The Scientist’s Role in Combating Food Fraud
Using both targeted and non-targeted analysis, scientists are improving the ability to detect, and even prevent, cases of food fraud
The global food supply chain is a complex mechanism that provides the world with food for survival and enjoyment. Each step—from growing the raw materials to production of finished products— presents its own challenges to ensure that safe food is produced and consumer expectations are met. Unfortunately, there exists unscrupulous individuals looking to make an illegal profit along the way.
Food fraud is one of the most urgent and active areas of interest in the food industry. Food fraud includes a range of activities, including mislabeling, theft, or counterfeiting, that are conducted intentionally with the goal of a financial benefit. Economically motivated adulteration (EMA)—when a food is adulterated through dilution, substitution, or contamination—is where the analytical scientist can provide great value in identifying cases of food fraud.
Evolution of food fraud
How big of a problem is food fraud? It is estimated that the cost to the food industry is $30-40 billion per year and that ~10 percent of all commercially produced food and beverages are affected by fraud. Not only is there a monetary impact, but consumer safety and confidence are also at significant risk.
Ever since food has been produced for sale, EMA has been part of the picture. Going back to Rome 2,000 years ago, laws against food fraud can be found regarding the adulteration of wine. During the middle ages, adulteration of spices, milk, sweets, and many other items have been documented. Although laws are in place in the US and globally, food fraud continues to be a problem today. The drive for profit or to meet the call for scarce ingredients continues to feed motivations to conduct food fraud. Many examples can be found in news headlines. Some of which are outlined in the table below.
| Food fraud occurrence | Findings | Outcome |
|---|---|---|
| Melamine in infant formula and powdered milk (China 2008) | Dairy product quality can be evaluated by protein amount, which is often determined by nitrogen level. The addition of compounds high in nitrogen (i.e. melamine) gives a false high level of protein. | ~300,000 Chinese infants and young children were affected. 57,000 hospitalization and 6 reported deaths. |
| Olive oil adulteration (US 2016) | UC Davis Olive Center estimates that >70 percent of extra-virgin olive oil imported to the US was adulterated or mislabeled. | Although not a food safety issue, consumer trust was greatly eroded. |
| Adulteration of cumin with peanut and almond shells (2014) | Due to issues with the cumin harvest in India, cheaper materials were added to cumin to meet world demands. | In 2014 alone, 675 products were recalled due to undeclared peanut in products that contained cumin. Risk to those allergic to peanut. |
| Horse meat found in beef samples in Europe (2013) | Cheaper horse meat was substituted for beef. | One-third of frozen beef hamburgers tested found to contain horse. In addition, 85 percent contained pork. |
Challenges of identifying food fraud
When trying to identify food fraud, it is useful to think about the composition of different foods. Foods are a complex mixture of components and chemicals. No food consists of a single chemical compound. There aren’t any tests for measuring the amount of olive oil, or cumin, or milk, but rather components or aspects of the food are measured to determine adulteration. While a consumer might look at color, odor, flavor, or other sensory properties of a food to determine its quality, scientists look at fatty acid profiles of oils or protein levels in milk to evaluate quality. Fraudsters can easily fool the consumer’s senses. Diluting milk with water could lighten the color of the milk, but the fraudster could add chalk or other white colorant to offset that effect. Replacing honey with cheaper corn syrup or extra virgin olive oil with cheaper oils are easy ways to increase profit with few, if any, consumers noticing.
The approach that science takes to measure components present in food can also be misled. Using protein levels in milk is an effective way to detect the fraud mentioned above. The analytical scientist can’t measure protein level directly, but rather they determine protein by measuring nitrogen levels in a sample, then calculating protein based upon that number. Once the fraudster knows how the testing is being conducted, they find a way around it. By adding a chemical with a high nitrogen content (i.e. melamine), the analytical test is tricked into believing that the protein level is high in the milk. It then becomes imperative that the food scientist can detect for compounds like melamine. But how can the food scientist know what the fraudsters are adding to the foods in advance?
Examples of this type of fraud can be seen in many other products, from orange juice to vanilla extract. The key to limit the prevalence of food fraud is to find new approaches and technologies to stay at the forefront.
Combating food fraud
As this battle rages between fraudsters and analytical scientists, science is using a multi-pronged approach of prevention and detection.
Prevention
Various global agencies and organizations are working together to combat food fraud. This is accomplished by sharing information globally about what adulterations have occurred to determine what foods and ingredients are most likely to be adulterated. The US Pharmacopeia (USP) has developed a Food Fraud Mitigation Guidance document to help companies develop a system for identifying vulnerabilities in their ingredient supply chain and create a control plan to mitigate risks.
To help with identifying vulnerable materials, a food fraud database was developed by USP and is now maintained by Decernis. The database is a continuously updated collection of thousands of ingredients and related records gathered from scientific literature, media publications, regulatory reports, judicial records, and trade associations from around the world.
Education is another vital factor in preventing food fraud. Michigan State University, under their Food Fraud Initiative led by John Spink, PhD, director, Food Fraud Prevention Academy Think Tank, offers Massive Open Online Courses (MOOC) on food fraud prevention. These courses are offered for free on their website. John Spink also wrote the first textbook published on the topic of food fraud prevention, Food Fraud Prevention – Introduction, Implementation, and Management.
Other programs like the Global Food Safety Initiative (GFSI), the EU Food Fraud Network, and INFOSAN are increasing the awareness of food fraud and how to combat it. Individual companies are also getting on board—Mars Global Food Safety Center based in Beijing, China, addresses food safety issues including food authenticity issues.
Detection
The ability to detect food fraud has become a big business, with instrument companies dedicating departments and instrumentation to combat food fraud. The approach currently being used to detect EMA can be broken down into two strategies—targeted and non-targeted analysis.
Targeted analysis looks for pre-defined characteristics or adulterants, and focuses on the detection of a few selected analytes. This is highly effective since adulterants are typically added at significant levels, making them easy to detect when the analyte of interest is known. Methods such as chromatography, spectroscopy, DNA sequencing, and even thermal analysis can be used if known standards of the adulterants are available. Some of the challenges with this approach are that you need to know what the adulterant is ahead of time, and the methodologies can require extensive sample preparation and long turnaround times.
Non-targeted analysis aims at studying a global fingerprint that should be as comprehensive as possible. This approach is advantageous when no information about the adulterant is known or unconventional adulterants are added. While mainly using spectroscopy methods, other analytical techniques can be used. The key is to have powerful data analysis programs that can identify when samples look out of the ordinary. By scanning hundreds of authentic samples, a rich database is obtained for comparison and the chemometric software can identify samples that do not fit into the normal range. This is an ideal approach for screening high throughput of samples and requires little to no sample preparation. This strategy is still developing and lacks overall guidance or legislative methods, but as advances in software and analytical techniques progress, non-targeted analysis is proving to be a powerful tool in identifying food fraud.
Consumer safety and confidence are of utmost importance when considering the food supply chain and analytical scientists are feverishly working on ways to eliminate food fraud. As new prevention approaches are developed and testing technologies and data analysis improve, food fraud detection has become a highly intense field of study.
