Formation and characterization of protein-based films from yellow pea (Pisum sativum) protein isolate and concentrate for edible applications
Bibliographic record
Abstract
This study investigated the properties of films or bioplastics fabricated using a wet processing method from yellow pea protein isolate (YPI) and protein concentrate (YPC) for potential application in food packaging. The wet processing method included mixing the protein with water and glycerol followed by casting and drying the films in a humidity- and temperature-controlled chamber. Whey protein isolate (WPI) and a film from a blend of equal amounts of YPI and WPI, labelled as YPI + WPI, were also studied. Fourier transform-infra red analysis revealed that films from YPI, YPC, WPI and YPI + WPI were formed by protein polymerisation with the plasticiser, glycerol, via hydrophobic and hydrophilic interactions. The protein films had contact angles of <90° demonstrating that they had a hydrophilic surface, with YPC < YPI < YPI + WPI < WPI. The pattern of ultraviolent light transmission of the films was WPI > YPC > YPI + WPI > YPI, whereas the mechanical and thermal resilience of films formulated from YPI, YPC and the protein blend were comparable to the properties of WPI-based films. The findings demonstrate that yellow pea proteins can be used as biomaterials to develop protein and protein-blend films or bioplastics for food packaging and edible applications.
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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) | 0.000 | 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 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".