67 Occurrence of Mycotoxins in Forage-Based Feeds from US and Canada
Bibliographic record
Abstract
Abstract Mycotoxins are secondary fungal metabolites that contaminate a variety of feedstuffs and are detrimental to animal health and productivity. The risk of broad-spectrum mycotoxin exposure is elevated for ruminants due to the complexity of their diets. This study investigated the occurrence and contamination levels of mycotoxins in forage-based feeds including corn silage, haylage (including various cuttings of multiple forage sources), and straw samples from across the US and Canada. Samples were screened for the six major mycotoxin groups: aflatoxins, type A trichothecenes, type B trichothecenes (B-Trich), fumonisins (FUM), zearalenone (ZEN), and ochratoxin A via LC-MS/MS technique. Samples submitted for clinical health or performance concerns were excluded from the data set. The B-Trich occurred most frequently (95% positive) among 92 corn silage samples harvested in 2019 followed by ZEN (34%) and FUM (9%). Mean contamination levels (parts per billion, ppb) on dry matter basis were 2,788 ppb, 456 ppb, and 194 ppb, respectively. Only 4% of silage samples were below the limit of detection (LOD) for all mycotoxins evaluated. Among 20 haylage samples from 2019 crop year, B-Trich were the most frequently detected, with 50% of samples positive at a mean concentration of 3,222 ppb. Twenty-one 2019 straw samples were submitted for analysis, with 100% testing positive for some level of B-Trich (mean 2,001 ppb) and 81% ZEN positive with an average of 640 ppb. Seventy-one percent of straw samples were positive for both B-Trich and ZEN. Preliminary mycotoxin survey results from US and Canada suggest B-Trich and ZEN are the most frequently occurring major mycotoxins in 2019 forage-based feed samples. Based on the frequency and levels of mycotoxin contamination identified in the current data set, continued analysis of forage-based feeds is warranted as mycotoxins pose a potential risk to the health, performance, and reproductive success of ruminants.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".