Determination of Free Fatty Acids in Edible Oils with the Use of a Variable Filter Array IR Spectrometer
Bibliographic record
Abstract
Abstract The feasibility of employing a portable variable filter array (VFA) IR spectrometer equipped with a transmission flow cell to quantitatively analyze edible oils or biodiesel feedstocks for free fatty acids (FFA) was evaluated. The approach to FFA determination employed was based on a previously reported FTIR method that involves the extraction of FFAs into methanol containing the base NaHNCN, which converts the FFAs to their salts, followed by measurement of the carboxylate absorbance at ~1,573 cm −1 in the spectrum of the methanol phase. When this methodology was implemented on the low‐resolution VFA‐IR spectrometer, the analytical performance was comparable to that of conventional FTIR instrumentation at FFA concentrations of <1%. However, at higher FFA levels, the relatively weak pulsed IR source of the VFA‐IR spectrometer was found to provide insufficient energy for accurate measurement of the carboxylate absorption superimposed on the strong methanol absorption at ~1,450 cm −1 . By changing the extraction solvent to ethanol (EtOH), good spectra and calibrations could be obtained over an FFA range of 0–5%, having an overall SD of ±0.07% FFA. Based on this assessment, a VFA‐IR spectrometer provides an economical instrumental means for at‐line monitoring of FFA levels in crude and refined edible oils and biodiesel feedstocks, capable of analyzing ~20–30 prepared samples per hour.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".