140 Effects of Dietary Inclusion of a Medium Chain Fatty Acid Blend and a Phytogenic Feed Additive on Growth Performance, Gut Health, and Mortality of <i>Escherichia Coli</i>-Challenged Pigs
Bibliographic record
Abstract
Abstract An experiment was conducted to test the hypothesis that supplementing diets with a blend of medium chain fatty acids (MCFA) and a phytogenic feed additive (Fresta Protect, Delacon, Linz, Austria), together or separately, would improve growth performance and stool quality of nursery pigs challenged with Escherichia coli (ETEC). A total of 200 pigs [5.52 ± 0.17 kg body weight (BW)] were weaned at 17 to 19 days of age, allotted to 40 pens (5 pigs/pen), and allowed to acclimate for 2 days before initiation of dietary treatments. Pens were blocked by BW and randomly assigned to 1 of 5 treatments: negative control (NC), NC + 55 mg/kg carbadox (Positive control; PC), NC + 1.0% MCFA, NC + 0.1% phytogenic, or NC + 1.0% MCFA and 0.1% phytogenic. All pigs were administered an oral gavage of 5 mL ETEC (blend of K88+ and F18+) with a final titer of 1010 CFU/pig on day 5 and 6. Body weights were recorded on days 0, 4, 11, and 18, whereas feed intake was recorded for the overall trial (day 0 - 18). Fecal scores were assessed daily on an ordered likert scale to determine the joint probability of more normal stool quality. Data were analyzed using the lme4 package of R 4.1.2, and the statistical models included the fixed effect of treatment and random effect of BW block. Growth performance data were assumed to be normally distributed, whereas mortality and stool quality were analyzed using generalized linear mixed models specifying binomial and multinomial distributions, respectively. Contrasts were used to test for effects of dietary additive (carbadox, MCFA, phytogenic, or MCFA and phytogenic) compared with NC (Table 1). Results indicated post-challenge BW, post-challenge and overall average daily gain (ADG), and overall gain:feed (G:F) were greater (P < 0.05) for PC than for NC. In the pre-challenge phase, dietary inclusion of MCFA reduced (P < 0.05) final BW and ADG compared with NC, but overall G:F was greater (P < 0.05) than NC when the MCFA blend was fed. Inclusion of the phytogenic increased (P < 0.05) ADG in the post-challenge period and G:F in the overall trial compared with NC. The combination of MCFA blend and phytogenic resulted in increased (P < 0.05) post-challenge final BW, post-challenge ADG, and overall ADG compared with NC. All treatments, except MCFA blend, tended (P < 0.10) to reduce mortality compared with NC. The PC, MCFA blend, and combination treatments resulted in a greater (P < 0.05) probability of normal stool quality than NC. In conclusion, supplementation of the phytogenic and the combination of MCFA with phytogenic improved growth performance and tended to reduce mortality of nursery pigs under ETEC challenge. Furthermore, the combination improved stool quality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".