Chemical composition and digestible and metabolizable energy contents in cold-pressed canola expellers fed to growing pigs
Bibliographic record
Abstract
Abstract Cold-pressed canola expellers (CPCE) are a byproduct of canola oil production obtained using the pressing method without thermal and chemical treatment. While CPCE is a valuable source of dietary energy and protein in swine nutrition, the discrepancy in processing conditions leads to variability in the nutritional quality of CPCE from different sources. This study aimed to determine the chemical composition, and digestible energy (DE) and metabolizable energy (ME) values of CPCE when fed to growing pigs. Samples of CPCE were collected from five processing facilities across Western Canada. The physical appearance of the CPCE samples hinted at a potential quality variation. Samples were subjected to a complete chemical characterization. Variations (P < 0.05) were observed in the chemical composition, with the exception of non-phytate phosphorus, xylose, mannose, and galactose. On a g/kg dry matter (DM) basis, CPCE samples ranged as follows: ether extract from 85 to 177; crude protein (CP) from 351 to 419; neutral detergent fiber 231 to 300; total dietary fiber from 326 to 373; glycoproteins from 30 to 76; non-starch polysaccharides from 188 to 204, non-phytate phosphorus from 5.5 to 6.4, and gross energy (GE) in kcal/kg 5,027 to 5,635. The total glucosinolates (GLS) ranged from 5.0 to 9.7 µmol/g DM. Thirty-six (36) growing barrows, with an average initial body weight of 19.2 ± 1.0 kg, were individually housed in metabolism crates and assigned to one of the six experimental diets in a completely randomized design, with six pigs per diet. The diets included a corn–soybean meal (SBM)-based basal diet (100%) and five (5) experimental diets in which 18% of the basal diet was substituted with CPCE from different producers. Pigs were fed the experimental diets for 10 d, with 5-d adaptation period, followed by a 5-d period for the total, but separate, collection of feces and urine. Significant differences (P < 0.05) among processing plants were observed in the DE and ME contents of CPCE, which averaged 3,531 and 3,172 kcal/kg DM, respectively. Differences (P < 0.05) were noted in the apparent total tract digestibility of GE, nitrogen (N), as well as in the retention of DM, GE, and N in CPCE samples. In conclusion, while the chemical composition and values of DE and ME in CPCE vary among processors, the byproduct obtained through cold pressing process can be a valuable source of energy and protein for pig nutrition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".