PSXV-7 Nutrient Digestibility Evaluation in Finisher Pigs from Diverse Feed Efficiency Groups
Bibliographic record
Abstract
Abstract Feed efficiency (FE) is a critical trait in swine production to improve the overall production efficiency and profitability and is an important goal for pig breeding companies. FE is a complex trait involving utilization and storage of dietary nutrients in different organs, and more especially in skeletal muscles. However, whether nutrient digestibility in the pig is altered by genetic selection for FE is less clear. Thus, this study investigated the variation in apparent total tract nutrient digestibility (ATTD) in finisher boars selected for high (HFE) or low (LFE) FE within a Large White dam and sire line. A total of 130 boars were selected at 23 wk of age based on their genomic-enabled breeding value for FE and fed ad libitum a corn-soybean meal-based diet using feeding stations that recorded individual feed intake and body weight. Fecal and diet samples were analyzed for dry matter, neutral detergent fiber, acid detergent fiber, crude protein (CP), energy, ash, phosphorus, and calcium to determine ATTD using acid-insoluble ash as an indigestible marker. There was no difference in ATTD values between genetic lines (P > 0.10). However, HFE pigs had greater (P = 0.03 ATTD of CP compared with LFE pigs. Based on the estimated protein deposition and the average feed intake one week before sampling, calculated dietary digestible lysine content diet met the requirements for the average pig. However, HFE pigs had a reduced feed intake, implying that they might have experienced a shortage of lysine in the diet. It is unclear whether the improved ATTD of CP was due to a lysine-shortage or differences in genetic merit for FE.
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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 | 0.001 | 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 | 0.000 |
| 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".