Utilising yellow mealworm larvae reared on deoxynivalenol-contaminated wheat as a feed ingredient for poultry diets
Bibliographic record
Abstract
This study determined if yellow mealworm larvae (YML) grown on deoxynivalenol (DON) contaminated wheat would affect broiler chicken performance. The YML were reared on wheat with low (LDW; 630 μg/kg) or high (HDW; 30,730 μg/kg) DON concentrations. The DON concentrations in the dried insect meals were 0 or 17.5 μg/kg for YML grown on LDW and HDW, respectively. Seventy-five male Ross 708 broilers were randomly placed into 15 cages and reared on one of three diets from day 1-35 (five replications/treatment). On day 14, broiler numbers were reduced to four per cage. The diets consisted of a control containing no YML meal (CD) and two diets containing 5% YML meal produced on either LDW (LMD) or HDW (HMD). Feed intake and body weight (BW) were measured over the duration of the experiment to calculate feed to gain ratio (F:G). On day 35, all birds were slaughtered and dissected to collect weights of the breasts, thighs, drums, wings, abdominal fat pads, and organs. Crude protein retention was higher in birds fed the LMD and HMD treatments compared to CD (P=0.0091). Dry matter retention was higher in the HMD diet compared to the CD and LMD diets (P=0.0046). Feed intake was lower in birds fed HMD compared to CD and LMD (P=0.0031) although final BW was not reduced. In conclusion, dietary inclusion of YML did not affect the growth, meat yield or organ weights of the birds. The YML reared on DON-contaminated wheat (up to 30,730 ug/kg) and included in broiler diets at 5% could be an effective means of converting salvage wheat into a safe and sustainable source of protein.
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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".