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Record W3203424296 · doi:10.3390/app11198960

Evolution of Fusarium Head Blight Management in Wheat: Scientific Perspectives on Biological Control Agents and Crop Genotypes Protocooperation

2021· article· en· W3203424296 on OpenAlexafffundabout
Antonia J. Powell, Vladimir Vujanovic

Bibliographic record

VenueApplied Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaSaskatchewan Wheat Development Commission
KeywordsFusariumCultivarAgronomyFungicideBiologyCropDisease controlBiological pest controlBiotechnologyAgroforestryGeographyHorticulture

Abstract

fetched live from OpenAlex

Over the past century, the economically devastating Fusarium Head Blight (FHB) disease has persistently ravished small grain cereal crops worldwide. Annually, losses globally are in the billions of United States dollars (USD), with common bread wheat and durum wheat accounting for a major portion of these losses. Since the unforgettable FHB epidemics of the 1990s and early 2000s in North America, different management strategies have been employed to treat this disease. However, even with some of the best practices including chemical fungicides and innovative breeding technological advances that have given rise to a spectrum of moderately resistant cultivars, FHB still remains an obstinate problem in cereal farms globally. This is in part due to several constraints such as the Fusarium complex of species and the struggle to develop and employ methods that can effectively combat more than one pathogenic line or species simultaneously. This review highlights the last 100 years of major FHB epidemics in the US and Canada, as well as the evolution of different management strategies, and recent progress in resistance and cultivar development. It also takes a look at protocooperation between specific biocontrol agents and cereal genotypes as a promising tool for combatting FHB.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.286

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 studies0.0000.000
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 head0.250
Teacher spread0.223 · 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

Citations34
Published2021
Admission routes3
Has abstractyes

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