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Record W2560183905 · doi:10.2135/cropsci2016.04.0263

Is Deoxynivalenol Contamination a Serious Problem for Oat in Eastern Canada?

2016· article· en· W2560183905 on OpenAlexaffabout
Weikai Yan, Denis Pageau, Richard A. Martin, Allan Cummiskey, Barbara A. Blackwell

Bibliographic record

VenueCrop Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsHealth PEIAgriculture and Agri-Food Canada
FundersCenters for Disease Control and Prevention
KeywordsCultivarAvenaBiologyContaminationFusariumAgronomyMycotoxinPoaceaeHorticultureBiotechnologyEcology

Abstract

fetched live from OpenAlex

To assess the severity of deoxynivalenol (DON) contamination in oat ( Avena sativa L.) grain from infection of Fusarium head blight in eastern Canada, DON were determined for 3243 oat grain samples, involving 160 oat genotypes tested in 87 year–location combinations in Quebec and Atlantic Canada (Maritimes) oat registration and recommendation trials from 2008 to 2015. Analysis of the data led to the following findings. First, there are repeatable genetic differences in DON contamination. Relatively resistant cultivars (e.g., ‘CDC Dancer’) and susceptible cultivars (e.g., ‘AC Rigodon’) were identified. Genotypes better than CDC Dancer or worse than AC Rigodon were also identified. Second, cultivars with less DON contamination tended to have thinner hulls, i.e., greater groat percentage. Third, oat grain produced in Quebec and Maritimes was generally safe for use as feed or food, according to the Canadian permissible DON limits. In about 16% of the trials, however, the grain may not be suitable for making infant food according to the EU limit. Using a resistant cultivar such as CDC Dancer can reduce this risk to 10%, while using a susceptible cultivar such as AC Rigodon can increase the risk to 21%. Breeding for Fusarium head blight resistance, as measured by less DON contamination, should be a component in oat breeding for the region.

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 score0.639
Threshold uncertainty score0.990

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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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