Pigs receiving daily tailored diets using precision-feeding techniques have different threonine requirements than pigs fed in conventional phase-feeding systems
Bibliographic record
Abstract
There is large variation in amino acids requirements among pigs, hence feeding pigs individually with daily tailored diets or in groups with a single feed may require different levels of nutrients. Thus, the response to different threonine levels (70%, 85%, 100%, 115%, and 130% of the ideal threonine:lysine protein ratio of 0.65) was studied in growing pigs raised in a conventional group phase-feeding (GPF) system or fed individually using individual precision-feeding (IPF) techniques. In a 21-day trial, 110 barrows (25 ± 0.80 kg body weight) were housed in the same room and fed using electronic feeders. Five pigs per treatment were slaughtered at the end of the trial. Threonine intake increased linearly for the IPF and GPF pigs ( P < 0.05). Lysine intake was similar across the treatments. Average daily gain, gain:feed ratio, and protein deposition were affected linearly by threonine level ( P < 0.05) in both feeding systems. Protein deposition in the GPF pigs was maximized at 150 g/d and a 0.65 threonine:lysine ratio, whereas protein deposition increased linearly in the IPF pigs. Plasma Met and serine levels were 11 and 7% higher, respectively, in the IPF pigs than in the GPF pigs ( P < 0.05). Dietary threonine increased ( P < 0.05) threonine concentration in the longissimus dorsi in a quadratic manner in the IPF pigs, whereas there was no effect in the GPF pigs. Longissimus dorsi collagen decreased as dietary threonine increased in the IPF and GPF pigs ( P < 0.10). Carcass muscle crude protein was 2% higher in the GPF pigs than in the IPF pigs ( P < 0.05). Individual pigs are able to modulate growth and the composition of growth according to threonine intake. The average amino acid ratio value that is currently used for GPF cannot be used for IPF.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".