Evaluation of portable vibrational spectroscopy for identifying plasticizers in dairy tubing.

Plasticisers are commonly used to increase the flexibility of a wide variety of food contact materials including the plastic tubing, liners, and gaskets used in the dairy industry. In recent years, some classes of plasticisers have come under scrutiny due to the potential for transfer of these compounds into the milk itself, which can then be further processed into foods such as powdered milks and cheeses, infant formula, and baked goods. One such set of plasticisers that is being evaluated for frequency of use, potential routes of exposure, and risk to consumers is ortho-phthalates, hereafter referred to as phthalates. In order to better understand the actual use of phthalate versus non-phthalate plasticised tubing, a robust, rapid, and portable analytical method is necessary for on-site screening. Laboratory Raman and near-infrared spectrometers have been used extensively for polymer and additive evaluation, and advances in portable/hand-held technology could lead to feasible plasticiser evaluation in the field. This research overviews efforts to evaluate six portable spectroscopy devices for their ability to identify phthalate versus non-phthalate plasticised polyvinyl chloride (PVC) dairy tubing, liners, and gaskets. The most successful method, a hand-held Raman spectrometer along with a plasticiser spectral library or a chemometric model, can rapidly and accurately identify phthalate containing PVC and has the potential to be employed as a future field screening technique for regulators and the dairy industry.

Detection of decomposition in mahi-mahi, croaker, red snapper, and weakfish using an electronic-nose sensor and chemometric modeling.

This study evaluated an electronic-nose (e-nose) sensor in combination with support vector machine (SVM) modeling for predicting the decomposition state of four types of fish fillets: mahi-mahi, croaker, red snapper, and weakfish. The National Seafood Sensory Expert scored fillets were thawed, 10-g portions were weighed into glass jars which were then sealed, and the jars were held at approximately 30°C to allow volatile components to be trapped and available for analysis. The measurement of the sample vial headspace was performed with an e-nose device consisting of nanocomposite, metal oxide semiconductor (MOS), electrochemical, and photoionization sensors. Classification models were then trained based on the sensory grade of each fillet, and the e-nose companion chemometric software identified that eight MOS were the most informative for determining a sensory pass from sensory fail sample. For SVM, the cross-validation (CV) correct classification rates for mahi-mahi, croaker, red snapper, and weakfish were 100%, 100%, 97%, and 97%, respectively. When the SVM prediction performances of the eight MOS were evaluated using a calibration-independent test set of samples, correct classification rates of 93-100% were observed. Based on these results, the e-nose measurements coupled with SVM models were found to be potentially promising for predicting the spoilage of these four fish species. PRACTICAL APPLICATION: This report describes the application of an electronic-nose sensor as a potential rapid and low-cost screening method for fish spoilage. It could provide regulators and stakeholders with a practical tool to rapidly and accurately assess fish decomposition.

A Rapid, Univariate FT-NIR Procedure to Determine Moisture Concentration in Olive Oil.

We recently observed that the weak near-infrared (NIR) band near 5260 cm-1 was relatively more intense for extra virgin olive oil (EVOO) than for refined olive oil (ROO). We also observed that its intensity was diminished upon heating and erroneously presumed that it may be attributed to volatile carbonyl components in EVOO. In the present study we demonstrate for the first time that this band is primarily attributed to a water O-H combination band. To accurately determine the intensity of this weak band, observed on a shifted and sloping baseline, we measured the peak-to-peak (p-p) height of its first derivative. An exponential calibration curve for p-p height versus gravimetrically-determined concentration of spiked water was satisfactorily generated. The calibration curve was first evaluated by using independent sets of gravimetrically prepared test samples. Subsequently, it was used to determine the moisture content, a quality parameter, for a limited set of authenticated reference olive oils whose quality and purity were confirmed by official methods. These concentrations, 0.098-0.12% H2O (w/w) for EVOO, 0.022-0.030% H2O (w/w) for ROO, and 0.028-0.054% H2O (w/w) for pomace olive oil (POO), were consistent with those reported in the literature. For 88 commercial products investigated, the moisture levels fell in the range from 0.026% to 0.13% (w/w). The correlation between moisture content and other olive oil quality parameters has been reported in the literature and has yet to be further investigated.