Mycotoxin determination in fungal contaminated Canadian silage toxic to dairy cows and goats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Silage has become a key component of year-long animal feed in Canada and parts of northern Europe. It provides several advantages to farmers over traditional feed components, such as increased digestibility, higher nutrient content and preservation of the forages to meet seasonal feeding demands. Some ensiled materials can contain toxic fungal metabolites resulting from ‘in field’ contamination. In addition, when improperly stored or exposed to air during the feedout stage, silage is highly susceptible to aerobic spoilage by yeasts and filamentous fungi resulting in lower nutrient value and further mycotoxin contamination. In this study, silage samples were collected from 25 Canadian dairy goat and cattle farms where animals experienced feed-related health issues. Twenty-six unique fungal species were isolated from these samples, with the majority being Penicillium . High resolution liquid chromatography tandem mass spectrometry (HRLC-MS/MS) was used to identify a total of 125 known mycotoxins and fungal secondary metabolites from these silage samples, many of which were not produced by the 26 isolated filamentous fungi grown in agar cultures. Various mycotoxins resulting from preharvest contamination were detected, including ergot alkaloids, fumonisins and trichothecenes, some in high concentrations. Toxins produced after harvest included roquefortine C, citrinin and penitrem A. This study reinforces the need for farmers to implement best management practices to minimise fungal contamination and the resulting mycotoxin deposition in their crop and stored feed to maintain animal health.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it