Impact of <scp>Ylang Ylang</scp> essential oil on the physical, thermal, and antioxidant properties of corn starch/bovine gelatin films
Bibliographic record
Abstract
Abstract In the present study we evaluated the antioxidant activity, morphological, barrier, thermal, surface optical, and mechanical properties of corn starch/bovine gelatin‐based films containing Ylang Ylang essential oil (YYEO) with various concentrations (0.1%, 0.5%, and 1%) were incorporated in the film matrix. The obtained findings indicated that the tensile strength of the fabricated films did not show any significant difference. The addition of YYEO to composite films led to notable enhancements in their properties, including an increase in elongation at break (15.86%–54.78%), water solubility (35.66%–49.49%), moisture content (13.61%–19.03%), and swelling index (347%–453%). The film containing YYEO exhibited greater water vapor permeability compared to the control film. Additionally, the swelling ratio of all YYEO‐enriched films was noticeably lower than that of the control films. The incorporation of YYEO also improved the hydrophobicity of the biocomposite films. Thermal analysis demonstrated enhanced thermal stability with the addition of YYEO. Furthermore, antioxidant assays, such as DPPH and ABTS, revealed a significant boost in antioxidant activity in the oil‐loaded films. This study explores the use of YYEO in developing composite films made from corn starch and gelatin. The resulting films demonstrate a good potential for use in food packaging applications. Highlights EAB increased while TS remained unchanged with the addition of YYEO. YYEO increased solubility, moisture content, and swelling index. Improvement in WVP and thermal stability. YYEO significantly altered optical properties and improved hydrophobicity. Films showed structural compatibility and consistent microstructural changes with the addition of YYEO.
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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".