213 Increased Standardized Ileal Digestible Isoleucine to Lysine Ratio Improved Feed Efficiency in Pigs Fed Distillers Dried Grains with Solubles from 11 to 80 kg
Bibliographic record
Abstract
Abstract An experiment was conducted to determine the impact of dietary SID Ile to Lys ratio on the performance pigs from 11 to 80 kg of BW. A total of 1,092 pigs (initial BW = 11.1, SEM = 0.6 kg; 14 pens/treatment; 13 pigs/pen) were used in an 80d trial with a randomized complete block design. Dietary treatments were in a 2 x 3 factorial arrangement containing 2 levels of DDGS (0 and 25%) and 3 levels of SID Ile/Lys (0.54, 0.58, and 0.62). Energy and nutrient levels of all treatments were formulated at equal levels that met or exceeded NRC (2012) requirements. The SID Ile/Lys ratio was controlled by crystalline Ile. The MIXED procedures of SAS 9.4 were employed for statistical analysis. Orthogonal contrasts were used to test for main effects of DDGS and SID Ile/Lys. In the results, formulating with 25% DDGS decreased FBW, ADG, and ADFI (P < 0.05) of growing pigs. The average FBW of treatments without and with 25% DDGS were 81.7 and 78.6 kg, respectively. The ADG of diets without and with DDGS were 0.88 vs 0.84 kg/d, respectively. The ADFI of treatments without DDGS were 1.85 kg/day, while the counterparts of treatments fed diets containing 25% DDGS were 1.79 kg/d. Feeding diets containing 25% DDGS tended to decrease Gain:Feed (0.477 vs. 0.472; P < 0.10). Increasing the level of SID Ile/Lys (from 0.54 to 0.62) linearly increased Gain:Feed in pigs fed diets containing 25% DDGS (0.467, 0.471, 0.477, respectively; P < 0.05). In summary, this study demonstrated feeding diets containing 25% DDGS decreased the performance of growing pigs by reducing ADG and ADFI. Greater SID Ile/Lys in diets may help reduce the negative impact of DDGS diets in grow-finishing pigs by improving feed efficiency.
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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 | 0.001 | 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 | 0.000 | 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".