Species diversity of Fusarium head blight and deoxynivalenol (DON) levels in western Canadian wheat fields and generating Leptosphaeria maculans isolates carrying single avirulent (Avr) genes
Bibliographic record
Abstract
Wheat and canola are two major economically important food crops grown in western Canada, accounting for billions of dollars in revenue. Fusarium head blight (FHB) in wheat and blackleg in canola are the most destructive diseases that cause economic losses annually. Both diseases are caused by fungal pathogens, where FHB is primarily caused by Fusarium graminearum, while Leptosphaeria maculans causes the blackleg disease. This project's first objective is to evaluate the Fusarium species diversity and deoxynivalenol (DON) levels in western Canadian wheat fields in 2019 and 2020. The analysis of deoxynivalenol (DON) revealed that spring wheat grain contained higher DON levels than winter wheat grain samples. Additionally, for spring wheat, a significantly lower DON content was found in the grain than in the chaff collected from the same wheat heads for both years. The species diversity analysis showed that F. graminearum was the most frequent Fusarium species found in the infected samples except the samples from Alberta, while the highest percentage of F. graminearum was found in the spring wheat samples from Manitoba. The analysis of chemotype diversity of infected samples showed that 3ADON is the dominant chemotype in FHB disease. For the blackleg disease, a growing concern among blackleg researchers is that resistance (R) genes are identified, the same gene as two different genes by two independent laboratories, as not all research laboratories use a standard set of well-characterized isolates. To standardize the R gene identification and novel R gene discovery, the second objective of this thesis is to develop a procedure to generate L. maculans isolates that only carry a single avirulent (Avr) gene. Mating between two L. maculans isolates showed less efficiency in achieving the above objective. Thus, gene editing with the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 was utilized. Seven transformed isolates displayed reduced virulence on the canola cultivar Westar, even though they were not mutated at the target gene.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".