PSVI-9 Occurrence of mycotoxins in US forage grasses
Bibliographic record
Abstract
Abstract Initial survey of standing pastures in the southern United States investigated the occurrence of mycotoxins in grasses. Zearalenone (ZEN), an endocrine disruptor, was the most prevalent mycotoxin and is a potential threat to reproductive performance in grazing livestock. The ongoing survey expanded to cover a greater geographic area and additional grass species, as well as hay and preserved forages, were included in the survey to further investigate the presence of mycotoxins in US grasses. Fresh pasture samples were hand-plucked (25–30 subsamples per pasture) to simulate cattle foraging behavior and composited for analysis. Baled forages were sampled using a probe and other preserved forages were collected via grab samples from the face of bags or silos. Samples were screened for the presence of mycotoxins at Activation Laboratories (Ancaster, Ontario, Canada; 16 mycotoxins) or Romer Labs (Union, MO; 17 mycotoxins) via liquid chromatography tandem mass spectrometry method. Parameters of the main mycotoxins detected are presented on a dry basis in parts per billion (ppb) in Table 1. A total of 415 samples were collected March 2016 through February 2019 primarily from southern states (FL, TX, AL, GA, LA). One or more mycotoxins were detected in 286 samples (68.9%). ZEN was detected most frequently across all samples (60.0%; 1428.4 ± 181.3 ppb) with type A trichothecenes (A-Trich; including T-2 toxin & HT-2 toxin; 16.6%; 1139.5 ± 647.2 ppb) and type B trichothecenes (B-Trich; including deoxynivalenol, nivalenol, and fusarenon X; 9.6%; 1230.9 ± 522.9 ppb) being the next most prevalent toxin group. These survey results suggest a variety of mycotoxins occur in multiple grass species and can be detected from fresh pasture as well as in hay and other preserved forages. The types and concentrations of mycotoxins detected may pose challenges to livestock reproduction, health, and performance even when consuming high forage diets.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".