Lignin and green solvent extracted phenolic compounds from date palm leaves as functional ingredients for the formulation of soy protein isolate biocomposite packaging materials: A circular packaging concept
Bibliographic record
Abstract
The current study investigated valorization of lignin nanoparticles (LNPs) and phenolic compounds loaded in chitosan (DLECNPs) extracted from date palm leaves into the soy protein isolate (SPI) biocomposite films. The mechanical, structural, barrier, physiochemical, thermal, optical, antioxidant, and antimicrobial properties of the formulated composite films were investigated. The findings showed that the incorporation of DLECNPs into the SPI films significantly improved the film's antioxidant properties by more than 3 times and showed antibacterial inhibition zone in the range of 10-15 mm against six pathogenic bacteria. Further, incorporating LNPs into SPI-DLECNPs films notably improved the mechanical properties from 4.32 MPa and 29.27 % tensile strength and elongation at break, respectively to 10.13 MPa and 54.94 %, the water vapor permeability from 7.38 g/Pa s m to 5.59 g/Pa s m, and the antibacterial inhibition zone from a range of 10.2 mm to 15.0-21.5 mm as well as making the films more heterogeneous and stronger than control SPI film. Moreover, LNPs changed the initial films' color from light yellow to dark red and reduced the films' transparency. The results indicated that LNPs reinforced SPI composite films showed significant improvements in several properties and thus can be used as a potential ingredient for formulation of biodegradable packaging films.
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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 | 0.001 | 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 | 0.001 | 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".