Improved Determination of Isolated trans Isomers in Edible Oils by Fourier Transform Infrared Spectroscopy Using Spectral Reconstitution
Bibliographic record
Abstract
A substantially more sensitive and accurate alternative to the single-bounce attenuated total reflectance (SB-ATR) Fourier transform infrared spectroscopic method of AOAC/American Oil Chemists' Society (AOCS) was developed for determination of isolated trans isomers, based on transmission measurements using a technique called spectral reconstitution (SR). The method involves the 1:1.5 dilution of an oil with odorless mineral spirits (OMS) containing a spectral marker. The resulting reduction in sample viscosity facilitates the use of a transmission flow cell, with the spectral marker serving to determine the precise dilution ratio. This allows the spectral contributions of the OMS to be eliminated and a facsimile of the neat oil spectrum to be mathematically reconstituted. The transmission-SR (T-SR) procedure was initially evaluated relative to SB-ATR to track changes in the trans content of mixtures of unhydrogenated canola and a highly hydrogenated sunflower oil (0-30% trans). The results indicated that the T-SR procedure had the potential to serve as the basis of an accurate quantitative method. A subsequent T-SR calibration based on the spectral ratioing principle of the SB-ATR AOACIAOCS method was developed by gravimetrically adding trielaidin (0-4%) to extra virgin olive oil (EVO), producing an excellent linear response with a standard deviation (SD) of < 0.04% trans. Subsequent comparison of SB-ATR and T-SR calibrations developed for 5 oils of different types, each spiked with low levels of trielaidin (0-1.2% trans), clearly indicated that SB-ATR was signal-limited, whereas the T-SR procedure performed well. The EVO calibration was subsequently used to predict the added trans content of these spiked oils, after the spectrum of the corresponding unspiked oil had been ratioed out. The resulting plot of predicted versus added trans was linear, with a slope of 1.02 and an overall SD of <0.05% trans. When the spectra of these oils were ratioed against the spectrum of EVO, the trans predictions for some of the oils were offset by 2-3 percentage points, emphasizing the need for the appropriate trans-free reference oil to perform accurate analyses. If the latter condition is met, then T-SR provides a very simple technique, with the potential for automation, for analysis of oils by transmission spectroscopy, with approximately 20x the sensitivity of the AOAC/AOCS SB-ATR method.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".