Effects of dietary fish silage and fish fat on growth performance and meat quality of broiler chicks
Bibliographic record
Abstract
Two experiments were conducted to study the effect of concentrated fish silage and additional fish fat on growth performance (exp. 1) and meat quality (exp. 2) of broiler chicks. In exp.1, 600 day-old male and female chicks with an initial weight of 36.3 g ± 0.6 SD were allocated to five treatment groups. The treatments were a control diet, two test diets with 50 g kg−1 fish silage and different levels of fish fat (6 or 8 g kg−1), and two diets with 100 g kg−1 fish silage and different levels of fish fat (8 or 10 g kg−1). In exp. 2, 150 day-old female chicks with an initial weight of 36.3 g ± 0.7 SD were allocated to five treatment groups. The treatments were a control diet, and one of four test diets containing 50 g kg−1 fish silage and different levels of fish fat (2, 9, 17 or 25 g kg−1). In exp. 1, chicks fed diets with fish silage had a greater weight gain (P < 0.001), a greater feed intake (P < 0.05) and a lower feed-to-gain (MJ ME kg−1) (P < 0.001) than those fed the control diet. In exp. 2, no significant differences in weight gain or carcass weight were found among diets. The proportions of the fatty acids C18:3, C20:1, C20:5, C22:5 and C22:6 in abdominal fat, and C20:1, C22:1, C22:5 and C22:6 in breast meat, increased by the dietary inclusion of fish silage and fish fat. Increasing levels of dietary fish fat decreased blood plasma levels of vitamin E and ceruloplasmin. The diets containing the highest levels of fish fat (16.8 or 24.8 g kg−1) caused off-odour and off-taste of thigh meat stored at −16 °C for both six months and one month. Key words: Fish silage, fish fat, broilers, growth performance, sensory quality
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".