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Genetic diversity of oat accessions revealed by SSR markers

2022· article· en· W4379043704 on OpenAlexfundno aff
Yarvaan Munkhtuya

Bibliographic record

VenueInternational Journal of Agriculture and Food Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaLouisiana State University
KeywordsGermplasmGenetic diversityBiologyMicrosatelliteJaccard indexAlleleCropGenetic similarityGenetic markerBiotechnologyLocus (genetics)Genetic resourcesGenetic distanceGenetic variationAgronomyHorticultureGeneticsPopulationMathematicsStatistics

Abstract

fetched live from OpenAlex

Oat is an important cereal crop for the food and feed industries. Genetic resources of oat are the basic materials for sustainable breeding programs. Microsatellites (SSR) are a useful tool for understanding the genetic background of oat germplasm resources. We used 83 SSR primer pairs to assess the genetic diversity of 286 oat accessions from five countries. The results indicated the presence of considerable variation among accessions. The number of alleles per SSR locus ranged from 2 to 8, with an average of 3.49; allelic frequencies ranged from 0.002 to 0.709; Nei’s genediversity was 0.67, ranging from 0.44 to 0.85; and polymorphism information content (PIC) values ranged from 0.37 to 0.83. Genetic distance estimated by the Jaccard model was compared between accession groups as well as among all accessions using all marker alleles. The principle coordinates analysis based on genetic dissimilarity also revealed distinct groups of accessions. We concluded that SSR markers are effective for identification of oat germplasm resources and use of germplasm from North America and Asia should lead to significant progress in Mongolian oat breeding programs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.295

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 science0.0010.000
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 head0.221
Teacher spread0.208 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Agriculture and Food ScienceSame topicWheat and Barley Genetics and PathologyFrench-language works237,207