Deoxynivalenol-3-Glucoside Content Is Highly Associated with Deoxynivalenol Levels in Two-Row Barley Genotypes of Importance to Canadian Barley Breeding Programs
Bibliographic record
Abstract
Barley (Hordeum vulgare L.) is a multipurpose crop that can be harvested as grain or cut prior to maturity for use as forage. Fusarium head blight (FHB) is a devastating disease of barley that reduces quality of grain. FHB can also result in the accumulation of mycotoxins such as deoxynivalenol (DON). Breeding FHB resistant varieties has been a long-term goal of many barley-producing countries, including Canada. While the genetic basis of DON detoxification via production of less-phytotoxic conjugates such as DON-3-glucoside (DON3G) is well documented in barley, little information exists in reference to varietal response. Over two years, 16 spring, two-row barley genotypes, of importance to western Canadian barley breeding programs, were grown as short-rows and inoculated following spike emergence with a Fusarium graminearum conidia suspension. Half of the plots were harvested at soft dough stage and then dissected into rachis and grain components, whereas the remainder was harvested at maturity. Multiple Fusarium-mycotoxins were assayed using liquid chromatography-mass spectrometry. Mycotoxin content was elevated at the earlier harvest point, especially in the rachis tissue. DON3G constituted a significant percentage (26%) of total trichothecene content and thus its co-occurrence with DON should be considered by barley industries. DON3G was highly correlated with DON and 3-acetyl-deoxynivalenol (3ADON). The ratio of D3G/DON exhibited consistency across genotypes, however more-resistant genotypes were characterized by a higher ratio at the soft-dough stage followed by a decrease at maturity. Plant breeding practices that use DON content as a biomarker for resistance would likely result in the development of barley cultivars with lower total DON-like compounds.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".