Effects of dietary lysine level on the content and fatty acid composition of intramuscular fat in late-stage finishing pigs
Bibliographic record
Abstract
This study was conducted to investigate how dietary lysine level affects the intramuscular fat (IMF) content and fatty acid (FA) composition in late-stage finishing pigs. Nine crossbred barrows [94.4 ± 6.7 kg body weight (BW)] were randomly allotted to three treatment groups (n = 3). Three corn- and soybean-meal-based diets were formulated to meet the National Research Council (2012) requirements for various nutrients except for lysine, whose concentrations were 0.43%, 0.71%, and 0.98% (as-fed basis) for Diets 1 (lysine-deficient), 2 (lysine-adequate), and 3 (lysine-excess), respectively. After 5 wk of ad libitum access to diets, pigs were harvested and longissimus dorsi samples were collected. The IMF content and FA composition of the samples were analyzed by gas chromatography. Results showed that the IMF content of the muscle was increased linearly (P < 0.05) with decreasing dietary lysine level from 0.98% to 0.43%. Dietary lysine level altered the composition of FA, especially the unsaturated FA, in the muscle. Particularly, the percentages of C18:1 n-9 and total monounsaturated FA were higher, whereas the percentages of C18:2 n-6 and total polyunsaturated FA were lower, in the muscle of the pigs fed Diet 1. Collectively, dietary lysine deficiency increased the proportion of monounsaturated FA and decreased the proportion of polyunsaturated FA, which may benefit pork palatability.
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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 | 0.001 | 0.001 |
| 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".