Growth performance, carcass quality, meat quality and fatty acid composition of pigs fed diets
Bibliographic record
Abstract
Two hundred gilts and 200 barrows, housed within sex in pens of 25, were randomly allotted to two replications of four dietary treatments to determine the effects of incorporating 30, 20, 10 or 0% extruded soybeans (ESB), displacing a commercial protein supplement, in barley-based grower and finisher diets for pigs. Growth, feed intake and carcass quality of the pigs, and meat quality and fatty acid composition of the pork from a random subset of the pigs on test were determined. No sex × diet interactions were observed. ESB inclusion rate had no effect on growth rate; however, per-pen feed consumption decreased numerically with increasing ESB resulting in an improvement in feed efficiency. The 30% ESB inclusion rate increased carcass fat content (P < 0.05) compared with the control, whereas lean content was unaffected. Meat colour and marbling score were similar across all treatments whereas fat and lean firmness was reduced by the 30% ESB inclusion rate (P < 0.05) compared with all other treatments. Increasing ESB in the diet altered the fatty acid content of the pork by decreasing the amount of short-chain saturated and monounsaturated fatty acids and increasing the amount of long-chain polyunsaturated fatty acids (PUFA). The results of this study indicate that ESB can be used as the sole source of supplemental protein in barley-based diets for pigs with no detrimental effects on performance and minimal negative effects on carcass and meat quality. Alteration of fatty acid content of pork from feeding ESB has both positive and negative implications for consumer acceptance by increasing PUFA content while concomitantly increasing the risk of premature oxidation. Key words: Extruded soybeans, pigs, pork, growth, fatty acids, meat quality
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".