Management of Fusarium graminearum and its mycotoxins in Ontario maize
Bibliographic record
Abstract
In the Great Lakes region of North America, gibberella ear rot (GER), caused by Fusarium graminearum Schwabe, affects grain quality due to the production of mycotoxins, resulting in multi-million-dollar losses annually. The management of GER requires an integrated approach using prediction tools, agronomic practices, genetics, and fungicides. The objective of this research was to determine effective management strategies for F. graminearum in grain maize in Ontario. Specifically, the efficacy of fungicides, including a novel carboxamide fungicide (pydiflumetofen), was evaluated for management of mycotoxin accumulation in small misted plots and field experiments from 2017 to 2019. The optimal fungicide application time was also investigated. The impact of agronomic practices such as plant population density, the effect of plant stress caused by in-row-plant developmental variability, and the effect of incorporated refuge genetics on mycotoxin accumulation was also investigated in small misted-plots in 2019 and 2020. A survey was conducted on F. graminearum isolates from southwestern Ontario to determine the mycotoxin profile and the range of sensitivity of strains isolated from wheat kernels, maize kernels and overwintering maize stalks to fungicides currently recommended to manage GER and fusarium head blight (FHB). The results show that the highest efficacious fungicide timing to reduce mycotoxin accumulation and GER severity was at full silk stage. Relatively high plant population densities and in-row-plant developmental variability increased mycotoxin concentrations because of plant competition rather than environmental conditions, highlighting the importance of reducing plant competitive stress as a strategy to reduce mycotoxin concentrations. In this study, there was no l difference in DON accumulation between the Bt component and the non-Bt component in each of four not-Bt refuge-incorporated hybrids tested. However, there was evidence that hybrids varied in susceptibility to mycotoxins. Lastly, the majority of isolates in Ontario are able to produce both 3ANX and 15ADON. The chemotype was not affected by isolate source (wheat grain, maize grain, maize stalks) and all isolates tested were sensitive to the main fungicides used to manage GER and FHB in Canada.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 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 source (direct Gemma or distilled Codex), 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".