JAMES C. GRIFFITHS

Fraudulent additions of melamine to the animal and human food supply in 2007 and 2008 were clear cases of intentional adulteration fueled by knowledge of chemistry and criminal intent (Xin and Stone, 2008; FDA, 2009). The addition of melamine took advantage of an analytical vulnerability of the widely used Kjeldahl and Dumas test procedures for measuring protein content in foods. Both procedures determine protein as the fraction of nitrogen measured times a nitrogen-to-protein conversion factor. Dumas analysis generally measures all forms of nitrogen, and the Kjeldahl analysis measures only organically bound nitrogen plus ammonia with incomplete or no recovery of nitrates and nitrites. Use of these approaches to quantify protein can be exploited by simply adding a cheap organic compound that contains nitrogen (Abernethy et al., 2008). These unfortunate incidents not only took human and animal lives and harmed many more but also resulted in severe financial consequences for food producers and consumers because of price increases, market disruptions, trade restrictions, product liability costs, loss of revenues, and brand damage (Ingelfinger, 2008; Kennedy, 2008). To protect consumers from future intentional adulteration of protein-based foods with melamine or other adulterants, food safety nets need to be reinforced with new analytical strategies whose vulnerabilities cannot be as readily exploited.To boost protein content, melamine was being added to Chinese wheat gluten used in pet food.

Common wisdom suggests that testing to absolute safety is not possible, especially considering the food industry’s use of intricate global supply chains and complex formulations to produce finished products. Although this offers more products to consumers at lower prices, it also introduces new challenges to maintain the integrity and safety of food ingredients and resulting food products. Numerous tools are available to help maintain the integrity of food ingredients as they pass through the supply chain; chemical-analytical verification of identity and quality is an essential tool. However, frequent testing introduces time delays, logistical complexities, and costs that are ultimately passed on to consumers. A manufacturer’s decision about when to test a food ingredient and what analytical method to employ is often driven by a risk–benefit analysis that weighs the assurance and protection gained by testing against the costs incurred.

Verifying the Integrity of Food
In principle, there are two ways to use analytical chemistry to verify the integrity of food ingredients: testing to confirm the absence of adulterants or testing to confirm the identity, quality, and purity of an ingredient. By late 2007 it was widely known that melamine was being added to Chinese wheat gluten intended for use in pet food in order to artificially boost the protein content of this high-protein ingredient. However, this knowledge was not immediately translated into a realization that other high-protein ingredients were equally vulnerable to this type of adulteration. In fact, only the clustered occurrence of renal failure in babies less than two years later led to the discovery of the melamine adulteration of the Chinese dairy supply chain and the development of reactive monitoring strategies and new methods to test for melamine in different food matrices (Huang et al., 2009; Mauer et al., 2009; Wang et al., 2009; Zhu et al., 2009).

Checking for Adulterants
Testing for the absence of a specific adulterant has one critical limitation: it requires the a priori knowledge of the existence and nature of an adulterant, and it prevents only adulteration with this specific, known adulterant and not other known or unknown adulterants. Additionally, a priori knowledge of the adulterant does not always prevent its fraudulent use. The risk–benefit analysis to use testing to detect adulteration presumes a decrease in testing if data suggest that a particular adulterant is not a threat in order to shift resources to other adulterants that have a higher likelihood of occurrence. This process, however, may lead to a cyclical reoccurrence, as exemplified by the adulteration of wheat with urea. One of the first reports of the adulteration of feed with non-protein nitrogen compounds such as urea was published in 1959 (Huss, 1959). As time passed, the perceived risk of urea adulteration in wheat decreased notably, perhaps because of efficient monitoring programs employed throughout the wheat supply chain. In 1988 this specific type of adulteration resurfaced when wheat was again adulterated with urea (Folkenberg, 1990).

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Reactive monitoring strategies for specific adulterants are also limited by the ever-increasing sensitivity of analytical methods that are capable of detecting the adulterant at levels that may be toxicologically irrelevant and/or not the result of intentional adulteration. For example, recently proposed international safety limits for melamine are in the 0.5–2.5 parts per million (ppm) range (Codex Alimentarius, 2010), but LC-MS/MS methods are capable of detecting melamine in the parts per billion (ppb) range when melamine levels have been reported from pesticide residues and other sources that are not related to adulteration (Taylor et al., 2008; WHO, 2009).

The Compendial Strategy
Other strategies to prevent adulteration are available and may help to circumvent the disadvantages of reactive monitoring. One is to specifically look and test for the identity, quality, and purity of a food ingredient—that is, what should be in a food ingredient instead of what should not. This is the compendial strategy, which comprehensively compares the authenticity, identity, and purity of test ingredients with established criteria. Examples include monograph testing standards in the Food Chemicals Codex (FCC) published by the U.S. Pharmacopeia, the Compendium of Food Additive Specifications published by the Joint FAO/WHO Expert Committee on Food Additives (JECFA), and others. This strategy employs complementary analytical testing approaches: qualitative identification methods to determine if an ingredient is authentic and quantitative purity assessment methods to precisely quantify what should be in an ingredient.

The compendial strategy can be used to detect known and unknown adulterants that are present in sufficient amounts to influence the identity and or purity of a food ingredient. Hence, this approach can be one of the best defense mechanisms against economically motivated adulteration in which adulterants typically are added in significant amounts. However, analytical accuracy and sensitivity may limit the use of this approach for low-level adulteration. For example, to detect the presence of an adulterant at 900 ppm, using a purity assessment approach, one must reliably detect the difference between 99.91% and 100% purity. Such a goal may be well beyond the capability of most routine measurement techniques. Although this may appear to be a real limitation in preventing intentional adulteration with known or unknown adulterants, in reality most adulterants must be present at much higher levels to make adulteration for economic gain profitable. In the case of melamine, for example, to reduce the cost of wheat gluten by 50%, adulteration with melamine at 10% would be necessary (DeVries, 2009).

Unfortunately, in the melamine incidents a reliable compendial approach for protein-based ingredients did not exist. Compendial standards for testing the purity of protein-based ingredients still rely on total nitrogen determination techniques with a numerical conversion to apparent protein content, and their lack of specificity renders these methods susceptible to the presence of other non-protein sources of nitrogen. This vulnerability indicates an urgent need to advance analytical science in these areas to prevent future economically motivated adulteration of high-protein food ingredients.

Future Challenges
The challenge ahead in developing new procedures for testing protein-based food ingredients lies in the analytical performance requirements. New test methods must be specific, validated for each matrix, precise, suitable for routine analysis, inexpensive, and rapid because a large quantity of food protein must be tested: The estimated annual total global production of food protein is 400 million metric tons or more (Owusu-Apenten, 2002).

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To reliably and quantitatively determine the purity of food protein, new total protein determination methods need to be established with higher discrimination power against the presence of nonprotein nitrogen sources. A recently published review sheds some light on opportunities and challenges in this area (Moore et al., 2010). This report suggests a few promising analytical techniques such as modifications to existing total nitrogen approaches to selectively isolate protein before analysis, use of well-known colorimetric techniques like Bradford, or measurement of total amino acid contents. However, all of these techniques require further evaluation to determine their suitability for this specific analytical need. Also, many of these promising techniques may be compatible only with food ingredients that consist mainly of protein and/or show a relatively low degree of variability in compositions. It should be noted that the dairy industry has already improved the basic Kjeldahl method for the bovine milk matrix by selectively precipitating and separating true protein from non-protein nitrogen before performing the Kjeldahl total nitrogen procedure (Barbano and Clark, 2006).

For qualitative authentication of protein-based food ingredients, new rapid techniques capable of detecting the presence of inauthentic proteins and unexpected non-protein compounds must be established. Conceptually, such methods could compare the compositional fingerprint of a test ingredient and a library of authentic fingerprints for that ingredient to yield a simple answer about whether a sample is abnormal or normal. For more than a decade, use of spectral or hyphenated chromatographic–detector techniques combined with chemometric data analysis (e.g., principal component analysis) has been reported in single lab studies for authenticating foods (Downey, 1996; Tzouros and Arvanitoyannis, 2001; Karoui and Baerdemaeker, 2007). Several challenges must be resolved before this approach can gain widespread use in routine analysis of protein food ingredients, such as ensuring comparability of results among instruments and labs and accounting for the compositional variability of authentic food ingredients produced around the world. An opportunity to correct for the latter is the generation, maintenance, and dissemination of ingredient-specific fingerprint data libraries that represent the entire range of authentic materials in commerce. This is a significant issue because of the number of factors that can influence the composition of food protein ingredients, including genetic variation across species, differential within-species metabolic responses to the environment, and variation in processing. For comparability of results between instruments, calibration transfer standards are needed to standardize the data libraries to the unique performance of each instrument. In terms of current analytical capabilities, the use of infrared spectroscopy is already commonplace for quantitative quality assessment, particularly in the dairy industry, and could potentially be adapted for use in assessing authenticity (Barbano and Clark, 2006).

Solution for Adulterants
Detection of potential adulterants in food proteins remains a challenge. Because the nature and thus the safety implications of adulteration are entirely in the hands of criminals, an important but often unknown public health threat exists. Currently available testing procedures to ensure the quality of protein-based food ingredients are based on determining the total nitrogen content. The low discrimination power of these procedures leaves consumers vulnerable to economically motivated adulterations. The compendial testing strategy has the potential to significantly mitigate this risk but requires critical advancements in analytical science to develop and establish new authenticity and purity analytical methods. To be useful, methods following a compendial test strategy must meet the demanding analytical performance requirements of the food industry that sources protein-based ingredients through complex and global supply chains. Rapid definitive assessment of the quality and safety of raw materials will produce safe and affordable foods.

 

Jeffrey C. Moore, Ph.D., a Member of IFT, is Scientific Liaison, Food Chemicals Codex, at the U.S. Pharmacopeia ([email protected]). Markus Lipp, Ph.D., a Member of IFT, is Director, Food Standards, at the U.S. Pharmacopeia ([email protected]). James Griffiths, Ph.D., a Member of IFT, is Vice President, Food, Dietary Supplement and Excipient Standards at the U.S. Pharmacopeia ([email protected])

References

Abernethy, D.R., Sheehan, C., Griffiths, J.C., and Williams, R.L. 2008. Adulteration of drugs and foods: compendial approaches to lowering risks. Clin Pharmacol Ther 85:444–447.

Barbano, D.M. and Clark, J.L. 2006. Major advances in testing of dairy products: Milk component and dairy product attribute testing. J Dairy Sci 89: 189–1194.

Codex Alimentarius, Joint FAO/WHO Food Standards Program, Codex Committee on Contaminants in Foods, Joint FAO/WHO Food Standards Program. 2010. Proposed draft maximum levels for melamine in food and feed (N13-2009). ftp://ftp.fao.org/codex/cccf4/cf04_05e.pdf. Accessed May 15, 2010.

DeVries, J.W. 2009. Industry perspectives on protein measurements and preventing intentional adulteration. Presented at the U.S. Pharmacopeia’s Food Protein Workshop, June 16–17, 2009. http://www.usp.org/pdf/EN/meetings/workshops/openingPlenary.pdf. Accessed May15, 2010

Downey, G. 1996. Authentication of food and food ingredients by near infrared spectroscopy. J. Near Infrared Spectrosc 4: 47–61.

FDA. 2009. U.S. Food and Drug Administration’s Public meeting on economically motivated adulteration. http://www.fda.gov/NewsEvents/MeetingsConferencesWorkshops/ucm163619.htm. Accessed May 15, 2010.

Folkenberg, J., Nelson, R., and Snider, S. 1990. Spiked wheat – Schuler Grain Co. uses additive to artificially boost the protein content of its wheat. FDA Consumer 24 (December)

Huang, G., Ouyang, Z., and Cooks, R.G. 2009. High-throughput trace melamine analysis in complex mixtures. Chem Commun 5: 556–558.

Huss, W. 1959. Microscopic and enzymic methods for detection of adulterations of feeds with urea. Landwirt Forsch 12: 171–177.

Ingelfinger, J.R. 2008. Melamine and the global implications of food contamination. N Engl J Med 359: 2745–2748.

Karoui, R. and Baerdemaeker, J.D. 2007. A review of the analytical methods coupled with chemometric tools for the determination of the quality and identity of dairy products. Food Chem 102: 621–640.

Kennedy, S. 2008. Why can’t we test our way to absolute food safety. Science 322: 1641–1643.

Mauer, L.J., Chernyshova, A.A., Hiatt, A., Deering, A., and Davis, R. 2009. Melamine detection in infant formula powder using near- and mid-infrared spectroscopy. J Agric Food Chem 57: 3974–3980.

Moore, .J.C., DeVries, J.W., Lipp, M., Griffiths, J.C., and Abernethy, D.R. 2010. Total protein methods and their potential utility to reduce the risk of food protein adulteration. Compr Rev Food Sci F 9: 330–357. doi: 10.1111/j.1541-4337.2010.00114.x

Owusu-Apenten, R.K. 2002. Food protein analysis: quantitative effects on processing. New York: Marcel Dekker, Inc. 488 p.

Taylor, A., Sakuma, T., and Schreiber, A. 2008. A new, fast and sensitive LC/MS/MS method for the accurate quantitation and confirmation of melamine and cyanuric acid in pet food samples. http://www.barascientific.com/article/Melamine/PDF/Melamine.pdf. Accessed May 15, 2010.

Tzouros, N.E. and Arvanitoyannis, I.S. 2001. Agricultural produces: synopsis of employed quality control methods for the authentication of foods and application of chemometrics for the classification of foods according to their variety or geographical origin. Crit Rev Food Sci 41: 287–319.

Wang, Z., Chen, D., Gao, X., and Song, Z. 2009. Subpicogram determination of melamine in milk products using luminalmyoglobin chemiluminescence system. J Agric Food Chem 57: 3464–3469.

WHO (World Health Organization). 2009. oxicological and health aspects of melamine and cyanuric acid, Report of a WHO Expert Meeting, in collaboration with FAO and supported by Health Canada, December 1–4, 2008. http://whqlibdoc.who.int/publications/2009/9789241597951_eng.pdf. Accessed May 15, 2010

Xin, H. and Stone, R. 2008. Tainted milk scandal. Chinese probe unmasks high-tech adulteration with melamine. Science 322: 1310–1311.

Zhu, L., Gamez, G., Chen, H., Chingin, K., and Zenobi, R. 2009. Rapid detection of melamine in untreated milk and wheat gluten by ultrasound-assisted extractive electrospray ionization mass spectrometry (EESI-MS). Chem Commun 5: 559–561.