Rheological and Textural Characteristics of Date Paste
Bibliographic record
Abstract
The rheological properties of two commercial date pastes were investigated in the temperature range of 20–70°C. From typical flow behavior curves, it was observed that date pastes exhibited pseudoplastic behavior. The shear stress-shear rate data were fitted using six common rheological models. The Casson model best described the experimental data at all temperatures. The Arrhenius model described successfully the temperature dependence of apparent viscosity of date pastes (R2 > 0.99) with an Ea value in the range of 25,392.6–25,485.7 kJ/kmol. The textural attributes measured were: hardness, springiness, gumminess, cohesiveness, chewiness, and adhesiveness for the texture profile analysis test, and firmness, adhesive force, mean load, and total positive area for the Ottawa test. There was a significant difference in textural attributes between two varieties of date paste studied. Texture profile analysis results showed that all parameters obtained for black date pastes were higher than golden date pastes except for springiness and cohesiveness. However, the Ottawa results showed that golden date pastes were firmer and less adhesive than black date pastes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".