Impacts of pathogen strain and barley cultivar on Fusarium head blight in barley and during malting
Bibliographic record
Abstract
Abstract Fusarium head blight (FHB) is a devastating disease in barley, causing significant losses for the malting and brewing industries. We hypothesized that the variation observed in Fusarium ‐related issues during malting may be partially attributable to differences among Fusarium graminearum strains. Field trials in 2019–2021 used barley cultivars with different FHB resistance: Newdale (intermediate) and AAC Goldman (moderately resistant). Barley plants were grown under disease‐conducive conditions, and plots were inoculated with conidial suspensions of each of seven different F. graminearum monoclonal isolates plus a noninoculated control. Disease severity (as a percentage of symptomatic spikelets) significantly differed among years (2020 > 2019 > 2021). F. graminearum density in barley varied significantly across years (2019 > 2021 > 2020). Pathogen strain identity and cultivar (Newdale > AAC Goldman) had significant effects on F. graminearum density in barley grain. The harvested barley was micromalted. The deoxynivalenol (DON) content in barley and malt significantly differed among years and cultivars, with the highest levels in 2019 and in Newdale. Pathogen strain identity significantly influenced DON content in barley and malt. F. graminearum density in malt showed significant variation among years (2021 > 2019 > 2020) and was influenced by the pathogen strain identity, while cultivar did not significantly affect F. graminearum density in malt. Gushing varied significantly across years but was not affected by cultivar or pathogen strain identity and was independent of F. graminearum density. Our finding that F. graminearum strain identity altered impact in barley grain and malt may explain the variability of FHB impacts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".