Characterization of a Food‐Safe Colorimetric Indicator Based on Black Rice Anthocyanin/PET Films for Visual Analysis of Fish Spoilage
Bibliographic record
Abstract
ABSTRACT The safety of food products is of prime importance for consumers and manufacturers. Many means can be used to validate a food product's safety before it is consumed. This study is about the preparation, characterization and evaluation of a generally recognized as safe (GRAS) sensitive colorimetric sensor that detects volatile gases (TVB‐N) resulting from fish spoilage, thus indicating the pH variation of packaged fish products. This is performed by coating a thin layer of ink sensors on the surface of the supporting matrix (corona‐treated PET). Various visual pH indicators were prepared based on black rice anthocyanin as an FDA‐approved dye. Black rice, which contains more than 80% cyanidin‐3‐glucoside, is the most prevalent anthocyanin component. Because of its low toxicity and high concentration, it can be utilized as a natural food colourant. pH indicators based on black rice can show distinct colours in various pH: from red (low pH) to violet (4–6) and deep purple/blue (6–7), blue (7–9) to yellowish/light brown (9–13) throughout the acid–base reaction by the analyte. The ink formulation was prepared by incorporating a binder system (PVOH‐PEG) for higher surface wettability, a crosslinking agent (citric acid) for higher adhesion, an antifoaming agent (natural vanillin) and acetic acid as a pH fixing agent. Corona treatments affected substrate surface chemistry in this study. The samples with thermal treatment passed the ASTM D3330 tape test, the 8000 passages for dry sponge and the 25 passages for wet sponge through the abrasion method. Anthocyanin concentration in formulated ink based on calculation by UV–vis spectra is 0.240 mg/100 g. Sensitivity tests towards TVB‐N gases were carried out at a temperature of 4°C to evaluate the performance of colorimetric films with formulated ink along with thermal treatment (temperature: 165°C, time: 5 min) using the volatile gases emitted by the fish sample inside the package.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".