23 Evaluation of further processed soy protein sources on growth performance of nursery pigs fed a low complexity diet
Bibliographic record
Abstract
Abstract An experiment was conducted to evaluate various further processed soy protein sources on growth performance of nursery pigs. The sources evaluated included a hydrothermal mechanical processed (HTM) SBM (ProvisoyTM, Cargill, USA), an enzymatically modified (ENZ) SBM, a fermented (FM) SBM, and a soy protein concentrate (SPC). In total, 1,840 weaned pigs [6.4 ± 0.2 kg initial body weight (BW)] were allotted to 18 replicate pens per treatment (23 pigs per pen) in 2 barns. Pens were blocked by location within barn and randomly allotted to 4 treatments (HTM, ENZ, FM, and SPC). A low complexity diet with 22.5 and 30% conventional SBM in phase 1 (d 0-10) and 2 (d 10-22), respectively, and limited inclusion of highly digestible protein ingredients and health promoting additives was used as the basal diet. Soybean meal and SID Lys levels were constant across diets within phases by adjusting the levels of HTM, ENZ, FM, and SPC. Pigs were fed a common phase 3 diet during the last phase (d 22-39). Pig and feed weights were recorded at the beginning and end of each phase. Data were analyzed using the lme4 package of R 4.1.2, and the statistical model included the fixed effect of treatment, as well as the random effects of barn and location within barn. Mortality and removals were analyzed as generalized linear mixed models, with a binomial distribution. Contrasts were used to evaluate the effects of HTM vs ENZ, HTM vs FM, and HTM vs SPC. Results indicate that overall body weight, average daily gain, and average daily feed intake did not differ among treatments, but HTM tended to improve (P < 0.10) overall gain:feed compared to SPC and numerically reduced mortality and removals by 1.7% compared to FM. In conclusion, in a low complexity diet, pigs fed further processed soy protein, regardless of source, ended the trial with similar growth performance. However, feeding HTM resulted in numerically lower mortality and removals compared to FM.
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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 | 0.000 |
| 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".