Effects of Feeding Micronized and Extruded Flaxseed on Ruminal Fermentation and Nutrient Utilization by Dairy Cows
Bibliographic record
Abstract
Four lactating Holstein cows with ruminal and duo-denal cannulas were used in a 4 x 4 latin square design to determine the effects of feeding heat-treated flaxseed on ruminal fermentation and site and extent of nutrient utilization. Four diets were formulated: a control diet with no flaxseed, a raw flaxseed diet (RF), a micronized flaxseed diet (MF), and an extruded flaxseed diet (EF). Flaxseed diets contained 12.6% flaxseed (dry matter [DM] basis). Ruminal pH, NH3 N, and total concentration of volatile fatty acids were not affected by dietary treatments. However, feeding flaxseed decreased the molar proportion of acetate and increased that of propionate. Flaxseed supplementation had no effect on ruminal digestion of DM, organic matter (OM), neutral detergent fiber (NDF), crude protein (CP), fatty acids (FA), and gross energy. However, ruminal digestion of acid detergent fiber (ADF) was lower for cows fed the flaxseed diets than for cows fed the control diet. Feeding flaxseed tended to increase post-ruminal and total tract digestibilities of DM, OM, NDF, and gross energy. Feeding heat-treated flaxseed diets relative to RF had no effect on ruminal, post-ruminal, and total tract nutrient digestibilities. Cows fed EF had higher ruminal and lower post-ruminal digestibilities of DM, OM, ADF, CP, and FA than cows fed MF. However, total tract digestibilities were similar for the 2 heat treatments. It was concluded that flaxseed supplementation improved total tract nutrient utilization with no adverse effects on ruminal fermentation. Extrusion failed to protect flaxseed from ruminal digestion. However, micronization can be used to increase the ruminal undegraded protein value of flaxseed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".