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Record W2606798953 · doi:10.2135/cropsci2016.12.0974

Pea Phenology: Crop Potential in a Warming Environment

2017· article· en· W2606798953 on OpenAlexafffundabout
Shaoming Huang, Krishna Kishore Gali, Bunyamin Tar’an, Thomas D. Warkentin, Rosalind Bueckert

Bibliographic record

VenueCrop Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsUniversity of Saskatchewan
FundersWestern Grains Research Foundation
KeywordsBiologyPhenologyQuantitative trait locusSeedingSativumPoint of deliveryAgronomyCultivarInbred strainCropField peaHorticultureGeneticsGene

Abstract

fetched live from OpenAlex

One hundred and seven recombinant inbred lines (RILs) were developed from the cross of field pea ( Pisum sativum L.) cultivars CDC Centennial × CDC Sage with the objectives of evaluating phenology and yield components, and to map the quantitative trait loci (QTLs) responsible for these traits. Experiments were conducted in 2013 using normal seeding date at Saskatoon and Rosthern in Saskatchewan, and in 2014 using both normal and late seeding. The late seeding date was used to expose the plots to a more heat stressful environment, analogous to that experienced in warmer regions of the North American prairies. Days to flowering termination (DTFT) was positively correlated with final seed yield under both normal and late seeding conditions. Among the yield components, pod number (PN) was most positively associated with seed yield, followed by thousand seed weight (TSW) and seed number per pod (SNPP). A genetic linkage map consisting of 1024 loci with a total coverage of 1702 cM was developed using SNP markers. Ten QTLs were found consistent over more than one environment, five for flowering traits and five for yield component traits. A stable QTL at Linkage Group 6b for days to flowering was detected over four environments. The QTLs for flowering duration, TSW and reproductive node number were different between normal and late seeding, which implies different mechanisms were involved under the contrasting environments.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score1.000

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.022
GPT teacher head0.223
Teacher spread0.201 · 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.

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

Citations40
Published2017
Admission routes3
Has abstractyes

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