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Methodologies for Food Fraud

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Methodologies for Food Fraud Food Fraud Guide Methodologies for Food Fraud Tips for robust experimental results Executive summary Knowing that food fraud scandals often drive public awareness and regulatory changes, the goal of this paper is to present analytical techniques and experimental methodologies, and introduce multivariate statistics and sample class prediction as it relates to food adulteration. Some approaches such as molecular spectroscopy tend to be less expensive, and a few of these instruments have been miniaturized to the point where they can be field-deployed. Spectroscopic instruments are useful in fingerprinting food because small changes in a sample’s spectral profile can be detected with the latest technology, assuming appropriate data normalization techniques are applied. Similarly, the use of both unit- and high-resolution-based mass spectrometry (MS) can be important in food fraud testing because they can fingerprint food based on the pattern of discrete compounds they detect. While other techniques such as inductively coupled plasma mass spectrometry (ICP/MS) and inductively coupled plasma optical emission spectrometry (ICP/OES) have proven adept at identifying geographic origin based on trace element analysis. Genomic testing can accurately identify fish DNA, even from processed samples. From a methodological perspective, nontargeted approaches have proven effective in fingerprinting samples. The advent of inexpensive computer workstations and statistical software has made it possible to link nontargeted workflows with multivariate statistical analysis to extract useful information from analytical data. Until recently, these approaches have been too expensive or complex for researchers to perform by themselves; instead, the data had been handed over to dedicated statisticians or never fully investigated. But now, there are moderately priced tools that allow researchers to more easily use statistical approaches for determining attributes such as sample quality and building sample class prediction models. Introduction Beyond fundamental safety concerns, food adulteration cheats consumers, as As background to why adulteration is has been demonstrated with extra virgin an important issue, you may recall the olive oil (EVOO). A study from 2010 found melamine scandal that broke out in 2007 that imported olive oil, which at that when dogs and cats were poisoned by time accounted for 99% of the EVOO on their food.1 Investigations discovered the US market, often failed the sensory the dog and cat food was tainted with test for EVOO classification.6 Experts a mixture of melamine and its triazine now claim that up to 80% of EVOO is analogs (ammelide, ammeline, and fraudulently labeled.7 It is relatively cyanuric acid). These inexpensive but straightforward to perform established highly nitrogenous industrial chemicals tests for distinguishing EVOO and were being used to boost the nitrogen other grades of olive oils. Two popular content in food to give the perception examples are the HPLC measurement The Agilent 8890 GC system and Agilent 5977B 2 that the foods were rich in protein. of diacylglycerol or pyropheophytin GC/MSD. 8 As awareness grew, the adulteration (a breakdown product of chlorophyll). Many volatile and semivolatile of food with melamine quickly became However, these tests can generate compounds are routinely analyzed by an international problem. It was later false positive and false negative results, electron ionization (EI)-based GC/MS. detected in baby formula produced in and fraudsters can use an alternative This technique has the advantage of the US, cookies distributed in Canada, adulterating oil to pass the tests. EI spectra that can easily be library chocolate sold in Asia and Australia, Furthermore, there are flavor defects searched against the large NIST 17/Wiley condensed milk in Thailand, and eggs that can lead to a true EVOO not passing Registry 11 library that contains 597K in Hong Kong. During the scandal, sensory testing. Mustiness, rancidity, and compounds and over one million spectra. international agencies such as the acidity can all be issues, especially with This gives an unprecedented ability to World Health Organization, the Food and badly stored EVOO. Chemical analysis tentatively identify many volatile and Agriculture Organization, the European offers potential solutions to screen for semivolatile compounds. There are Food Safety Association, and the these issues based on the concentration some limited structure-elucidation tools, International Food Safety Authorities of specific markers such as acids, esters, such as the MS Interpreter and the Network worked together to characterize and aldehydes being found at high ppb to substructure search feature provided and control the crisis. While 68 countries low ppm concentrations.9 by NIST, which are useful with unit banned or recalled foods suspected As chemists search for more mass data. Adding a full-spectrum of containing melamine,3 many reliable tests for EMA, new analytical accurate-mass instrument such as countries established allowable limits instruments and methodologies are a GC/TOF or GC/Q-TOF provides for melamine, with the FDA maximum being explored. The key is finding the structural information and allows residue limit (MRL) as 1 part per million right technique for your application and identification of unknown compounds (ppm) for infant baby formula, and budget. through the generation of fragmentation 2.5 ppm for other products.4 The FDA trees and thermodynamic-based also set up an economically motivated MS-based food testing structure elucidation tools such as adulteration (EMA) working group. In Agilent Molecular Structure Correlator. 2009, it defined EMA as the fraudulent, Full spectrum (time of flight), scanning The FT-traps have excellent mass intentional substitution or addition of a (quadrupole), and image building resolution, but image building is not substance in a product for the purpose (Fourier transform) MS techniques are yet fully developed for EI analysis, and of increasing the apparent value of good tools for sample classification. the match factors are lowered due to that product or reducing the cost of its They vary in price from inexpensive gas missing peaks. One solution to this production (that is, for economic gain).5 chromatography/mass spectrometry problem is to develop a proprietary (GC/MS) instruments, more expensive identification algorithm that places Fourier transform mass spectrometers greater emphasis on mass accuracy, and (FTMS), to high-price, high-value liquid less weight on missing ions. phase ion mobility quadrupole time of flight instruments (IM/Q-TOF). 2 Feature-finding analysis batch-wise manual editing of the results oxidation. Volatile components such There is also a mixture of commercial should be permitted following batch as these are relatively easy to separate and academic feature-finding tools recursive feature extraction. XCMS chromatographically, and can be used going back to AMDIS that was made is an online public resource for the to evaluate sensory attributes as well public by NIST in the early 1990s.10 A nontargeted analysis of small molecules as characteristics associated with rice good academic solution for EI peak developed by The Scripps Research adulteration.15 Subsequently, integrating alignment and data extraction is the Institute that follows a similar workflow headspace solid-phase microextraction AMDIS/manual curation/SpectConnect. to fill in missing peak data.12 into the methodology eliminates much of 16 Unlike XCMS and MZmine, SpectConnect Once the feature-finding data have been the sample preparation. is specifically designed for EI data. reviewed and any integration errors GC also lends itself to multidimensional addressed, the data can be exported chromatography with various as text files. If a peak is not found, it commercially available solutions from is considered missing. There may be companies such as Agilent, LECO, an option in the statistical software and ZOEX. An advantage for these to treat missing values either as zero techniques is that they typically have abundance or as peaks that were a higher signal-to-noise (S/N) than not found. Selecting zero abundance the unmodulated counterparts. Their strongly impacts the statistics. Choose disadvantage is that they require this option only if the data have been specialized hardware and peak carefully reviewed, and it has been deconvolution tools from companies confirmed that the peak is missing. such as GC Image. This software tool Select missing values if the data are works well for analyzing samples not carefully reviewed and the missing sequentially, but has not been optimized component might be a false negative. The Agilent 1290 Infinity II LC system with an for batch analysis, a cornerstone of Targeted and nontargeted methods Agilent 6546 LC/Q-TOF. nontargeted analysis.11 The combination of targeted and To build reproducible prediction models, Nontargeted workflows depend on nontargeted chemometric approaches MS-based EMA methods should focus reproducible feature-finding software, provides a good solution when on finding robust identifiers instead ideally based on recursion. Recursive evaluating samples that allow accurate of all identifiers. An example of this feature finding aims to minimize both identification of expected compounds, approach is when a LC/Q-TOF was false positives and false negatives. but also allow for the presence of used in full-spectrum mode to show It does this by eliminating ions unexpected
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