A rapid method for the quantitative determination of peroxide value (PV) of vegetable oils by Fourier transform infrared (FTIR) transmission spectroscopy is described. Calibration standards were prepared by the addition of tbutyl hydroperoxide to a series of vegetable oils, along with random amounts of oleic acid and water. Additional standards were derived through the addition of mono-and diglyeeride spectral contributions, as well as zero PV spectra obtained from deuterated oils. A partial least squares (PLS) calibration model for the prediction of PV was developed based on the spectral range 3750-3150 cm-k Validation of the method was carried out by comparing the PV of a series of vegetable oils predicted by the PLS model to the values obtained by the American Oil Chemists' S(~ciety iodometric method. The reproducibility of the FTIR method [coefficient of variation (CV) = 5%)] was found to be better than that of the chemical method ICV = 9%), although its accuracy was limited by the reproducibility of the chemical method. The method, as structured, makes use of a l-ram CaF2 flow cell to allow rapid sample handling by aspiration. The spectrometer was preprogrammed in Visual Basic to guide the operator in performing the analysis so that no knowledge of FTIR spectroscopy is required to implement the method. The method would be suitable for PV determinations in the edible oil industry and takes an average of three minutes per sample.

A Fourier transform infrared (FTIR) transmissionbased spectroscopic method was investigated for the simultaneous monitoring of aldehyde formation and the determination of anisidine value (AV) in thermally stressed oils. Synthetic calibration standards were prepared by adding known amounts of hexanal, t-2-hexenal and t,t-2,4-decadienal to canola oil (these compounds considered representative of aldehydic compounds formed during oxidation) plus random amounts of other compounds representative of oxidation by-products. The standards were analyzed for their chemical AV. With the partial least squares (PLS) technique, an FTIR spectrometer was calibrated to predict both the concentrations of individual aldehyde types and AV, with the individual aldehyde contributions being related to the chemical AV by multiple linear regression to derive "apparent" AV values. The predictive capability of the PLS calibrations was assessed by analyzing canola oils that were thermally stressed at 120, 155, and 200~ The apparent AV, predicted for these samples, matched the chemical AV values within +I .65 AV units. A PLS calibration also was derived by using thermally stressed samples as calibration standards. This approach provided similar predictive accuracy as the use of synthetic calibration standards. As such, quantitative determination of AV by FTIR spectroscopy was shown to be feasible, and the synthetic calibration approach provided additional information on the aldehyde types present in a sample and allowed the use of a simple gravimetric approach for calibrating an FTIR spectrometer. This study provides the basis for the development of a rapid, automated FTIR method for the direct analysis for AV of thermally stressed fats and oils in their neat form without the use of chemical reagents. The implementation of such a method as a quality control tool would eliminate the use and disposal of hazardous solvents and reagents, required by the conventional chemical method, and drastically reduce analysis time (-2 min/sample). Possible applications include monitoring of the oxidative state of frying oils or evaluation of oxidative stability of biodegradable lubricants.JAOCS 73, 787-794 (I 996).

The use of Fourier transform-near infrared (FT-NIR) spectroscopy combined with multivariate pattern recognition techniques was evaluated to address the need for a fast and senisitive method for the detection of bacterial contamination in liquids. The complex cellular composition of bacteria produces FT-NIR vibrational transitions (overtone and combination bands), forming the basis for identification and subtyping. A database including strains of Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Bacillus cereus, and Bacillus thuringiensis was built, with special care taken to optimize sample preparation. The bacterial cells were treated with 70% (vol/vol) ethanolto enhance safe handling of pathogenic strains and then concentrated on an aluminum oxide membrane to obtain a thin bacterial film. This simple membrane filtration procedure generated reproducible FT-NIR spectra that allowed for the rapid discrimination among closely related strains. Principal component analysis and soft independent modeling of class analogy of transformed spectra in the region 5,100 to 4,400 cm(-1) were able to discriminate between bacterial species. Spectroscopic analysis of apple juices inoculated with different strains of E. coli at approximately 10(5) CFU/ml showed that FT-NIR spectralfeatures are consistent with bacterial contamination and soft independent modeling of class analogy correctly predicted the identity of the contaminant as strains of E. coli. FT-NIR in conjunction with multivariate techniques can be used for the rapid and accurate evaluation of potential bacterial contamination in liquids with minimal sample manipulation, and hence limited exposure of the laboratory worker to the agents.

IR spectroscopy's sensitivity to molecularstructure and interactions provides a "molecular fingerprint", which is the basis for biomedical applications.