Digestibility of protein, amino acids and starch in mink (<i>Mustela vison</i>) fed diets processed by different extrusion conditions
Bibliographic record
Abstract
An experiment was carried out to evaluate the effect of different extrusion processes on digestibility of a fish-meal-based diet fed to mink. The feed was processed in a twin-screw extruder with the exit temperatures of the meal of 100, 125 or 150°C. Feed production was carried out three times, using different extrusion conditions to achieve the target temperatures. An untreated meal mixture was included as a control diet. True digestibilities of crude protein and total amino acids were lower for diets extruded at 125 and 150°C than for the control (P < 0.05). Digestibilities of crude protein, total amino acids, and the amino acids alanine, arginine, aspartic acid, cysteine, glutamic acid, histidine, isoleucine, leucine, lysine and valine decreased when increasing extrusion temperature from 100 to 125 °C (P < 0.05), a further increase in temperature did not influence digestibility (P > 0.05). The highest reduction was seen for cysteine (6.8 percentage units). Starch digestibility was increased by extrusion, but there was no effect of temperature (P > 0.05). Digestibilities of crude protein, total amino acids, alanine, arginine, aspartic acid, glutamic acid, glycine, proline, histidine, lysine, tryptophan and valine were affected by the processing method (P < 0. 05), which, by multivariate analysis, was revealed to be associated mainly with processing parameters: revolutions per minute, conditioner temperature, die temperature and feeding rate. Digestibility of starch was influenced mainly by the addition of water. Key words: Digestibility, protein, amino acid, starch, mink, extrusion
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".