Design and Evaluation of pH-Sensitive Pectin Films Infused with Anthocyanin-Rich Extracts from Australian Native Fruits for Intelligent Food Packaging Applications
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Bibliographic record
Abstract
Abstract This study investigates the incorporation of anthocyanin-rich extracts from Mountain Pepper Berry (MPB) and Queen Garnet Plum (QGP) into pectin-based films to develop pH-sensitive indicators. Using glycerol as an extraction solvent, significant differences in anthocyanin composition were identified: MPB extracts contained a diverse range of anthocyanin species, with a total content of 267.13 ± 5.21 mg L⁻¹, compared to the predominantly cyanidin-based QGP extracts, with 222.14 ± 1.61 mg L⁻¹. Differences in anthocyanin structures were elucidated using UPLC-Q-ToF-MS/MS analysis. FTIR and UV-Vis spectroscopy were used to assess the compatibility of the extracts with pectin and the homogeneity of anthocyanins within the film structure. Mechanical testing revealed that MPB films exhibited superior tensile strength (8.53 ± 0.51 MPa), stiffness (2274 ± 158.64 gmm − 1 ), and energy to failure (141.7 ± 16.23 J m − 3 ) compared to QGP films, which had lower tensile strength (7.74 ± 0.32 MPa), stiffness (1947 ± 125.82 gmm − 1 ), and energy to failure (115 ± 18.81 J m − 3 ). Both film types displayed similar moisture content (MPB: 48.89%, QGP: 48.13%) and water vapour permeability, indicating comparable barrier properties. When exposed to volatile ammonia, QGP films showed a more pronounced colour change, attributed to their anthocyanin profile, with a notable shift from red to brown. This research highlights the potential of glycerol-extracted anthocyanins from Australian native fruits as functional additives in pectin films, offering promising applications for intelligent packaging with enhanced mechanical performance and responsive colour-changing properties. Graphical Abstract
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it