424 Mycotoxin Survey of Southern US Pasture Grasses.
Bibliographic record
Abstract
A survey was conducted to explore the occurrence of mycotoxins in Southern US pasture grasses. Zearalenone (ZEN) in common Bermudagrass (Cynodon dactylon) was initially identified as a major challenge in South Central Florida. The ongoing survey was expanded to represent a greater geographic area and additional grass species to further investigate the existence of mycotoxins in standing forages across the Southern US. Grass samples were hand-plucked to simulate cattle foraging behavior. Subsamples (25–30 per pasture) were composited and screened for the presence of mycotoxins at Activation Laboratories (Ancaster, Ontario, Canada; 15 mycotoxins) or Romer Labs (Union, MO; 17 mycotoxins) via the liquid chromatography tandem mass spectrometry method. Mycotoxin levels for positive samples are presented on a dry basis in parts per billion (ppb). A total of 297 samples were collected from March 2016 through February 2018. Overall, one or more mycotoxins were detected in 205 samples (69.0%). Zearalenone was the predominant mycotoxin detected across grass species (61.6% overall; Table 1). In addition to ZEN, type B trichothecenes (B-Trich; including deoxynivalenol, nivalenol, and fusarenon X) were detected in 12 limpograss samples (80%; mean of positives 3293 ppb). Few bermudagrass samples (3.3%; mean 200 ppb) had detectable levels of B-Trich, but type A trichothecenes (T-2 or HT-2 toxin) were detected in 43 (15.9%; mean 1492 ppb) of those samples. Preliminary results of the survey indicate that various mycotoxins can occur in several species of Southern pasture grasses at levels which may pose challenges to livestock reproduction, health, and performance. Additional research is needed to better understand the potential challenge mycotoxins may pose to grazing livestock.
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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 | 0.000 | 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".