Effects of Feeding Camelina (Seeds or Meal) on Milk Fatty Acid Composition and Butter Spreadability
Bibliographic record
Abstract
The nutritional and rheological properties of butter depend on the fatty acid composition of milk. Therefore, feeding oilseeds rich in unsaturated fatty acids is likely to affect butter properties. The aim of this trial was to examine to what extent feeding the linolenic acid-rich cruciferous plant camelina can affect the fatty acid composition of dairy products and the properties of butter. A control diet composed of 60% corn silage-based ration and completed with high-energy and nitrogenous concentrates was compared with 2 experimental diets designed to provide the same amount of polyunsaturated fatty acids via either camelina seed (630 g/d, CS diet) or camelina meal (2 kg/d, CM diet). The diets were isoenergetic and isonitrogenous. The trial followed a double 3 x 3 Latin-square design with 4-wk periods on 6 Holstein dairy cows. The camelina diets tended to decrease dry matter intake but did not have a significant effect on milk production. They generated a slight decrease in milk protein and a strong decrease in milk fat yield and content. The CM diet led to a stronger decrease in fat content. Camelina generated a greater proportion of monounsaturated fatty acids, notably C18:1 trans isomers, including trans-10 and trans-11 C18:1, which increased by 11.0- and 2.6-fold, respectively, with the CM diet. Camelina also led to an increase in conjugated linoleic acids, particularly rumenic acid, cis-9, trans-11 C18:2. Camelina did not affect parameters of buttermaking except churning time with milk from CM fed cows, which was longer. The butters of camelina diets were softer at all temperatures tested, especially with the CM diet. In conclusion, feeding camelina can modify milk fatty acid profile and butter spreadability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 teacher head, 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".