Composition and Emulsifying Characteristics of Grasscutter Meat from Varying Dietary Energy Levels
Bibliographic record
Abstract
Sixteen (16) grasscutters (Thryonomys swinderianus) used for this study had been fed, in groups of four, one of four treatment diets namely; 2000, 2200, 2400, and 2600 kcalME/kg respectively. Two grasscutters were randomly selected from each treatment group for slaughter. Equal weights (150g) of meat samples collected from the forelimbs and hindlimbs of each slaughtered grasscutter were mixed, packed in waterproof plastic bags and stored overnight at -2oC hter. Equal weights (150g) of meat samples collected from the forelimbs and hindlimbs of each slaughtered grasscutter were mixed, packed in waterproof plastic bags and stored overnight at -2oC. The chemical composition and emulsifying characteristics of the meat samples were determined. It was found that the chemical composition and emulsifying characteristics (including protein content, emulsifying capacity, water holding capacity, emulsion stability and cooking loss) of grasscutter meat from varying dietary energy levels were significantly (P<0.05) different. These findings indicate that the protein content and emulsifying characteristics were significantly higher for meat from grasscutters fed the 2000 kcalME/kg diet than for meat from grasscutters fed the higher dietary energy levels. e; a positive interaction by increasing soil water content in root zone versus a negative interaction by decreasing diurnal soil temperatures to suboptimal values especially before wheat heading. Low soil temperatures under sludge may become critical for shoot propagation and head density at sub-optimal temperatures of cold years for wheat growth.. The chemical composition and emulsifying characteristics of the meat samples were determined. It was found that the chemical composition and emulsifying characteristics (including protein content, emulsifying capacity, water holding capacity, emulsion stability and cooking loss) of grasscutter meat from varying dietary energy levels were significantly (P<0.05) different. These findings indicate that the protein content and emulsifying characteristics were significantly higher for meat from grasscutters fed the 2000 kcalME/kg diet than for meat from grasscutters fed the higher dietary energy levels. e; a positive interaction by increasing soil water content in root zone versus a negative interaction by decreasing diurnal soil temperatures to suboptimal values especially before wheat heading. Low soil temperatures under sludge may become critical for shoot propagation and head density at sub-optimal temperatures of cold years for wheat growth.
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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) | 0.000 | 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".