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Record W1994522607 · doi:10.5376/mpb.2013.04.0011

Cross Species Amplification of Adzukibean Derived Microsatellite Loci and Diversity Analysis in Greengram and Related <i>Vigna</i> Species

2013· article· en· W1994522607 on OpenAlexvenueno aff
M. Sathya, P. Jayamani

Bibliographic record

VenueMolecular Plant Breeding · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyVignaMicrosatelliteGenetic diversityGeneticsEvolutionary biologyBotanyAlleleGenePopulation

Abstract

fetched live from OpenAlex

Greengram or mungbean ( Vigna radiata (L.) Wilczek) is a well known grain legume in Asian countries. Among the different DNA markers, microsatellite or simple sequence repeats (SSRs) are the markers of choice for various genetic studies due to co-dominant nature, loci specificity and high reproducibility. In the present study, a set of thirty-five microsatellite primer pairs derived from adzukibean ( Vigna angularis (Willd.) Ohwi & Ohashi) were used to assess the transferability and tested for their ability to amplify microsatellite loci in greengram and related Vigna species. Of the thirty five microsatellite markers, thirty-two were successfully amplified across the thirty six genotypes and twenty eight were polymorphic. A total of 83 microsatellite alleles were generated with an average of 2.96 alleles per locus. Number of alleles ranged from two to five. Dendrogram formed based on UPGMA, 36 genotypes were grouped into five clusters. Similarly, the neighbour-joining tree developed based on weighted average for dissimilarity matrix grouped 36 genotypes into five groups. The finding suggests that adzukibean derived microsatellite markers are highly informative and could be used to improve the greengram at molecular level.

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 score0.847
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.190
Teacher spread0.172 · 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
Published2013
Admission routes1
Has abstractyes

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