PSVI-9 Nutrient and energy digestibility of steam-exploded canola meal in cannulated grower pigs
Bibliographic record
Abstract
Abstract Nutrient digestibility is lower in canola meal (CM) than soybean meal due to its fiber matrix. High steam pressure processing may increase nutrient digestibility of CM in pigs. To explore, Brassica napus CM was processed at 700 or 1,100 kPa followed by sudden release of pressure to ambient and yielded steam-exploded CM7 and CM11, respectively. The CM, CM7, and CM11 were included at 40% in 3 test diets. An N-free diet was fed to pigs to measure basal endogenous losses of crude protein (CP) and amino acids (AA) and served as basal to measure energy digestibility of CM. Seven ileal cannulated grower pigs (initial BW, 29 kg) were fed the 4 diets over three 9-d periods in 2 Youden squares. Pigs were fed diets at 3.0 × maintenance (110 kcal of DE per kg of BW0.75). Compared to CM, CM7, and CM11 had reduced chemical availability of lysine (87.6 vs. 83.1 and 85.7%), but lower glucosinolate content (1.14 vs. 0.99 and 0.92 µmol/g). Apparent ileal and total tract digestibility of energy was lower (P < 0.05) for CM7 than CM and intermediate for CM11, resulting in lower (P < 0.05) predicted net energy for CM7 and CM11 than CM (1.88 and 1.91 vs. 1.94 Mcal/kg, respectively). Standardized ileal digestibility (SID) of lysine was lower (P < 0.05) for CM7 and CM11 than CM (67.1 and 70.3% vs. 74.3, respectively). The SID of threonine was lower (P < 0.05) for CM7 than CM and intermediate for CM11. In summary, steam-explosion of CM damaged lysine reducing its digestibility and did not increase energy digestibility. In conclusion, steam-explosion of CM did not increase nutrient digestibility of CM for pigs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".