Effect of extrusion of soybean meal on feed spectroscopic molecular structures and on performance, blood metabolites and nutrient digestibility of Holstein dairy calves
Bibliographic record
Abstract
OBJECTIVE: Performance and physiological responses of dairy calves may change by using extruded soybean meal (ESBM) instead of common soybean meal (SBM) in starter feed. The aims of the current study were i) to determine the effect of extrusion processing of SBM on protein electrophoretic size, fourier transform infrared spectroscopy (FTIR) structures and Cornell Net Carbohydrate and Protein System (CNCPS) protein subfractions and ii) to determine the effect of substitution of SBM with ESBM in starter feed of Holstein heifer calves during pre and post-weaning on performance, nutrient digestibility, and blood metabolites. METHODS: The SBM was substituted with ESBM at the level of 0%, 25%, 50%, 75%, and 100% (dry matter [DM] basis). Fifty heifer calves (initial body weight 40.3±0.63 kg) were used for the study. After birth, animals were fed colostrum for 3 days and then they were fed whole milk until weaning. Animals had free access to starter feed and water during the study. RESULTS: Extrusion of SBM decreased electrophoretic protein size and increased rapidly degradable true protein fraction, changed FTIR protein and amide II region. With increasing level of ESBM in the diet, starter intake increased quadratically during the pre-weaning period (p<0.05) and body weight, DM intake and average daily gain increased linearly during the post-weaning and the whole study period (p<0.05). Tbe DM and crude protein digestibilities at week 14 and blood glucose and beta hydroxybutyric acid increased linearly in calves as the level of ESBM increased in the diet (p<0.05). CONCLUSION: Dairy calves performance and physiological responses were sensitive to SBM protein characteristics including electrophoretic size, FTIR structures and CNCPS protein fractions.
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 | 0.001 |
| 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".