Using Liquid Smoke to Improve Mechanical and Water Resistance Properties of Gelatin Films
Bibliographic record
Abstract
Improvement of mechanical and water barrier properties is critical for gelatin films when applied to edible food packaging. A liquid smoke (LS) obtained from hawthorn nucleus was used to improve the performance of gelatin film based on its abundant compounds. Through SPME-GC-MS analysis, 86 volatile and semi-volatile chemical compounds was detected in LS, in which the total carbonyl compounds were 27.60%, with the main aldehyde as 2-furaldehyde (9.83%). For gelatin films, an observable influence of LS on film transparency was observed in gelatin films, but not for its thickness and microstructure. Desirably, adding LS into gelatin solution increased the tensile strength of the films, with a better value of 16.38 MPa as 3 wt% LS added, compared with the control (10.30 MPa). Accordingly, film elongation decreased with a LS dependent manner. Furthermore, the water resistance properties of gelatin film were improved by the LS addition, which was supported by the results of water contact angle, water vapor permeability. Moreover, the addition of LS also led to a higher insolubility for gelatin films. Also, thermal stability of the LS treated gelatin films was slightly enhanced with the DSC analysis. According to the FTIR spectra and crosslinking degree detection results, all the above enhancing of gelatin film should be attributed to the crosslinking between carbonyl groups in LS and amide functionalities in gelatin based on nucleophilic reaction.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".