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Record W2239932375 · doi:10.1094/asbcj-64-0001

Quality Risks Associated with the Utilization of Fusarium Head Blight Infected Malting Barley

2006· article· en· W2239932375 on OpenAlexaboutno aff
Paul Schwarz, Richard D. Horsley, Brian J. Steffenson, Bacilio Salas, John R. Barr

Bibliographic record

VenueJournal of the American Society of Brewing Chemists · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsnot available
Fundersnot available
KeywordsFusariumAgronomyBiologyHorticulture

Abstract

fetched live from OpenAlex

Fusarium head blight (FHB) has adversely affected the quality of barley grown in the northern Great Plains of the United States and the eastern Prairie Provinces of Canada since 1993. Objectives of this study were to document the occurrence of deoxynivalenol (DON) on barley within North Dakota and Minnesota, investigate relationships among FHB, DON, and malt quality, and to determine at what level FHB/DON-contaminated barley can be safely utilized for the production of quality malt. Since 1993, mean DON levels have ranged from 10.3 to 0.4 μg/g, with a corresponding 81 to 32% of the regional barley crop in excess of 0.5 μg/g. Strong relationships were not observed between either kernel size or kernel weight and DON. As a consequence, cleaning is unlikely to achieve significant reductions in DON levels in most cases. In terms of barley and malt quality, the strongest relationships were observed between barley DON and malt DON and malt DON and wort color. However, malt DON levels could not be reliably predicted from barley at <1.0 μg/g. Barley with a DON level of <1.0 μg/g produced acceptable malt.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.286
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations49
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Society of Brewing ChemistsSame topicMycotoxins in Agriculture and FoodFrench-language works237,207