Feed supplementation with red seaweeds, Chondrus crispus and Sarcodiotheca gaudichaudii, affects performance, egg quality, and gut microbiota of layer hens
Bibliographic record
Abstract
The aim of this study was to evaluate the effect of the inclusion of red seaweed supplementation to standard poultry diets on production performance, egg quality, intestinal histology, and cecal short-chain fatty acids in Lohmann Brown Classic laying hens. A total of 160 birds were randomly assigned to 8 treatment groups. Control hens were fed a basal layer diet; positive control hens were fed a diet containing 2% inulin; and 6 treatment groups were fed a diet containing one of the following; 0.5, 1, or 2% Chondrus crispus (CC0.5, CC1, and CC2, respectively) and one of the same 3 levels of Sarcodiotheca gaudichaudii (SG0.5, SG1, and SG2, respectively). Dietary supplementation had no significant effect on the feed intake, BW, egg production, fecal moisture content, and blood serum profile of the birds. The feed conversion ratio per gram of egg was significantly more efficient (P = 0.001) for CC2 and SG2 treatments. Moreover, SG1 supplementation increased egg yolk weight (P = 0.0035) and birds with CC1 supplementation had higher egg weight (P = 0.0006). The SG2 and CC2 groups had greater (P < 0.05) villus height and villus surface area compared with the control birds. Seaweed supplementation increased the abundance of beneficial bacteria [e.g., Bifidobacterium longum (4- to 14-fold), Streptococcus salivarius (4- to 15-fold)] and importantly reduced the prevalence of Clostridium perfringens in the gut of the chicken. Additionally, the concentrations of short-chain fatty acids, including acetic acid, propionic acid, n-butyric acid, and i-butyric acid, were significantly higher (P < 0.05) in CC and SG treatments than in the control. In conclusion, dietary supplementation using red seaweed inclusions can act as a potential prebiotic to improve performance, egg quality, and overall gut health in layer hens.
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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) | 0.000 | 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 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".