Oxidative stability in grinds from omega-3 enhanced pork
Bibliographic record
Abstract
Juárez, M., Dugan, M. E. R., Larsen, I. L., Thacker, R., Rolland, D. C. and Aalhus, J. L. 2011. Oxidative stability in grinds from omega-3 enhanced pork. Can. J. Anim. Sci. 91: 623–634. In order to investigate the effect of enhancing n-3 fatty acid levels in carcasses on the retail and sensory characteristics of pork grinds, as well as the ability of increasing dietary levels of vitamin E to stabilize the increase in PUFA levels from flaxseed supplementation, 81 pigs were used in a 3×3 factorial experiment. Dietary treatments included three lengths of time (0, 3 and 6 wk) of flaxseed supplementation and three levels of vitamin E (40, 200 and 400 mg kg feed−1). α-Tocopherol tissue levels increased with dietary vitamin E supplementation (P<0.001), and fat softness (P=0.018) and total PUFA and n-3 fatty acids (P<0.001) increased with flaxseed supplementation. Most other animal performance, carcass and lean pork quality traits were not affected (P>0.05) by dietary treatments. In ground pork, the increase in TBARS after 6 d in retail was lower (P<0.001) with increasing dietary vitamin E levels. However, vitamin E had no effect (P>0.05) on the higher (P<0.001) TBARS levels observed in grinds from flaxseed fed pigs. The dietary addition of flaxseed negatively modified (P<0.05) all the sensory attributes of both cooked and reheated products. Increasing the fat content of the grinds up to 30% seemed to counteract (P>0.05) the negative effects of feeding flaxseed for 3 wk. Feeding vitamin E was not able to prevent negative effects (P<0.05) observed during retail display in grinds with either increasing fat content or higher n-3 fatty acids from dietary flaxseed. However, increasing dietary vitamin E only showed a protective effect (P<0.05) on retail appearance after long periods of ageing.
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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) | 0.000 | 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 | 0.001 |
| 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".