Impact of field fungal contamination of barley on ensiling properties, nutritional quality and the microbiome of barley silage
Bibliographic record
Abstract
Abstract Barley varieties of differing fungal disease resistance were grown in triplicate plots at Lacombe and Lethbridge, Alberta with the disease resistant variety (FR) sprayed with a foliar fungicide to maximize differences in field fungal disease. Both varieties were harvested at soft dough and ensiled in minisilos to assess differences in fungal contamination on ensiling properties, nutritional quality, aerobic stability and associated bacterial and fungal microbiomes. Data were analysed as repeated measures with the effect of treatment × time (duration of ensiling or aerobic exposure) included in the model. The percentage leaf area diseased by net form net blotch was higher (p < 0.05) in the untreated barley cv. Sundre (UN, 59.1% leaf area affected at Lacombe and 25.2% at Lethbridge) than in the FR barley cv. Chigwell (0.7% leaf area affected at Lacombe and 0.1% at Lethbridge). Fungal resistant barley had a lower (p < 0.01) acid and neutral detergent fibre content. Relative abundance of Xanthomonadales was higher (p = 0.02) for FR than UN, while Lactobacillales dominated the bacterial microbiome after 60 day of ensiling in both silages. Bacillales dominated both FR and UN after 21 day of aerobic exposure. Fungal resistant fresh barley forage had a tendency (p = 0.10) for a greater relative abundance of Pleosporales, while UN had higher (p < 0.01) Hypocreales. Mould counts were lower (p = 0.01) for FR than UN after 7 day of ensiling. Fungal resistant barley had minimal influence on the fungal community that contributed to the aerobic deterioration of barley silage.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".