Feed efficiency and fecal microbiome of nursery pigs from parents with divergent breeding value for feed conversion ratio
Bibliographic record
Abstract
Abstract Improving feed efficiency (FE) is essential for the swine industry’s economic and environmental sustainability. Genetic selection, particularly through estimating breeding values for feed conversion ratio (EBV_FCR), is a common strategy to enhance FE. However, the biological mechanisms underlying phenotypic variations in FE between pigs with different EBV_FCR values are not fully understood. This study investigates these mechanisms by examining growth performance, nutrient and energy digestibility, and fecal microbiota composition and functionality of pigs at the nursery stage. The study involved 128 pigs, weaned at 21 d (±2 d) and with an initial body weight of 6.87 kg (±0.34 kg). These pigs, selected from dam and sire lines with divergent EBV_FCR values, were randomly assigned to 32 pens with four pigs each. Pigs were fed a corn and soybean meal-based diet, divided into two feeding phases of 2 wk each, under similar rearing conditions. Results indicated no significant differences in average daily feed intake (ADFI), average daily body weight gain (ADG), or feed efficiency (FE, gain:feed) between pigs from different EBV_FCR lines (P > 0.05). Similarly, nutrient digestibility showed no significant variation (P > 0.05). While the overall fecal microbiota taxonomic composition was similar between the groups, there was a trend toward higher beta diversity in the microbiota of pigs from parents with lower EBV_FCR (high efficiency pigs, H pigs) (P < 0.083). Carbohydrate and amino acid metabolism were predominant in all pigs, regardless of genetic background, with similar predicted microbiota functionality across groups. The study concluded that genetic differences based on parents divergent EBV_FCR did not affect growth performance, nutrient utilization, or microbiota characteristics at the nursery stage. This suggests that while EBV_FCR based genetic selection does not impact early-stage performance or microbiome responses, its effects may differ in older pigs, warranting further research.
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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 | 0.000 | 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".