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Record W2537247694 · doi:10.21273/hortsci.35.3.400a

066 Determination of Genetic Diversity of Potato Varieties by Random Amplified Polymorphic DNA Analysis

2000· article· en· W2537247694 on OpenAlexaff
Jung-Yoon Yi, Eung‐Soo Kim, Hyun-Mook Cho, Young-Eun Park, Kuen-Woo Park

Bibliographic record

VenueHortScience · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRAPDGermplasmBiologyGenetic diversityGenotypeGeneticsgenomic DNAAmpliconBiotechnologyDNAPolymerase chain reactionBotanyGenePopulation

Abstract

fetched live from OpenAlex

This study was carried out to prove the new variety's originality by using Random Amplified Polymorphic DNA (RAPD) Analysis and to develope the specific markers for distinction new variety from others to database for improving the efficiency of germplasm conservation. The RAPD procedure was used to determine genetic diversity of 13 potato varieties including seven recommended varieties of Korea and six genotypes. Genomic DNAs from the 13 genotypes were amplified using PCR and URP 2F, 4R and 8R primers. URP primers which were 20-mers were received from NIAST (National Institute of Agricultural Science and Technology, Suwon, Korea) and they were shown very high reproducibility because of the high annealing temperature above 55 °C. So, they were known to be very desirable primers to examine the specificity between inter and intra species in various spectra. These 13 lines have many resemblances in plant characteristics each other because `Jopung', '92N09-6', `Daekwan 68', and `Daekwan 70' were originated from `Superior', `Atlantic', `Namsuh', and `Irish Cobbler' respectively. So, there are many difficulties to distinct new variety by the naked eye. The results of this study show that 2 sets of URP primers are very useful to distinct new variety and mutants from others.

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 score0.491
Threshold uncertainty score0.511

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 science0.0000.000
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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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
Published2000
Admission routes1
Has abstractyes

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