Deoxynivalenol Removal from Barley Intended as Swine Feed through the Use of an Abrasive Pearling Procedure
Bibliographic record
Abstract
Samples of naturally contaminated hulled barley, with varying deoxynivalenol concentrations, were subjected to an abrasive type dehulling procedure. The remaining grain fractions were analyzed for weight remaining (%), deoxynivalenol (ppm), crude protein (%CP), neutral detergent fiber (%NDF), ash (%ASH), gross energy (GE; kcal/kg), and calculated digestible energy values (DE; kcal/kg). Following the initial 15 s of pearling, 85% of the grain mass remained. Additional pearling resulted in a linear decline of grain mass. Following 15 s of pearling, the grain contained 34% of the initial deoxynivalenol content, irrespective of the initial level of contamination. Further pearling resulted in continued significant (p < 0.05) reductions in the percent of deoxynivalenol remaining to a level of 7.9% after 120 s but with significant losses in grain mass. Pearling can serve as an effective means of reducing the deoxynivalenol content of barley, with improvements in nutrient levels. However, the need to reduce the deoxynivalenol content of contaminated barley to less than 1 ppm for swine will necessitate the removal of a significant amount of the grain mass for heavily contaminated samples.
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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 | 0.000 | 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".