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Record W2099594276 · doi:10.21273/hortsci.44.7.2049

Ploidy Level and DNA Content of Perennial Ryegrass Germplasm as Determined by Flow Cytometry

2009· article· en· W2099594276 on OpenAlexaboutno aff
Ying Wang, Cale A. Bigelow, Yiwei Jiang

Bibliographic record

VenueHortScience · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPerennial plantLolium perenneGermplasmPloidyBiologyCultivarSeedlingAgronomyGrowing seasonBotanyHorticultureGenetics

Abstract

fetched live from OpenAlex

Perennial ryegrass ( Lolium perenne L.) is a widely used cool-season turfgrass species. The exact ploidy levels of the worldwide perennial ryegrass accessions in the USDA National Plant Germplasm System (NPGS) are unknown, which could complicate future use and breeding efforts. The objective of this study was to determine the ploidy level and DNA content of the 194 USDA NPGS perennial ryegrass accessions and six commercial cultivars (Brightstar SLT, Catalina II, Divine, Inspire, Manhattan 4, Silver Dollar) using flow cytometry. Among the 200 accessions, 194 diploids and six tetraploids were identified. Three tetraploids originated from Canada with the remaining from Ireland, Japan, and The Netherlands. The average DNA content was 5.60 pg/2C for the diploid and 11.45 pg/2C for the tetraploid. The 2C DNA content was positively correlated ( r = 0.23, P < 0.01) with seedling plant height but not seedling leaf width. This ploidy data provide important information for future marker trait analysis and cultivar improvement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.240
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2009
Admission routes1
Has abstractyes

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