Effect of high shear homogenisation on physicochemical, microstructure, particle size and volatile composition of residual pineapple pulp
Bibliographic record
Abstract
Summary Waste or by‐product utilisation is on focus to reduce the environmental threat and acquiring wealth out of waste. This study was planned to understand the effect of high shear homogenisation (SH) on physicochemical, microstructural, particle size, dietary fibre and volatile composition of residual pineapple pulp (RPP) for its utilisation. Shear homogenisation with three levels of rotor speed, that is 5000, 15 000 and 30 000 rpm, was employed for 5, 10 and 15 min. These responses reveal that the shear speed of 15 000 rpm for 10 min was relatively better in colour retention and enhanced soluble dietary fibre (SDF) by 48%. Increased levels of SDF after treatment help in the utilisation of RPP and its suitability for food supplementation. A gradual reduction in particle size from 40 to 400 μm was observed with shear homogenisation. Optical microscopy images revealed that larger cell fragments, fibrous nature and dense hairy mass of pomace were disrupted at 15 000 rpm. Moderate shear speed triggers the release of additional aroma volatiles, whereas higher rpm and time resulted in degradation of volatiles. The shear homogenised RPP is used for the development of fibre‐enriched yoghurt and incorporation at a 5% level resulted in high acceptable sensory scores.
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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".