Effect of initial moisture and temperature on the enzyme activity of pelleted high protein/fiber biomass.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High protein/fiber biomass, which is used as a feed enzyme to increase feed utilization efficiency of poultry rations, was pelletized. Feed enzymes reduce viscosity of gut contents and change nutrient absorption in animal digestive tract and as a result, improve the nutritional quality of feeds. However, the pelleting process may denature enzymes. Pelleting was optimized in terms of the initial moisture content of the biomass and the pelleting temperature. Preliminary pelleting tests were done in a single-pelleting unit and the results were validated using the pilot-scale pellet mill. The initial moisture content levels of biomass was varied from 14 to 22% wb and pelletized at temperatures of 60.0, 77.5, and 95.0oC during preliminary tests. Pellet durability and enzyme activity were measured to study the effect of each variable. To improve pellet durability, different binders were combined with the biomass and the feasibility of producing pellets in a pilot-scale pellet mill was tested. Although high pellet durability was obtained by pelleting the biomass in a pilot-scale pellet mill with steam conditioning at 14% moisture content, combined with 1.5% bentonite, and 5% fat, the enzyme activity of the pellets was low. However, pelleting the biomass without steam conditioning did not affect enzyme activity and can be a viable option for making durable pellet.
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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 it