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. A Fourier transform near infrared (FT-NIR) method was reported that identified five major fatty acids and volatiles in EVOO, plus four models that identify common adulterants and their content. However, it did not include diacylglycerol (DAG) and unesterified fatty acids (FFA) known to be associated with freshness of the oil. The newly improved FT-NIR method now includes 1,2-DAG and 1,3-DAG models based on the DAG isomer content in freshly prepared EVOO, and a FFA model based on quantitative addition of oleic acid. The new FT-NIR method was used to reassess previously used EVOO products to evaluate their freshness. Based on these results and review of the published data, we propose several revisions to the EVOO regulation: limit FFA to ≤0.5%, include 1,2-DAG and 1,3-DAG in standard, place no limit on 1,2-DAG because it characterizes the oils, set the 1,3-DAG content to ≤1.0%, and lower the content of 18:2n-6 to 1.5%.

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. For the first time, a recently developed FT-NIR spectroscopic methodology in conjunction with partial least squares analysis was applied to commercial products labeled EVOO purchased in College Park, MD, USA to rapidly predict whether they are authentic, potentially mixed with refined olive oil (RO) or other vegetable oil(s), or are of lower quality. Of the 88 commercial products labeled EVOO that were assessed according to published specified ranges, 33 (37.5%) satisfied the three published FT-NIR requirements identified for authentic EVOO products which included the purity test. This test was based on limits established for the contents of three potential adulterants, oils high in linoleic acid (OH-LNA), oils high in oleic acid (OH-OLA), palm olein (PO), and/or RO. The remaining 55 samples (62.5%) did not meet one or more of the criteria established for authentic EVOO. The breakdown of the 55 products was EVOO potentially mixed with OH-LNA (25.5%), OH-OLA (10.9%), PO (5.4%), RO (25.5%), or a combination of any of these four (32.7%). If assessments had been based strictly on whether the fatty acid composition was within the established ranges set by the International Olive Council (IOC), less than 10% would have been identified as non-EVOO. These findings are significant not only because they were consistent with previously published data based on the results of two sensory panels that were accredited by IOC but more importantly each measurement/analysis was accomplished in less than 5 min.

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. It was found that all the different types of EVOO varieties investigated belonged to four distinct groups, and each required the development of additional sets of specific PLS1 calibration models to ensure that they can be used to predict low concentrations of vegetable oils high in linoleic, oleic, or palmitic acid, and/or refined olive oil. These four distinct sets of PLS1 calibration models were required to cover the range of EVOO varieties with a linoleic acid content from 1.3 to 15.5 % of total fatty acids. An FT-NIR library was established with 66 EVOO products obtained from California and Europe. The quality and/or purity of EVOO were assessed by determining the FT-NIR Index, a measure of the volatile content of EVOO. The use of these PLS1 calibration models made it possible to predict the authenticity of EVOO and the identity and quantity of potential adulterant oils in minutes.

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. Some adulterated mixtures could be identified provided the FA profile was sufficiently different from those of EVOO. To identify the type and determine the quantity of an adulterant, gravimetric mixtures were prepared by spiking EVOO with different concentrations of each adulterant. Based on FT-NIR spectra, four PLS1 calibration models were developed for four specific groups of adulterants, each with a characteristic FA composition. Using these different PLS1 calibration models for prediction, plots of predicted vs. gravimetric concentrations of an adulterant in EVOO yielded linear regression functions with four unique sets of slopes, one for each group of adulterants. Four corresponding slope rules were defined that allowed for the determination of the nature and concentration of an adulterant in EVOO products by applying these four calibration models. The standard addition technique was used for confirmation.

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. Fourier transform near-infrared spectroscopy was shown to provide comparable results to dual-energy X-ray absorptiometry and magnetic resonance imaging. These latter methods, even though very reliable to measure body fat levels, cannot be used to measure the body fat of women during pregnancy because of health concerns, while FT-NIR poses no health risk. The FT-NIR results showed the percent body fat remained relatively constant throughout pregnancy, but fat mass and fat free mass increased. Fat mass followed an S curve with a maximum increase between 15 to 25 weeks of gestation that was only detected by repeated measurements using the FT-NIR technique. These results demonstrate the value of the FT-NIR method to directly measure the fat content of pregnant women in minutes instead of relying on indirect calculations or taking measurements before and after pregnancy to track gestational fat mass accretion.

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: 31.1 ± 3.7 kg/m(2)) and indicated a statistically significant linear relationship between the fat content in kilograms measured by FT-NIR and DXA (r = 0.95, P < 0.001). Bland-Altman analysis showed that almost all the differences between two measurements fell within 2 s.d. We report here that the FT-NIR method provided comparable measurements of subcutaneous body fat content similar to those of total fat obtained using DXA. The FT-NIR method is a lower cost, easy to use and transport, and, based on comparison with DXA, an accurate method to measure body fat content. We propose that FT-NIR is an ideal method for safe repeat measurements in large trials or in screening and monitoring individuals during interventions in which changes in body fat will occur.

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. FT-NIR classification models were developed based on chemometric analyses of 55 fats, oils, and fat/oil mixtures that were used in the identification of similar materials. This database was used to prepare three calibration models-one suitable for the analysis of common fats and oils with low levels of trans FA, and the other two for fats and oils with intermediate and high levels of trans FA. The FT-NIR method showed great potential to provide the complete FA composition of unknown fats and oils in minutes. Compared with the official GC method, the FT-NIR method analyzed fats and oils directly in their neat form and required no derivatization of the fats to volatile FAME, followed by time-consuming GC separations and analyses. The FT-NIR method also compared well with the official FTIR method using an attenuated total reflectance (ATR) cell; the latter provided only quantification of specific functional groups, such as the total trans FA content, whereas FT-NIR provided the complete FA profile. The FT-NIR method has the potential to be used for rapid screening and/or monitoring of fat products, trans FA determinations for regulatory labeling purposes, and detection of contaminants. The quantitative FT-NIR results for various edible oils and fats and their mixtures are presented based on the FT-NIR models developed.