PSIII-20 Impact of EnduraPig on Performance of PRRSV-Negative growing-finishing pigs
Bibliographic record
Abstract
Abstract A total of 479 weaned pigs [PIC Camborough × PIC 337; initial body weight (BW) = 26.8 kg; Porcine reproductive and respiratory syndrome virus, PRRSV-negative] were used to evaluate the effects of EnduraPig (PMI Additives), a patent-pending feed additive that has been designed to support health, performance, and immune function of pigs, on growth performance of growing-finishing pigs. Pigs were blocked by initial BW and gender and assigned to 48 pens, which were allotted to one of 4 dietary treatments (12 pens/treatment, 9-10 pigs/pen), including T1) Control, T2) EnduraPig 0.1% (EP low), T3) EnduraPig 0.2% (EP medium), and T4) EnduraPig 0.3% (EP high). The EnduraPig inclusion levels were reduced by one-half when pigs reached approximately 70 kg BW (d 42). A five-phase feeding program was used with all diets formulated on a corn-DDGS-soybean meal basis to meet the nutrient requirements of growing-finishing pigs. Analysis of variance for growth measures was performed using the MIXED Procedure of SAS (SAS 9.4), and polynomial contrasts were used to evaluate linear, quadratic, and cubic effects of the EP levels. Significant differences were declared at P ≤ 0.05 and trends at P ≤ 0.10. During d 0-72, feeding EnduraPig tended to improve average daily gain (ADG) (0.96, 0.97, 1.00, and 0.97 kg, respectively; cubic, P = 0.06) with the greatest ADG observed in EP medium. During d 72 to market, feeding EnduraPig increased ADG (1.13, 1.14, 1.18, and 1.17 kg, respectively; linear, P = 0.02), average daily feed intake (ADFI; 3.48, 3.42, 3.55, and 3.49, respectively; cubic, P = 0.02) and feed:gain (3.08, 3.00, 3.01, and 2.98, respectively; linear, P = 0.10). Overall (d 0-market), feeding EnduraPig enhanced ADG (1.02, 1.02, 1.05, and 1.03 kg, respectively; linear, quadratic, and cubic, P = 0.04, 0.09, 0.01), with the greatest ADG observed in EP medium resulting in a 4.0 kg greater market BW compared with the control (128.9, 129.2, 132.9, and 130.5, respectively; linear and cubic, P < 0.05). In addition, feeding EnduraPig numerically improved feed:gain (2.51, 2.48, 2.48, and 2.48, respectively; linear, P = 0.14). With respect to BW variation, feeding EnduraPig reduced the standard deviation in market BW (10.65, 8.06, 8.86, and 9.54 kg, respectively; quadratic, P < 0.05), with the greatest reduction from EP low and EP medium (by 24 and 17%, respectively) compared with the control. In summary, data from this study indicate that feeding EnduraPig at 0.2% from 27 kg to 70 kg BW and 0.1% from 70 to market improves growth performance and reduces BW variation of PRRSV-negative growing-finishing pigs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".