Oregano essential oil improves piglet health and performance through maternal feeding and is associated with changes in the gut microbiota
Bibliographic record
Abstract
BACKGROUND: With a growing demand for safe and sustainable alternatives to antimicrobials, functional feed ingredients such as plant essential oils have been evaluated for their potential to improve gut health. Amongst these, oregano essential oil (OEO) with the main active compounds carvacrol and thymol has been reported to have antimicrobial and antioxidative properties resulting in improved intestinal barrier function and growth in pigs and poultry. However, its impact on the gut microbiota still remains unclear. The aim of this study was to examine the effect of an oregano essential oil phytobiotic on sow and piglet performance and faecal microbiota. RESULTS: Piglets from OEO supplemented sows were significantly heavier at one week of age and showed a trend for improved average daily weight gain from birth to weaning. Post-weaning, maternally supplemented piglets were numerically heavier at 10 weeks post-weaning and at slaughter with a reduced variability in bodyweight. Health records showed that piglets in the OEO supplemented litters had significantly reduced incidence of therapeutic treatment and reduced mortality. In both sows and piglets, the structure and composition of the faecal microbiota varied considerably over time. Sows supplemented with OEO during lactation showed an increase in the relative abundance of Lactobacillaceae family. In addition, there was an increase in the relative abundance of families known to be important in fibre digestion (Fibrobacteriaceae and Akkermansiaceae). Analysis of piglet microbiota at two weeks and four weeks of age revealed a relative decrease in Enterobacteriaceae while butyrate producers (Lachnospiraceae family) were increased at both timepoints. CONCLUSION: We hypothesise that the effects observed from this study were exerted through modulation of the gut microbial communities in the sow and her offspring through maternal microbial transfer. Understanding the link between the gut microbiota and dietary factors represents a keystone to improving health and performance for sustainable pig production. Reducing antimicrobial usage can help to reduce the risk of antimicrobial resistance (AMR) which is a global focus for animal production.
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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 | 0.001 |
| 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".