ORIGINAL ARTICLE: Application of soybean meal, soy protein concentrate and isolate differing in α-galactosides content to low- and high-fibre diets in growing turkeys
Bibliographic record
Abstract
The aim of this experiment was to investigate the physiological and growth response of young turkeys (up to 8 weeks of age) to dietary replacement of soybean meal (SBM) by soy protein concentrate (PC) or protein isolate (PI). This replacement resulted in a differentiated dietary concentration of α-galactosides of over 2.5% in the SBM diet, approximately 2% with a mixture SBM and PC, 1% with a PC diet and 0.1% with a PI diet. Each treatment was applied in two ways: with lower (3.5%) or higher (5.3%) dietary crude fibre content, made by supplementation with soybean hulls. The highest and lowest body weight of turkeys was recorded both after the first and second 4-week half of the study in the PC and PI-type diets respectively. A gradual withdrawal of α-galactosides from a diet was accompanied by a decline in ileal tissue mass, ileal viscosity and activity of endogenous maltase (the latter was found to be significant at 4 weeks of age). At the same time, two-way anova revealed that an elevated level of crude fibre (HF treatment) caused an increase in ileal tissue mass (p < 0.05 after 4 weeks of feeding) as well as a decrease in activity level of intestinal sucrase and maltase. The presence of raffinose family oligosaccharides in a diet, in contrast to dietary crude fibre level, significantly affected the caecal metabolism. The rate of bacterial production of short-chain fatty acids in the caeca was distinctly diminished by dietary withdrawal of α-galactosides. In conclusion, the soy protein concentrate, in contrast to the protein isolate preparation, exerted positive effects on the turkeys' growth and gastrointestinal tract physiology and should be considered as an effective SBM substitute.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".