The effect of bacterial protein grown on natural gas on growth performance and sensory quality of broiler chickens
Bibliographic record
Abstract
Bacterial protein meal (BPM) produced from natural gas by Methylococcus capsulatus (Bath), Alcaligenes acidovorans, Bacillus brevis and Bacillus firmus was studied as a protein source for broiler chickens. Three experiments from day-old to slaughter at 35 d were carried out. In exp. 1, BPM was fed at 0, 20, 40, 60, 80 and 100 g kg-1 diet (as fed) replacing soybean meal protein. Levels of BPM up to 60 g kg-1 had no effect on 0-5 wk gain, while the 80 and 100 g kg-1 levels significantly reduced gain, especially in the 0–2 wk period. In exp. 2, chickens were fed diets containing 0, 30, 60 and 90 g kg-1 BPM and two protein levels, 23 and 21 g kg-1. The highest level of BPM significantly reduced growth, independent of protein level, whereas growth responses to lower levels of BPM were similar to the control diet. In exp. 3, 90 g kg-1 BPM in diets containing 23 g kg-1 protein had no negative effect on growth, but significantly reduced the abdominal fat pad. Overall, substitution of soybean meal protein with increasing levels of BPM significantly lowered feed-to-gain ratio during the last part of the feeding period. Sensory analysis of thigh meat after 2 mo of frozen storage (exp. 1) showed that meat from 35-d-old chickens fed 60 and 100 g kg-1 BPM had less odor intensity and less rancid flavor than meat from control animals fed no BPM. Other sensory attributes were not affected by treatment. Key words: Bacterial protein meal, chicken, growth performance, feed:gain ratio, feed conversion, 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".