Improvement of the Fourier Transform Near Infrared Method to Evaluate Extra Virgin Olive Oils by Analyzing 1,2-Diacylglycerols and 1,3-Diacylglycerols and Adding Unesterified Fatty Acids.

Extra virgin olive oils (EVOO) command higher prices because they contain health-promoting nutrients and desirable sensory characteristics. Many targeted methods have limited success in determining olive oil authenticity. Therefore, attention has been paid to rapid spectroscopic methods that provide the composition of multiple components.

First Application of Newly Developed FT-NIR Spectroscopic Methodology to Predict Authenticity of Extra Virgin Olive Oil Retail Products in the USA.

Economically motivated adulteration (EMA) of extra virgin olive oils (EVOO) has been a worldwide problem and a concern for government regulators for a long time. The US Food and Drug Administration (FDA) is mandated to protect the US public against intentional adulteration of foods and has jurisdiction over deceptive label declarations. To detect EMA of olive oil and address food safety vulnerabilities, we used a previously developed rapid screening methodology to authenticate EVOO.

Developing FT-NIR and PLS1 Methodology for Predicting Adulteration in Representative Varieties/Blends of Extra Virgin Olive Oils.

It was previously demonstrated that Fourier transform near infrared (FT-NIR) spectroscopy and partial least squares (PLS1) were successfully used to assess whether an olive oil was extra virgin, and if adulterated, with which type of vegetable oil and by how much using previously developed PLS1 calibration models. This last prediction required an initial set of four PLS1 calibration models that were based on gravimetrically prepared mixtures of a specific variety of extra virgin olive oil (EVOO) spiked with adulterants. The current study was undertaken after obtaining a range of EVOO varieties grown in different countries.

Novel, Rapid Identification, and Quantification of Adulterants in Extra Virgin Olive Oil Using Near-Infrared Spectroscopy and Chemometrics.

A new, rapid Fourier transform near infrared (FT-NIR) spectroscopic procedure is described to screen for the authenticity of extra virgin olive oils (EVOO) and to determine the kind and amount of an adulterant in EVOO. To screen EVOO, a partial least squares (PLS1) calibration model was developed to estimate a newly created FT-NIR index based mainly on the relative intensities of two unique carbonyl overtone absorptions in the FT-NIR spectra of EVOO and other mixtures attributed to volatile (5280 cm(-1)) and non-volatile (5180 cm(-1)) components. Spectra were also used to predict the fatty acid (FA) composition of EVOO or samples spiked with an adulterant using previously developed PLS1 calibration models.

First direct body fat content measurement during pregnancy using Fourier transform near-infrared spectroscopy.

Currently, there are no direct and reliable methods to measure the body fat content of women during pregnancy. Estimates of fat accretion can significantly affect calculations of energy requirements. We report here the first direct measurement of determining the body fat content of two women during pregnancy using the Fourier transform near-infrared spectroscopy (FT-NIR) method.

Body fat content determination in premenopausal, overweight, and obese young women using DXA and FT-NIR.

Even though BMI is the most commonly used method for assessing and monitoring obesity, it does not take into account the individual's body fat content assuming instead that body mass is closely associated with body fat, which is a tenuous assumption. The aim of this study was to make a direct comparison between measurements of body fat content using a convenient and rapid Fourier transform near-infrared (FT-NIR) spectroscopy and dual-energy X-ray absorptiometry (DXA). We recruited 52, premenopausal women (age range 19-45), all of whom had a BMI that classified them as either overweight or obese (range: 27-40 kg/m(2), mean: 31.

A rapid method for the quantification of fatty acids in fats and oils with emphasis on trans fatty acids using Fourier Transform near infrared spectroscopy (FT-NIR).

A rapid method was developed for classifying and quantifying the FA composition of edible oils and fats using Fourier Transform near infrared spectroscopy (FT-NIR). The FT-NIR spectra showed unique fingerprints for saturated FA, cis and trans monounsaturated FA, and all n-6 and n-3 PUFA within TAG to permit qualitative and quantitative comparisons of fats and oils. The quantitative models were based on incorporating accurate GC data of the different fats and oils and FT-NIR spectral information into the calibration model using chemometric analysis.