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Record W2060433765 · doi:10.2135/cropsci2014.05.0405

Black Barley as a Means of Mitigating Deoxynivalenol Contamination

2015· article· en· W2060433765 on OpenAlexafffundabout
Thin Meiw Choo, B. Vigier, Marc E. Savard, Barbara A. Blackwell, Richard A. Martin, Junmei Wang, Jianming Yang, El‐Sayed M. Abdel‐Aal

Bibliographic record

VenueCrop Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsUniversity of Prince Edward IslandAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsBiologyHordeum vulgareMycotoxinInoculationHorticultureAgronomyCultivarFusariumPlant disease resistancePoaceaeBotany

Abstract

fetched live from OpenAlex

ABSTRACT Fusarium head blight (FHB) is a destructive disease of barley ( Hordeum vulgare L.) in many countries. The disease can result in mycotoxin contamination such as deoxynivalenol (DON) in the grain. The objective of this study was to determine if black barley is more resistant to DON accumulation than yellow barley as the former contains a high level of phenolic compounds. In one experiment, 100 recombinant inbred lines (RILs) were derived from each of the two barley crosses: AC Klinck/CH9403‐2 and AC Legend/CH9403‐2 with half of them being black and the other half yellow. These lines along with their parents were evaluated for resistance to DON accumulation under natural infection conditions at Harrington (Prince Edward Island) for 3 yr (2005–2007). They were also evaluated for resistance to FHB incidence and DON accumulation under artificial inoculation conditions at Ottawa (Ontario) in 2005 and 2006 and at Hangzhou (China) in 2005–2006. Black RILs on average contained 17 to 59% less DON than yellow RILs under natural conditions in both crosses in two tests. Black RILs had 2 to 20% lower FHB incidence than yellow RILs in both crosses in two tests and contained 16 to 18% less DON in one test. In another experiment, 26 hulless accessions were evaluated at Ottawa in 2011 and 2012. Black accessions on average contained 53% less DON than the yellow accessions in 2012 and they contained 46% less DON when the DON data were combined over 2 yr. In conclusion, black barley can be used as a means of mitigating DON contamination.

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)0.001
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 score0.210
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.249
Teacher spread0.218 · 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

Citations18
Published2015
Admission routes3
Has abstractyes

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