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Record W4285008813 · doi:10.21273/jashs05189-22

Mapping Winterhardiness in Garden Roses

2022· article· en· W4285008813 on OpenAlexafffundabout
Cindy Rouet, Joseph O’Neill, Travis Banks, Karen Tanino, Elodie Derivry, Daryl J. Somers, Elizabeth A. Lee

Bibliographic record

VenueJournal of the American Society for Horticultural Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsUniversity of SaskatchewanUniversity of GuelphVineland Research and Innovation Centre
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsQuantitative trait locusBiologyCultivarHardiness (plants)TraitHorticultureBotanyGeneticsGene

Abstract

fetched live from OpenAlex

Field winterhardiness is a critical trait in rose cultivars ( Rosa × hybrida ) grown in northern climates. Although the molecular basis of cold hardiness has been well documented in model organisms such as Arabidopsis thaliana , little is known about the genetics and mechanisms underlying winterhardiness in roses. This research aims to explore the genetic control of winterhardiness for application in breeding programs using quantitative trail loci (QTL) analysis in two biparental rose populations derived from cold-hardy roses of the Canadian Explorer Series Collection. Field winterhardiness was assessed as a complex trait with winter damage and regrowth recorded in multiyear and multilocation trials in Ontario and Saskatchewan, Canada. In addition, this research explored the relationship between field measurements and electrolyte leakage recorded under artificial conditions. Electrolyte leakage had limited utility for application in rose breeding programs as a substitute for field evaluation, but did enable identification of QTL associated with potential cold hardiness candidate genes. A QTL for electrolyte leakage mapped to a genomic region that harbors a CBF1 -like transcription factor. A total of 14 QTLs associated with field winter damage and regrowth were discovered, and they explained between 11% and 37% of the observed phenotypic variance. Two QTL associated with winter damage and regrowth overlapped with a known QTL for black spot ( Diplocarpon rosae ) disease resistance, Rdr1 , in an environment under high disease pressure. Due to the complexity of field winterhardiness and its direct reliance on intertwined factors, such as overall plant health, moisture status, snow cover, and period of prolonged sub-zero temperatures, field trials are the ultimate measurement of field winterhardiness. Transgressive segregation was observed for all traits, and it was most likely due to complementary gene action. Field winter damage and regrowth were highly heritable in single environments, but they were subject to genotype × environment interaction resulting from pest pressure and severe climatic conditions.

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)0.002
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 score0.940
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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 designBench or experimental
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

Citations4
Published2022
Admission routes3
Has abstractyes

Explore more

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