Photometric Titration Method to Determine Bromination of Red and Yellow Dyes in Crackers
Bibliographic record
Abstract
The change in absorbance of a solution may be used to follow the change in concentration of a radiation-absorbing constituent during a titration. The absorbance is directly proportional to the concentration of the absorbing constituent. This method might be useful to determine bromination reaction in colorful crackers, which are favourite food of children and adults in our country, Indonesia. In this work, we determined red and yellow dyes in unregistered crackers sold at Jatinangor, West Java, Indonesia. The dyes were isolated by extraction using a mixture of 2% of ammonia in 70% ethanol continued by preparative thin layer chromatography on GF254 silica gel plate and were separated and analyzed by using FTIR-8400 Shimadzu infrared spectrophotometer. Bromination reaction was measured by using photometric titration method. Thin layer chromatograms showed that the dyes were not either rhodamine B or tartrazine (Rf of the red and yellow dyes were 0.714 and 0.652, respectively, while those of rhodamine B and tartrazine were 0.591 and 0.673). Infrared spectroscopy showed characteristic peaks of the red dye at 3390.6 cm-1(O-H stretch), 2927.7 cm-1(C-H stretch of alkyl), 1404.1 cm-1 (O-H bend), 1616.2 cm-1(C=C stretch), and 1315 cm-1 (C-O stretch). The peaks of yellow dye occured at 3413.8 cm-1, (O-H stretch), 3213.2 cm-1 (C-H stretch of alkene), 2927.7 cm-1(C-H stretch of alkyl), 1400.2 cm-1(O-H bend), 1624.0 cm-1 (C=C stretch). Visible spectroscopy showed maximum wavelengths at 551 nm (red dye) and 432 nm (yellow dye). Photometric titration to determine bromination reaction in the dyes showed a decreasing in absorbance due to the conversion of colored analytes to colorless products. This fact indicated that bromination reaction was occured in the red and yellow dyes molecules via electrophilic addition reaction on its double bond.
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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 | 0.000 | 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 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".