Effects of fat crystal network structure on the rheological properties of high oleic-stearic acid fats before and after chemical and random enzymatic interesterification
Bibliographic record
Abstract
The effects of two methods of fatty acid interesterification (chemical and enzymatic) on the physico-chemical properties of oleic-stearic-rich fats were examined in this study. Interesterification resulted in a decrease in the concentration of triunsaturated and trisaturated triacylglycerols (TAGs) and an increase in the proportion of mixed TAGs and ultimately a lower melting point for the interesterified (IE) blends. Crystallization kinetic parameters (Avrami index and rate constant) were similar for the non-interesterified (NI) and IE blends when compared as a function of SFC. X-ray analysis revealed a predominance of the [beta]' form in the IE and the [beta] form crystals in the NI blends, while reflections centered at 45A? suggested the presence of a 2L lamellar crystalline structure in all treatments. Dilution and crystallization at 20-50°C did not change the polymorphism of the NI-blends, but did in the IE-blends. Needle-like crystals in the IE-blends and large symmetrical spherulites in the NI-blends were predominant in samples crystallized at 30°C for 24hrs. Over 75% of the structural elements had areas between 1-20 [mu]m 2 in the blends, and the NI-blends showed a higher percentage of crystals in this range compared to the IE-samples. A higher Db in the CI-sample relative to the EI sample, at an equivalent area fraction, was attributed to the homogeneity in the distribution of crystalline mass. The storage modulus (G') and yield force increased with FHCO concentration in the blends and was affected strongly by interesterification and showed a weak correlation with SFC content. An increase in G' at 30°C upon interesterification was attributed to a decrease in the fractal dimension of the fat crystal network which translated into a decrease in crystal cluster size. The higher G' in the CI-samples relative to the EI-samples was due to a higher [lambda] parameter which is directly proportional to the strength of interparticle interactions and inversely proportions to crystal size. The 30%CI-blend produced a fat with the same physical properties as commercial products and it was appropriate for use as a high stability shortening. The results of sensory analysis showed the same acceptability for the two types of cookies using commercial and 30% CI-blend shortening.
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 | 0.000 | 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 | 0.001 |
| 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".