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Dynamics of alfalfa seed hardness change depending on the seed storage time

2020· article· en· W3003486250 on OpenAlexaboutno aff
S. А. Ignatiev, А. А. Регидин, T. V. Gryazeva, К. N. Goryunov

Bibliographic record

VenueGrain Economy of Russia · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationSowingHorticultureBiologyRipeningPerennial plantBotany

Abstract

fetched live from OpenAlex

A significant part of perennial legumes seeds, including alfalfa, after ripening, has a seed coat nonpermeable for water and air, and therefore they do not germinate immediately after sowing. This property is called seed hardness. The purpose of our research was to study seed hardness of the alfalfa samples in the collection of the FSBSI “ARC “Donskoy” depending on the seed storage time. The seed hardness of the studied varieties after 1 month of storage ranged from 31 to 74% on average for two years. The varieties “Sonora 76” (the USA) and “Stavropolskaya 430” (Russia) possessed the highest value of the studied trait (62% and 74%, respectively). The seed hardness of the standard variety “Rostovskaya 90” was 49.5%. After 6 months of storage, the percentage of seed hardness in all studied varieties significantly decreased. The studied indicator of the standard variety “Rostovskaya 90” decreased to 24%. The varieties “Smuglyanka” (Ukraine), “Zvezdochka” (Russia), “Veko” (Canada), “Admiral” (Canada), “Verta+” (Canada), “AZNIHI-5” (Azerbaijan), “Tashkentskaya 1” (Uzbekistan), “Karlygash” (Kazakhstan) with the indicators from 7% to 13% had a significantly lower percentage of seed hardness compared with the standard variety. The varieties “Sonora 76” (USA) and “Stavropolskaya 430” (Russia), with seed hardness of 38.5% and 49%, respectively, significantly exceeded the standard variety “Rostovskaya 90”. After 12 months of storage, seed hardness of the studied varieties ranged from 4 to 22.5%. The indicator for this trait of the variety, taken as a standard was 16.5%. A significantly lower percentage of seed hardness (from 3% to 10%) was in 12 studied varieties, the lowest indicator was shown by the variety “Zvezdochka” (Russia). The two varieties “Sonora 76” (USA) and “Stavropolskaya 430” (Russia) showed a significant excess with indicators of 21.5% and 22.5%, respectively.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.031
GPT teacher head0.189
Teacher spread0.158 · 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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Citations3
Published2020
Admission routes1
Has abstractyes

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