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Record W2014973164 · doi:10.2135/cropsci2012.08.0487

Selection for Cold Tolerance during Flowering in Short‐Season Soybean

2013· article· en· W2014973164 on OpenAlexaffabout
Elroy R. Cober, Stephen J. Molnar, Satish Rai, J. F. Soper, H. D. Voldeng

Bibliographic record

VenueCrop Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyCultivarPoint of deliveryCold toleranceHorticultureInbred strainMarker-assisted selectionBreeding programQuantitative trait locusBotanyGeneticsGene

Abstract

fetched live from OpenAlex

ABSTRACT Cold temperatures during early reproductive development may result in reduced pod and seed formation in soybean [ Glycine max (L.) Merr.]. The objectives of this work were to quantify cold tolerance of six potential parents, to screen breeding populations for cold tolerance, to search for associations between molecular markers and cold tolerance phenotypes, and to evaluate field performance of breeding lines. Six cultivars were evaluated for pod and seed set after exposure to 0 to 6 wk cold periods (15/5°C day/night), which began at flowering in growth cabinets. Evaluation at 6 vs. 2 wk following the end of a 3 or 6 wk cold period best discriminated between cold tolerant (CT) and cold sensitive (CS) cultivars. Two recombinant inbred line populations were cold stressed in growth cabinets with divergent selection performed over the F 5 through F 7 generations to select CT and CS lines. Bulked segregant analysis identified six chromosomal regions, four of which are related by homology, as potentially impacting the trait. Over 8 yr in the field at Ottawa, Canada, CT lines yielded 379 kg ha −1 more but matured 5.5 d later than CS lines without visual symptoms of cold damage. Following selection for early maturity, random lines from an additional four populations developed from a selected CT and CS line each crossed to another CT and CS parent were field tested in three environments. Cold tolerant × CT lines yielded about 8% more than CS × CS lines, again without visual cold damage symptoms.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.245

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 head0.017
GPT teacher head0.228
Teacher spread0.211 · 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

Citations13
Published2013
Admission routes2
Has abstractyes

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