Investigating the possibility of monitoring lectin levels in commercial soybean meals intended for poultry feeding using steam-heated soybean meal as a model
Bibliographic record
Abstract
Native soybean lectins (SBL) could potentially have deleterious effects on young animals. The objectives of this study were to determine the optimum processing temperature and time at which SBL is inactivated and to investigate the possibility of using urease activity (UA) to predict residual lectin levels in soybean meal (SBM). Raw defatted SBM was steam-heated at incremental temperatures between 90 and 120 degrees C for 5 to 20 min in an autoclave. The processed meals were subjected to native-PAGE and measurement of total carbohydrate-binding lectin (TCBL), agglutinating lectin (AL), UA, and trypsin inhibitor (TI). Processing severity was evaluated by determining protein solubility in 0.2% potassium hydroxide. Results indicated that levels of all antinutrients (TCBL, AL, UA, and TI) decreased with increasing processing temperature (P < 0.05). The intensity of the lectin band on the electrophoresis gel was considerably reduced when meal was heated at 100 degrees C for 5 min. This result implied that lectin inactivation occurred at 100 degrees C. More than 90% of all the original antinutrient levels in the raw meal were destroyed when meals were heated at 100 degrees C for 5 min. Meals processed at 100 degrees C for 5 to 20 min had protein solubility values (80 to 85%) indicative of adequate processing. The denaturation pattern of UA was highly correlated with that of SBL (r > or = 0.73), indicating that UA could be used for monitoring lectin levels in commercial meals. We concluded that UA of 0.03 to 0.09 units of pH change are indicative of adequately processed meals that contain negligible lectin levels.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".