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Record W2806989118 · doi:10.2134/agronj2018.01.0068

Molecular Identification and Characterization of Seeded Turf Bermudagrass Cultivars Using Simple Sequence Repeat Markers

2018· article· en· W2806989118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAgronomy Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaOklahoma Agricultural Experiment StationU.S. Department of Agriculture
KeywordsCultivarBiologyGenetic diversityGermplasmCynodon dactylonMicrosatelliteAgronomyGenetic markerLocus (genetics)AllelePopulationGeneticsGene

Abstract

fetched live from OpenAlex

Core Ideas Six to nine signature alleles were revealed for each of the four standard seeded bermudagrass cultivars with 32 SSR markers. All individual bermudagrass plants were correctly assigned to their source cultivars using the SSR markers. The SSR marker profiles can be effectively used to identify blinded individuals to the source cultivars. Common bermudagrass [ Cynodon dactylon (L.) Pers. var. dactylon ], is increasingly used in the development of seed‐propagated turf cultivars. Each seeded bermudagrass cultivar is a heterogeneous population composed of heterozygous genotypes. Therefore, the accurate identification of seeded bermudagrass cultivars is a challenge and has not yet been reported although this kind of information would be valuable for new cultivar development, seed certification, and intellectual property protection. Accordingly, the objectives of this study were (i) to characterize the genetic diversity within and relatedness between turf‐type seeded cultivars; and (ii) to investigate the assignment of individuals to their source cultivars using simple sequence repeat (SSR) markers. Four seeded cultivars, NuMex Sahara, Princess‐77, Riviera, and Yukon were used in the investigation. Thirty individual plants, two bulk samples, and two additional individual plants from each of the four cultivars were genotyped with 32 SSR markers that were sampled to span a major portion of the species genome. The number of alleles amplified per SSR locus ranged from 3 to 10, with a mean of 5. Six to nine signature alleles were identified for each of the four cultivars. Genetic distance estimates and clustering results were consistent with the respective breeding history. Individual plants formed four distinct groupings corresponding exactly to the four cultivars and all individuals were correctly assigned to their respective source cultivars. The total gene diversity of the four cultivars was 0.257, indicating high diversity. The posterior test also indicated that bulk samples and two additional individual plants were clearly assigned to their source cultivars. The approach developed in this study is useful for the accurate identification of seeded bermudagrass cultivars.

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.

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 score0.891
Threshold uncertainty score0.398

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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