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Record W4250968066 · doi:10.36814/pgr.2021.29.06

Peculiarities of traits expression of feed and seed productivity of alfalia collection accessions under high soil acidity

2021· article· en· W4250968066 on OpenAlexaboutno aff
VD Buhaiov, V. Horenskyi

Bibliographic record

VenueGenetičnì resursi roslin · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSowingProductivityAgronomyDry matterBiologyYield (engineering)Mathematics

Abstract

fetched live from OpenAlex

Aim. To study and assess the environmental adaptability of feed and seed productivity of alfalfa collection accessions under high soil acidity by determining its components - regression coefficient and stability variance. Results and Discussion. Breeding nurseries were established by summer coverless sowing: gutter sowing (row spacing 15cm) - for feed productivity; wide-row sowing (45cm) – for seed productivity. The record plot area was 3 m2, in two replications. To assess the feed productivity, we measured the dry matter yield of four mowings (budding phase); to assess the seed productivity, we determined yield from the first mowing. The environmental plasticity coefficient for the feed productivity (bi) varied across the studied accessions from ̶ 1.24 to 2.33. bi> 1 was found in 16 accessions, but the dry matter yields from most of them were significantly lower than that from the check variety, Syniukha. Low values (0 – 0.34) of the stability variance (Si2) indicate that the obtained empirical values differ little from the theoretical ones. As to the seed productivity, bi> 1 was detected in 16 accessions, 8 of which exceeded the check variety, Syniukha, in terms of seed yield. The stability variance varied in a fairly wide range from 0.12 to 308.93. The obtained values of Si2 confirm the difficulty of alfalfa breeding for increased seed productivity compared to feed productivity, which are often positively affected by opposite hydrothermal conditions: drought positively affects the seed yield, while excessive rainfall boost the feed productivity. Conclusions. Alfalfa accessions with a relatively strong response to the improvement of growing conditions with increased feed and seed productivities were selected; they can be used as starting material in breeding for these traits: Radoslava, Olha, Vavilovka (Rodnychok) (Ukraine); Evrika 1 (RF); Ferax 58 (Canada).

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.223
Teacher spread0.197 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

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