Concurrent selection for microbial suppression of<i>Fusarium graminearum</i>, Fusarium head blight and deoxynivalenol in wheat
Bibliographic record
Abstract
AIM: Identify biological agents that can both control Fusarium head blight (FHB) and reduce deoxynivalenol (DON) production. METHODS AND RESULTS: Concurrent screening methods were used to progressively select soil and food micro-organisms for the ability to suppress Fusarium graminearum, FHB and DON production. The micro-organisms were assessed using up to five assays including: a co-culture and dual-culture assay, an indirect impedance assay, a wheat floret assay, and two assays assessing DON production. Paenibacillus polymyxa W1-14-3 and C1-8-b gave the greatest inhibition of F. graminearum and reduction of DON production in greenhouse evaluations. Compared to a control treatment, they reduced disease severity by 56.5 and 55.4%, F. graminearum colonization of wheat heads by 58.8 and 62.4%, DON production by 84.8 and 89.4%, and increased 100-kernel weights by 56.6 and 66.9%, respectively. CONCLUSIONS: The concurrent selection has resulted in promising antagonists that may possess multiple modes of action, and have the ability to colonize wheat heads in controlled environments. SIGNIFICANCE AND IMPACT OF THE STUDY: A novel concurrent screening method was developed for selection of biocontrol agents for FHB. Two isolates of P. polymyxa were selected and identified. Their potential use as biocontrol agents for FHB is highlighted in this study.
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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".