Nutritional supplementation of ahiflower seed and press cake in laying hens and its effect on production performance, nutrient digestibility, egg quality, and yolk omega-3 fatty acid enrichment during mid- to post-peak production phase
Bibliographic record
Abstract
Ahiflower seed (AFS) and ahiflower press cake (AFP) are rich in n-3 fatty acids and other nutrients that can be beneficial for laying hens or deposited in their eggs. A total of 288 36-week-old white leghorn hens were allocated into eight treatments with six replicates of 6 birds/cage for 12 weeks. The treatments included the control (CON), CON + 10% flaxseed (10%FX), 1, 5, or 10% AFS, or 5, 10, or 15% AFP. Overall, 10%AFP increased BW compared to 1%AFS. Diets did not affect n-6/n-3, apparent total tract digestibility (ATTD) of energy, and most of the egg quality parameters. In the egg yolk, stearidonic acid was increased (P<.0001) in 10%AFS (0.15mg/g) compared to CON (0.01mg/g), 10%FX (0.08mg/g), and all other treatment groups. The eicosapentaenoic acid was increased (P=0.0001) in 10%AFS (0.28mg/g) and 10%FX (0.29 mg/g) compared to CON (0.05mg/g). Compared to CON (1.49 mg/g) and other treatment groups, 10%FX (9.47mg/g) increased (P0.000) α-linolenic acid while docosahexaenoic acid was increased (P0.000) by 10%AFS (5.39mg/g) compared to CON (2.82mg/g). Hens fed 10%FX, 5% and 15%AFP had increased (P=0.0001) linoleic acid (34mg/g) compared to CON (26.6mg/g). In conclusion, 10%AFS increased n-3 FAs in egg yolk with no effect on egg quality, eggshell Ca and P levels, ATTD of energy, and n-6/n-3 ratio.
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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) | 0.001 | 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 | 0.001 | 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".