Sanjeewa R. Karunathilaka

Rapid Prediction of Fatty Acid Content in Marine Oil Omega-3 Dietary Supplements Using a Portable Fourier Transform Infrared (FTIR) Device and Partial Least-Squares Regression (PLSR) Analysis.

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-1 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.

Characterising variances of milk powder and instrumentation for the development of a non-targeted, Raman spectroscopy and chemometrics detection method for the evaluation of authenticity.

ABSTRACT There is a need to develop rapid tools to screen milk products for economically motivated adulteration. An understanding of the physiochemical variability within skim milk powder (SMP) and non-fat dry milk (NFDM) is the key to establishing the natural differences of these commodities prior to the development of non-targeted detection methods. This study explored the sources of variance in 71 commercial SMP and NFDM samples using Raman spectroscopy and principal component analysis (PCA) and characterised the largest number of commercial milk powders acquired from a broad number of international manufacturers. Spectral pre-processing using a gap-segment derivative transformation (gap size = 5, segment width = 9, fourth derivative) in combination with sample normalisation was necessary to reduce the fluorescence background of the milk powder samples. PC scores plots revealed no clear trends for various parameters, including day of analysis, powder type, supplier and processing temperatures, while the largest variance was due to irreproducibility in sample positioning. Significant chemical sources of variances were explained by using the spectral features in the PC loadings plots where four samples from the same manufacturer were determined to likely contain an additional component or lactose anomers, and one additional sample was identified as an outlier and likely containing an adulterant or differing quality components. The variance study discussed herein with this large, diverse set of milk powders holds promise for future use as a non-targeted screening method that could be applied to commercial milk powders. Graphical Abstract

Nontargeted, Rapid Screening of Extra Virgin Olive Oil Products for Authenticity Using Near-Infrared Spectroscopy in Combination with Conformity Index and Multivariate Statistical Analyses

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.

Non-targeted detection of milk powder adulteration using Raman spectroscopy and chemometrics: melamine case study

ABSTRACT Raman spectroscopy in combination with chemometrics was explored as a rapid, non-targeted screening method for the detection of milk powder (MP) adulteration using melamine as an example contaminant. Raman spectroscopy and an unsupervised pattern-recognition method, principal component analysis (PCA), allowed for the differentiation of authentic MPs from adulterated ones at concentrations > 1.0% for dry-blended (DB) samples and > 0.30% for wet-blended (WB) ones. Soft independent modelling of class analogy (SIMCA), a supervised pattern-recognition method, was also used to classify test samples as adulterated or authentic. Combined statistics at a 97% confidence level from the SIMCA models correctly classified adulteration of MP with melamine at concentrations ≥ 0.5% for DB samples and ≥ 0.30% for WB ones, while no false-positives from authentic MPs were found when the spectra in the 600–700 cm–1 range were pre-processed using standard normal variate (SNV) followed by a gap-segment derivatisation. The combined technique of Raman spectroscopy and chemometrics proved to be a useful tool for the rapid and cost-efficient non-targeted detection of adulteration in MP at per cent spiking levels. GRAPHICAL ABSTRACT

Quantitation of Saccharin and Cyclamate in Tabletop Formulations by Portable Raman and NIR Spectrometers in Combination with Partial Least Squares Regression

Rapid, direct, and reagent-free screening tools using vibrational spectroscopy in combination with partial least squares regression (PLSR) were developed for the determination of sodium saccharin and sodium cyclamate in tabletop formulations. The four vibrational spectroscopic instruments employed were a portable Raman spectrometer, a NIR handheld device, and two FT-NIR benchtop spectrometers. Wavenumber ranges and type of spectral pretreatment were optimized for each PLSR calibration model using an independent validation set. Each sweetener model provided reliable predictions (low errors in validation and r2 above 0.90) for both saccharin and cyclamate samples. Optimized models were tested with four commercially available tabletop formulations in order to simulate the application of the developed models towards routine sweetener analysis. With the exception of one model, the sweetener concentration predictions in commercial tabletop formulations using the portable devices were not significantly different from those based on spectra collected on the benchtop spectrometers. PLSR-predicted mean sweetener concentrations were within 80–120% of the label declared values, while the sweetener without a label declaration had consistent concentrations across the analytical methods used. As shown by the good agreement between spectroscopic and chromatographic analyses, the portable spectrometers offer an alternative to traditional chromatographic methods. To our knowledge, this is the first time portable Raman and handheld NIR devices with PLSR calibration models have been employed to evaluate sweeteners, and these analytical methods hold potential to be used for rapid screening of tabletop formulations for quality assurance and for regulatory labeling verification.

Portable Raman spectroscopy and chemometric methods for the analysis of marine oil dietary supplements

S 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018 – 1 – ANA 1a: Spectroscopic, Spectrometric and Chemometric Methods for Lipid Analysis Chairs: Sanjeewa Karunathilaka, US Food and Drug Administration, USA; and Bernd W.K. Diehl, Spectral Service AG, Germany Portable Raman Spectroscopy and Chemometric Methods for the Analysis of Marine Oil Dietary Supplements Betsy J. Yakes*, Sanjeewa R. Karunathilaka, Kyungeun Lee, Lea Brückner, and Magdi Mossoba, US Food and Drug Administration, USA Marine oil supplements containing long-chain omega-3 polyunsaturated fatty acids (PUFAs), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are the most commonly used nonvitamin, nonmineral dietary supplements in United States due to their potential health benefits. While established methods such GC-FID excel at analysis of omega3 PUFAs, there is a need for rapid and accurate screening of these omega-3 PUFA products to ensure both quality and accuracy of label declaration. As such, Raman spectroscopy using portable instruments followed by chemometric analysis was performed to understand the potential for rapid, on-site evaluation of these supplements for fatty acid content. For this study, 109 marine oils were procured, and spectra acquired for each neat (underivatized) oil on three Raman devices: (1) a portable Raman spectrometer with a unique laser setup and data processing to decrease fluorescence interference, (2) a handheld Raman analyzer with onboard chemometrics for immediate pass/fail triaging of complex samples, and (3) a smartphone sized Raman spectrometer containing orbital raster scanning that allows for larger sampling areas. For each instrument, a broadbased calibration library comprised of a wide variety of marine oils was made using partial least-squares regression (PLSR) to predict fatty acid composition. The current study evaluates the capabilities of each Raman spectrometer for the simple, rapid analysis of marine oil products for potential use in verifying label declarations and quality control during dietary supplement production. Vibrational Spectroscopy and Chemometric Procedures for the Rapid Assessment of Olive Oil Authenticity Magdi Mossoba*, Sanjeewa R. Karunathilaka, Cynthia Srigley, Kyungeun Lee, Lea Brückner, and Betsy J. Yakes, US Food and Drug Administration, USA FDA is mandated with protection of the US public against intentional adulteration of foods for economically motivated gain, including having jurisdiction over deceptive label declarations found with adulterated extra virgin olive oil (EVOO). In April 2016, a US Congressional Committee expressed concerns related to reports of the high prevalence of imported olive oil sold in the US that is adulterated or mislabeled. Such fraudulence reportedly includes the mixing of EVOO with seed oils, which could adversely impact the health of consumers who are allergic to seed oil. This issue underscores the urgent need for more rigorous analytical methodologies, including untargeted rapid screening tools, for detecting such fraudulence. We have applied rapid vibrational spectroscopy and chemometric procedures to the screening of 72 retail commercial products labeled extra virgin olive oil for the classification, and/or prediction of volatile content, fatty acid composition, and the type and ABSTRACTS 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018S 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018 – 2 – quantity of a refined edible oil potentially mixed with authentic EVOO. The current spectroscopic/ chemometric predictions will be compared to those based on the International Olive Council (IOC) official method COI/T.20/Doc. No 20/ Rev. 3 (2010) for the determination of olive oil purity; this method is based on the targeted determination of the absolute difference between the experimental HPLC values for TAGs with equivalent carbon number 42 (ECN42_HPLC) and the theoretical value for TAGs with an equivalent carbon number of 42 (ECN 42_theoretical) calculated from GC-based fatty acid composition. Automated Multicomponent Phospholipid Analysis Using 31p NMR Spectroscopy: Example of Vegetable Lecithin and Krill Oil Bernd W.K. Diehl*, and Yulia B. Monakhova, Spectral Service AG, Germany Nuclear magnetic resonance spectroscopy (NMR) is widely applied in the field of metabolomics due to its quantitative nature and the reproducibility of data generated. However; one of the main challenges in routine analysis by NMR is to obtain valuable information from large datasets of raw data in a high throughput, automatic, and reproducible way. In this study, a method to automatically annotate and quantify 12 phospholipids (PLs) in vegetable lecithin (soy, sunflower, raps) and krill oil is introduced. Automated routines were written in MATLAB environment for quantification of phosphatidylcholine (PC), phosphatidylinositol (PI), lyso-phosphatidylcholine (LPC), phosphatidylserine (PS), phosphatidylethanolamine (PE), diphosphatidylglycerol (DPG), phosphatidylglycerol (PG) and lysophosphatidylethanolamine (LPE) in lecithin and of PC, PC-ether, LPC, PE, APE, LPE in krill oil matrix. The routine includes NMR spectra import, extraction of data points, peaking of minima and maxima in the data, integration, quantitation against internal standard, reporting of results as Word file and their importing in our internal database. Our extensive studies on a representative set of more than 1000 lecithin (soy, raps, sunflower) and krill samples showed that the automated routine can automatically and accurately calculate the concentrations of all PLs. No systematic or proportional differences between automated and manual evaluation were detected. The developed program produces accurate results with the advantage of being fully automated and requires less than 5 seconds for each analysis. This tool is already used in highthroughput PL analysis of krill and lecithin and will be adjusted to other matrices (egg, milk, chocolate, etc.) as well. Analysis and Detection of Olive Oil Adulteration using Fourier Transform Near-Infrared Spectroscopy Ariel Bohman*1, Kathryn J. LawsonWood2, and Robert Packer1, 1PerkinElmer, USA; 2PerkinElmer, United Kingdom Olive oil has seen a large increase in market demand due to its linkage with lowering one’s risk of heart disease associated with its high monounsaturated fat content. As the demand and value of olive oil increases, less reputable producers look for ways to cut costs and increase profit margins resulting in the substitution or dilution of olive oil with less expensive edible oils. Economically motivated adulteration is the intentional addition of lower value substances to a product to increase company profit margins. The prevalence of adulterated olive oil has been ABSTRACTS 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018S 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018 – 3 – increasing with a reported 80% of Italian olive oil being considered fraudulent. Near-infrared spectroscopy, for detection of olive oil adulteration, offers many advantages over traditional reference methods, such as GC/MS and HPLC, as it is a rapid, non-destructive technique. Samples of olive oil and commonly used adulterants have been analyzed in transmission mode over the near-infrared region spanning from 14,000 to 4,000 cm-1. Nearinfrared spectroscopy coupled with chemometric analysis methods, such as soft independent modelling of class analogy (SIMCA), is capable of successfully distinguishing between olive oil and edible oils commonly used in the adulteration of olive oil. The objective of this work is to demonstrate the utility of near-infrared spectroscopy coupled with chemometric methods in the detection of adulterated olive oils. Analysis of transmission spectra of pure and adulterated olive oil samples will be presented to highlight the benefits of near-infrared spectroscopy as a rapid, non-destructive alternative to traditional screening methods for the detection of olive oil adulteration. ABSTRACTS 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018S 2018 AOCS ANNUAL MEETING AND EXPO May 6–9, 2018 – 4 – ANA 1b: Lipidomic Analysis Chairs: Francesca Giuffrida, Nestec SA, Switzerland; and J. David Pinkston, Kellogg Co., USA Lipidomic Profiling–An Integral Technology for Research and Development Elizaveta Freinkman*, Metabolon, Inc., USA Lipids are a diverse class of metabolites that serve many biological functions such as energy storage, structural components of cell membranes, and signaling. Accurate measurements of lipids are essential for biomarker discovery and for clarifying biological questions. This presentation will cover Metabolon’s different offerings pertaining to lipid research, and these include the complex lipid panel, sebum lipid panel, stratum corneum lipid panel, and the global metabolomic profiling. The applications of lipidomic profiling in research will be exemplified by case studies. Surveyor, the complex lipid data visualization and analysis software tool will be briefly discussed as well. Non-targeted Analysis for Quality and Authenticity Determination of Olive Oil. James A. Donarski1, Victoria Bailey-Horne1, Enrico Valli2, Diego L. García González3, and Tullia G.T. Gallina Toschi4, 1Fera Science Ltd., UK; 2University of Bologna; 3Instituto de la Grasa (CSIC), Spain; 4Alma Mater Studiorum—University of Bologna, Italy Europe is currently the largest producer of olive oil accounting for more than 70% of the world’s production. Non-EU countries are expanding their domestic production and increasing the competitiveness of the global olive oil market. The high price of olive oil, the distinctive sensory profile and its reputation as a healthy source of dietary fats makes olive oil a target for adulteration by illegal blending with other vegetable oils and deliberate mislabelling. The lack of efficient and harmonised analytical methods for detecting olive oil fraud has led to significant weaknesses that are exploited by counterfeiters. A

Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants

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.

Rapid screening of commercial extra virgin olive oil products for authenticity: Performance of a handheld NIR device

The performance of a handheld near infrared spectroscopic device was evaluated for the rapid screening of extra virgin olive oil for authenticity. Without any sample preparation, the spectra of authentic reference extra virgin olive oils, refined olive oils, potential adulterants consisting of edible oils, extra virgin olive oil spiked with adulterants, and a total of 93 commercial olive oil products were each rapidly (10 s) measured in the transflection mode. The univariate conformity index and the multivariate supervised soft independent modeling of class analogy classification tools were used to differentiate among the various oils investigated. Out of 88 commercial products labeled extra virgin olive oil, 39 (44%) were classified as belonging to the class of authentic extra virgin olive oils. The results were compared to those recently reported for analyses carried out with a benchtop Fourier transform-near infrared spectrometer.