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Record W2109561014 · doi:10.7202/706119ar

Importance de l’intéraction entre les cultivars de blé et les souches du Fusarium graminearum dans l’évaluation de la résistance à la fusariose de l’épi

2005· article· fr· W2109561014 on OpenAlexvenueaboutno aff
Mathieu Dusabenyagasani, Richard C. Hamelin, J. Collin, Daniel Dostaler

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyCultivarHorticulture

Abstract

fetched live from OpenAlex

Des expériences factorielles ont été réalisées au champ à deux stations, le campus de l'Université Laval en 1991 et 1992 et la ferme de Saint-Louis-de-Pintendre en 1992 et 1993, pour préciser si le développement de la fusariose de l'épi du blé est influencé par l'interaction entre les cultivars et les souches du Fusarium graminearum . Neuf souches du F. graminearum ont été inoculées à onze cultivars de blé ( Triticum aestivum ) et un cultivar de triticale ( x Triticosecale ) représentatifs de la gamme de sensibilité à cette maladie au Québec. L'analyse de la variance combinée a mis en évidence des interactions significatives entre les cultivars, les souches et les environnements. Les interactions cultivars x souches et cultivars x environnements expliquent une faible proportion de la somme des carrés totale et n'entraînent pas de modifications majeures dans le classement moyen de la sensibilité des cultivars. Concernant l'interaction cultivars x souches, le classement moyen de la sensibilité des cultivars, notamment Casavant et Concorde, variait avec les souches. Cette recherche contre pour la première fois que l'importance relative des différentes interactions entre les souches, les cultivars et les environnements est comparable dans l'évaluation de la résistance à la fusariose de l'épi du blé.

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 categoriesMeta-epidemiology (narrow)
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 score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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.

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
Published2005
Admission routes2
Has abstractyes

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