Using a portable field device, a Fourier transform infrared spectroscopy (FTIR) and partial least-squares regression (PLSR) method was developed for the rapid (<5 min) prediction of major and minor fatty acid (FA) concentrations in marine oil omega-3 dietary supplements. Calibration models were developed with 174 gravimetrically prepared samples. These models were tested using an independent validation set of dietary supplements. FAs analyzed included eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA); the sums of saturated, branched-chain, and monounsaturated FAs; and n-6, n-4, n-3, n-1, and trans polyunsaturated FA. The spectral ranges 650-1500 or 650-1500 and 2800-3050 cm provided reliable predictions for FA components in 34 neat oil products: standard error of prediction, 0.73-1.58%; residual predictive deviation, 6.41-12.6. This simple, nondestructive quantitative method is a rapid screening tool and a time and cost-saving alternative to gas chromatography for verifying label declarations and in quality control.

A rapid tool for evaluating authenticity was developed and applied to the screening of extra virgin olive oil (EVOO) retail products by using Fourier-transform near infrared (FT-NIR) spectroscopy in combination with univariate and multivariate data analysis methods. Using disposable glass tubes, spectra for 62 reference EVOO, 10 edible oil adulterants, 20 blends consisting of EVOO spiked with adulterants, 88 retail EVOO products and other test samples were rapidly measured in the transmission mode without any sample preparation. The univariate conformity index (CI) and the multivariate supervised soft independent modeling of class analogy (SIMCA) classification tool were used to analyze the various olive oil products which were tested for authenticity against a library of reference EVOO. Better discrimination between the authentic EVOO and some commercial EVOO products was observed with SIMCA than with CI analysis. Approximately 61% of all EVOO commercial products were flagged by SIMCA analysis, suggesting that further analysis be performed to identify quality issues and/or potential adulterants. Due to its simplicity and speed, FT-NIR spectroscopy in combination with multivariate data analysis can be used as a complementary tool to conventional official methods of analysis to rapidly flag EVOO products that may not belong to the class of authentic EVOO.

A non-targeted detection method using near-infrared (NIR) spectroscopy combined with chemometric modeling was developed for the rapid screening of commercial milk powder (MP) products as authentic or potentially mixed with known and unknown adulterants. Two benchtop FT-NIR spectrometers and a handheld NIR device were evaluated for model development. The performance of SIMCA classification models was then validated using an independent test set of genuine MP samples and a set of gravimetrically prepared mixtures consisting of MPs spiked with each of eleven potential adulterants. Classification models yielded 100% sensitivities for the benchtop spectrometers. Better specificity, which was influenced by the nature of the adulterant, was obtained for the benchtop FT-NIR instruments than for the handheld NIR device, which suffered from lower spectral resolution and a narrower spectral range. FT-NIR spectroscopy and SIMCA classification models show promise for the rapid screening of commercial MPs for the detection of potential adulteration.