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Record W4385603140 · doi:10.3390/toxins15080497

The Impact of Storage Temperature and Time on Ergot Alkaloid Concentrations

2023· article· en· W4385603140 on OpenAlexafffund
Jensen E. Cherewyk, Taylor J. Grusie-Ogilvie, Sarah Parker, Barry Blakley, Ahmad Al‐Dissi

Bibliographic record

VenueToxins · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsShared HealthUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlkaloidChemistryEnvironmental scienceStereochemistry

Abstract

fetched live from OpenAlex

Ergot sclerotia produce toxic secondary metabolites, ergot alkaloids, that infect cereal crops and grasses. Ergot alkaloids have two isomeric configurations: the C-8-R-isomer (R-epimer), and the C-8-S-isomer (S-epimer). Ergot contaminated matrices, such as cereal grains or grasses, may be stored for extended periods at various temperatures before being analyzed, utilized, or consumed. This study assessed the concentration of six common ergot alkaloids in both configurations found in naturally contaminated wheat over time (one, two, and four months) at different temperatures (room temperature, +4 °C, and −20 °C) using ultra-high-performance liquid chromatography–tandem mass spectrometry. The data indicate that the total ergot concentration within a natural contaminated sample varies over time at room temperature, +4 °C, and −20 °C. The total ergot concentration increased until month two, and decreased at month four, independent of temperature (p < 0.05). The total R-epimer concentration appeared to be less stable over time than the total S-epimer concentration. The changes in the total R and total S-epimer concentrations may have been caused by changes in the ergocristine and ergocristinine concentrations, respectively. Time and temperature should be considered when storing potentially contaminated matrices in a laboratory or practical agriculture situations. Quantification of ergot contaminated matrices should occur prior to their use to ensure the most reliable estimates of the concentration of ergot.

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 score0.950
Threshold uncertainty score0.160

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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