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Record W2159529915 · doi:10.1093/jxb/erm357

Deterioration of western redcedar (Thuja plicata Donn ex D. Don) seeds: protein oxidation and in vivo NMR monitoring of storage oils

2008· article· en· W2159529915 on OpenAlexafffund
Victor V. Terskikh, Ying Zeng, J. Allan Feurtado, Michael Giblin, Suzanne R. Abrams, Allison R. Kermode

Bibliographic record

VenueJournal of Experimental Botany · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsNational Research Council CanadaPlant Biotechnology InstituteSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThujaGerminationAccelerated agingReforestationBiologyBotanyChemistryHorticultureEcology

Abstract

fetched live from OpenAlex

Deterioration of conifer seeds during prolonged storage has a negative impact on reforestation and gene conservation efforts. Western redcedar (Thuja plicata Donn ex D. Don) is a species of tremendous value to the forest industry. The seeds of this species are particularly prone to viability losses during long-term storage. Reliable tools to assess losses in seed viability during storage and their underlying causes, as well as the development of methods to prevent storage-related deterioration of seeds are needed by the forest industry. In this work, various imaging methods and biochemical analyses were applied to study deterioration of western redcedar seeds. Seedlots that exhibited poor germination performance, i.e. those that had experienced the greatest losses of viability during prolonged storage, exhibited greater abundance of oxidized proteins, detected by protein oxidation assays, and more pronounced changes in their in vivo (13)C NMR spectra, most likely due to storage oil oxidation. The proportion of oxidized proteins also increased when seeds were subjected to accelerated ageing treatments. Detection of oxidized oils and proteins may constitute a reliable and useful tool for the forest industry.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.154

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 head0.027
GPT teacher head0.264
Teacher spread0.237 · 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

Citations36
Published2008
Admission routes2
Has abstractyes

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