Improving the bioavailability of manganese and meat quality of broilers by using hot-melt extrusion nano method
Bibliographic record
Abstract
1. Mineral excretion is an issue in the poultry industry. The use of micro minerals in nano form can increase bioavailability and decrease excretion rate. However, information concerning the bioavailability of nano manganese (Mn) in broiler chicks is limited.2. This experiment studied the influences of hot-melt extrusion (HME)–processed manganese sulphate on body weight gain, Mn bioavailability, nutrient digestibility and meat quality in broiler chicks fed a corn-soybean meal-based diet as a starter and grower phase. A total of 700 birds (Ross 308, 1-day-old) were randomly placed in 35 cages (20 birds per cage). The broiler chicks were fed one of seven experimental diets, which consisted of a control (without supplemental Mn), different levels of MnSO4 (IN-Mn60; 60, 120, and 200 mg/kg), or HME MnSO4 (HME-Mn; 60, 120, and 200 mg/kg).3. There was an increased serum Mn content in broilers fed diet supplemented with HME-Mn. In the grower phase, increased dietary Mn levels elevated the concentrations in the serum, liver, and tibia. There were increases in the excreta Mn content of broilers fed increasing levels. The supplementation of HME-Mn showed a lower percentage of abdominal fat compared with the IN-Mn treatment diets. Supplementation with HME-Mn decreased intramuscular fat compared with the diets supplemented with IN-Mn. The supplementation of HME-Mn decreased the thiobarbituric acid reactive substances (TBARS) at d 6 of age. The HME-Mn source showed a greater decrease in TBARS compared with the IN-Mn treatment.4. In conclusion, HME processing increased bioavailability and could be used as an environmentally friendly method to facilitate lower levels of Mn in the diet of broiler chickens.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".