Porosity, Bulk Density, and Volume Reduction During Drying: Review of Measurement Methods and Coefficient Determinations
Bibliographic record
Abstract
Several experimental methods for measuring porosity, bulk density, and volume reduction during drying of foodstuffs are available. These methods include, among others, geometric dimension, volume displacement, mercury porosimeter, micro-CT, and NMR. However, data on their accuracy, sensitivity, and appropriateness are scarce. This article reviews these experimental methods, areas of applications, and limits. In addition, the concept of porosity, bulk density, and volume reduction and their evolution as a function of moisture content during drying are presented. In this study, values of initial porosity (ϵ0) and density ratio (β) of some food products are summarized. It has been found that ϵ0 is highly dependent on the type of food products, while β ranges from 1.1 to 1.6. The possibility of calculating solid density based on food compositions has also been validated. The inter-predictions between porosity, bulk density, and volume density have been made mathematically evident.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".