The effects of inclusion level of an extruded flaxseed-pea supplement on nitrogen balance and flow of amino and fatty acids in a dual-flow continuous culture system
Bibliographic record
Abstract
n-3 Fatty acids (FA) have well-established benefits in human health, including anticarcinogenic and cardioprotective effects. This has prompted growing interest in enriching dairy products with n-3 FA through dietary manipulation in dairy cows. The objective of this study was to evaluate the effects of increasing dietary inclusion of linPRO-R (LIN), a proposed rumen-protected matrix of flaxseed and field pea proteins (21% fat, 24% CP, 10.07% n-3 FA; DM basis), on N metabolism, AA flow, and long-chain FA outflow using a dual-flow continuous culture system. Treatments consisted of 4 levels of LIN inclusion (0%, 2.5%, 5.0%, and 7.5% of diet DM) in a TMR, replacing portions of dried distillers grains and calcium salts of long-chain FA to maintain similar CP and ether extract levels across treatments. The study followed a replicated 4 × 4 Latin square design using 8 fermenters across four 10-d periods (7 d adaptation, 3 d sampling). Effluent samples were collected at 3, 6, 9, and 24 h after feeding and analyzed for AA, N balance, and long-chain FA concentrations. Data were analyzed using GLIMMIX procedure of SAS with fixed effects of treatment, period, and square, with fermenter nested within square as a random effect. Inclusion of LIN had no effect on AA flow, N flow, or calculations of RDP, RUP, or bacterial N efficiency. However, increasing dietary LIN reduced the outflow of SFA (notably C16:0) and increased the outflow of C18:3n3 (0.48%-3.47% of total FA), despite an increase in the biohydrogenation (93.4%-95.9%). These results suggest that LIN can enhance the delivery of n-3 FA postruminally, despite a large fraction of the FA being biohydrogenated, without impairing N metabolism or AA availability, supporting its use as a dietary strategy to increase the nutritive value of dairy products.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".