Long-term steam conditioning is needed to maximize the nutritional value of expander-processed soybean expellers
Bibliographic record
Abstract
Two experiments were conducted to determine standardized ileal digestibility (SID) of amino acids (AA) and the concentration of metabolizable energy (ME) in non-heat-treated and heat-treated soybean expellers (L-0, L-12, and L-48). L-0 underwent short-term steam conditioning for 60 s, whereas L-12 and L-48 underwent short-term steam conditioning for 60 s and long-term steam conditioning for 12 or 48 min. All heat-treated soybean expellers were expander processed. In experiment 1, 10 ileal-cannulated barrows (54.22 ± 4.54 kg) were allotted to a replicated 5 × 4 Youden square design with eight replicate pigs per diet. Each source of soybean expellers was included in one diet, and a nitrogen-free diet was also used. Results indicated that the SID of AA in non-heat-treated soybean expellers was less (P < 0.01) than in heat-treated soybean expellers. In experiment 2, 40 barrows (17.52 ± 1.63 kg) housed in metabolism crates were allotted to a corn-based diet or four corn–soybean expellers diets. Feces and urine were collected with 5 d adaptation and 4 d collection periods. The ME in non-heat-treated soybean expellers was less (P < 0.01) compared with L-0, L-12, or L-48. In conclusion, the SID of AA and the ME in heat-treated soybean expellers were greater than in non-heat-treated soybean expellers.
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) | 0.000 | 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) | 0.001 | 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".