New FTIR method for the determination of FFA in oils
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Bibliographic record
Abstract
Abstract A rapid, practical, and accurate FTIR method for the determination of FFA in edible oils was developed. Analogous to the AOCS titration procedure, the FTIR FFA determination is effected by an acid/base reaction but directly measures the product formed rather than utilizing an end point based on an electrode potential or color change. A suspension of a weak base, potassium phthalimide (K‐phthal) in 1‐propanol (1‐PrOH), is used to convert the FFA present in oils to their carboxylate salt without causing oil saponification, and differential spectroscopy is used to circumvent matrix effects. Samples are first diluted with 1‐PrOH, then split, with one‐half treated with the K‐phthal reagent and the other half with 1‐PrOH (blank reagent), their spectra collected, and differential spectra obtained to ratio out the invariant spectral contributions from the oil sample. Quantification of the percentage of FFA in the oil, expressed as %oleic acid, based on measurement of the peak height of the ν (COO − ) absorption of the FFA salt formed, yielded a calibration with an SE of <0.020% FFA over the range of 0–4%. The method was validated by standard addition and the analysis of Smalley check samples, the results indicating that the analytical performance of the FTIR procedure is as good as or better than that of the standard titrimetric procedure. As structured, the FTIR procedure is a primary method, as calibration is not dependent on reference values provided by another method, and has performance criteria that could lead to its consideration as an instrumental AOCS procedure for FFA determination. The FTIR portion of the analysis is automatable, and a system capable of analyzing ∼60 samples/h was developed that could be of benefit to laboratories that carry out a large number of FFA analyses per day.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it