Effects of dietary deoiled soy lecithin supplementation on milk production and fatty acid digestibility in Holstein dairy cows
Bibliographic record
Abstract
Deoiled soy lecithin is a feed additive enriched in phospholipids. Our study evaluated the effects of dietary deoiled soy lecithin supplementation on (1) milk production and composition, (2) plasma and milk fatty acid (FA) content and yield, and (3) apparent FA digestibility and absorption in lactating dairy cows fed fractionated palm fat. In a split-plot Latin square design, 16 Holstein cows (160 ± 7 days in milk; 3.6 ± 1.2 parity) were randomly allocated to a main plot receiving a corn silage and alfalfa haylage-based diet with palm fat containing either moderate (MPA) or high palmitic acid (HPA) content at 1.75% of ration dry matter (72 or 99% palmitic acid, respectively; n = 8/palm fat diet). On each palm fat diet, deoiled soy lecithin was top-dressed at 0, 0.12, 0.24, or 0.36% of ration dry matter in a replicated 4 × 4 Latin square design. Following a 14-d covariate period, lecithin supplementation spanned 14 d, with milk and blood collected during the final 3 d. Milk composition and pooled plasma markers were measured. The statistical model included the fixed effects of palm fat type, lecithin dose, period, and the interaction between palm fat type and lecithin dose. The random effect of cow nested within palm fat group was also included. Lecithin linearly decreased dry matter intake. In cows fed HPA, lecithin feeding reduced milk fat content and tended to decrease milk fat yield. Although no changes in milk yield were observed, a quadratic reduction in 3.5% fat-corrected milk was observed with increasing lecithin dose. Lecithin linearly increased energy-corrected milk efficiency in cows fed MPA. Lecithin supplementation also decreased milk urea nitrogen, relative to unsupplemented cows. The proportion of 16-carbon FA in milk fat decreased linearly with lecithin dose, whereas 18-carbon FA increased linearly. Lecithin reduced de novo FA (<16-carbon) content and tended to increase preformed FA (>16-carbon) content in a linear manner. Compared with MPA, HPA diets reduced apparent total and 16-carbon FA digestibility and absorption. Deoiled soy lecithin feeding did not modify FA digestibility or absorption. Our observations suggest that soy lecithin feeding modifies rumen digestion to reduce dry matter intake and change milk composition.
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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) | 0.000 | 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".