Development of an extruded flax-based feed ingredient
Bibliographic record
Abstract
Increasing the content of omega-3 fatty acids in the fatty acid profile of the animal products humans consume is becoming increasingly important as a way of promoting health and reducing the risk of disease.To achieve an improved fatty acid profile in milk and meat from dairy cows, it is necessary to feed the animals with high omega-3 fatty acid content feed.Flaxseed is a feed ingredient which may suffice these needs, however the nature of the omega-3 fatty acids present certain problems at the level of digestionbiohydrogenation in the rumen.Also, the extrusion method of producing a cooked flaxseed ingredient enhances the release of the oil from the flaxseed itself, but in turn increases the opportunity for oil loss during storage and transport.To limit oil loss, flaxseed was combined with three different absorbent materials (alfalfa, soy hulls, gluten) at three different ratios of absorbent to flaxseed for each absorbent (15:85, 20:80, 25:75) and the ability of the extruded samples to retain oil under compression was measured.Of the three absorbents, alfalfa performed the best (p < 0.0001) at a ratio of 25:75 (p = 0.0002).The samples were characterized in terms of the protein fractions -soluble crude protein, neutral detergent insoluble crude protein (NDICP) and acid detergent insoluble crude protein (ADICP) -and the digestibility of dry matter (DM) and crude protein (CP).The effect of extrusion, type of absorbent and the ratio of absorbent to flaxseed on the nutritional quality and some physical properties of the samples were ascertained.
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) | 0.001 | 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 | 0.000 | 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".