Effects of High-Grain Diet on the Quality of Meat and Carcass of Lambs and Economic Indices of Various Diets
Bibliographic record
Abstract
The Brazilian sheep farming sector suffers from low productivity, related to the extensive animal production system and low availability of native fodder during most of the year. An alternative to the systems would be the use of a diet without roughage, allowing greater weight gain and better quality carcasses. The aim of this study was to investigate the effects of diets containing different proportions of grains on the quality of carcass and meat of lambs as well as the economic indices of various diets. Three diets containing different proportions of concentrate and roughage (100:0, 80:20, and 60:40) were supplied. The concentrate comprised 85% whole-grain corn and 15% commercial pelletized supplement. Twenty-four male lambs (no racial pattern; average body weight, 20.9 ± 1.0 kg; age, 6 months) were randomly allotted to three collective bays for 52 days. Subsequently, the animals were slaughtered, and further analyses were performed. The diet with 100% concentrate achieved overall higher carcass yield, lower weight loss on cooking, and greater lipid oxidation. However, no diet affected weight gain, slaughter weight, carcass length and thorax depth, pH, temperature, color, water-holding capacity, and meat shear force (P > 0.05). The best economic indices were obtained with the diet containing 100% concentrate. Therefore, based on the results obtained, the use of 100% concentrated diet for lambs is the most suitable practice to improve the sheep production from a productive and economic point of view.
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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 | 0.002 | 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) | 0.000 | 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".