity, in comparison with the standard variety ‘Rostovskaya 90’, revealed a significant difference in this trait in the samples ‘K-43272’, ‘K-50545’, ‘K-50561’.

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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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.148

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 studies0.0000.000
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 head0.026
GPT teacher head0.183
Teacher spread0.156 · 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