The effects of <i>Aronia melanocarpa</i> (AM) dietary supplementation on production performance, meat and egg quality, yolk volatile substances and antioxidant capacity of laying hens
Bibliographic record
Abstract
The effects of Aronia melanocarpa (AM) dietary supplementation on production performance, meat and egg quality, yolk volatile substances and antioxidant capacity of laying hens. A total of 480 Roman brown laying hens aged 25 wks were randomly divided into control, LAM, MAM and HAM groups and fed 0%, 1%, 4% and 7% AM, respectively. The results showed that AM dietary supplementation significantly increased the eggshell strength, significantly reduced 24 h dripping loss of breast and thigh muscles, and increased pH and 48 h dripping loss of breast and thigh muscles. Cooking loss was significantly lower only in the HAM group for breast muscle. The MAM group was able to significantly increase albumen height and Haugh units. Esters gradually decreased with the increase in AM content, and the addition of AM led to a decrease in alcoholic compounds but increased the contents of alkenes, alkanes, ketones, and acids. The dietary AM supplementation significantly reduces the MDA content of serum, liver, ovary, chest muscle, thigh muscle and yolk and increases the activities of GSH-Px, T-SOD and T-AOC. In summary, dietary AM supplementation could improve antioxidant capacity and expression of related genes, thereby improving meat and egg quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".