A New Fourier Transform Infrared Method for the Determination of Moisture in Edible Oils
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Bibliographic record
Abstract
A rapid, practical, and accurate Fourier transform infrared (FT-IR) method for the determination of moisture content in edible oils has been developed based on the extraction of water from oil samples into dry acetonitrile. A calibration curve covering a moisture content range of 0-2000 ppm was developed by recording the mid-infrared (MIR) spectra of moisture standards, prepared by gravimetric addition of water to acetonitrile that had been dried over molecular sieves, in a 500 microm ZnSe transmission flow cell and ratioing these spectra against that of the dry acetonitrile. Water was measured in the resulting differential spectra using either the OH stretching (3629 cm(-1) or bending (1631 cm(-1)) bands to produce linear standard curves having standard deviations (SDs) of approximately +/-20 ppm. For moisture analysis in oils, the oil sample was mixed with dry acetonitrile in a 1:1 w/v ratio, and after centrifugation to separate the phases, the spectrum of the upper acetonitrile layer was collected and ratioed against the spectrum of the dry acetonitrile used for extraction. The method was validated by standard addition experiments with samples of various oil types, as well as with oil samples deliberately contaminated with alcohols, hydroperoxides, and free fatty acids to investigate possible interferences from minor constituents that may be present in oils and are potentially extractable into acetonitrile. The results of these experiments confirmed that the moisture content of edible oils can be assessed with high accuracy (on the order of +/-10 ppm) by this method, thus providing an alternative to the conventional, but problematic, Karl Fischer method and facilitating the routine analysis of edible oils for moisture content.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it