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Record W4311793975 · doi:10.3390/plants11243525

Variability in Maturity, Oil and Protein Concentration, and Genetic Distinctness among Soybean Accessions Conserved at Plant Gene Resources of Canada

2022· article· en· W4311793975 on OpenAlexaffabout
Yong‐Bi Fu, Elroy R. Cober, Malcolm J. Morrison, Frédéric Marsolais, Rong Zhou, Ning Xu, Alison Claire Gahagan, Carolee Horbach

Bibliographic record

VenuePlants · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGermplasmBiologyMaturity (psychological)CultivarTraitGlycineGeneQuantitative trait locusBiotechnologySoybean oilHigh proteinAgronomyGeneticsAmino acidFood science

Abstract

fetched live from OpenAlex

(L.) Merr.) is one of the important crops in Canada and has the potential to expand its production further north into the Canadian Prairies. Such expansion, however, requires the search for adapted soybean germplasm useful for the development of productive cultivars with earlier maturity and increased protein concentration. We initiated several research activities to characterize 848 accessions of the soybean collection conserved at Plant Gene Resources of Canada (PGRC) for maturity, oil and protein concentration, and genetic distinctness. The characterization revealed a wide range of variations present in each assessed trait among the PGRC soybean accessions. The trait variabilities allowed for the identification of four core subsets of 35 PGRC soybean accessions, each specifically targeted for early maturity for growing in Saskatoon and Ottawa, and for high oil and protein concentration. The two early maturity core subsets for Saskatoon and Ottawa displayed days to maturity ranging from 103 to 126 days and 94 to 102 days, respectively. The two core subsets for high oil and protein concentration showed the highest oil and protein concentration from 25.0 to 22.7% and from 52.8 to 46.7%, respectively. However, these core subsets did not differ significantly in genetic distinctness (as measured with 19,898 SNP markers across 20 soybean chromosomes) from the whole PGRC soybean collection. These findings are useful, particularly for the management and utilization of the conserved soybean germplasm.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.939

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 head0.013
GPT teacher head0.184
Teacher spread0.171 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

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