Finding Food Security Solutions
A TEAM OF RESEARCHERS at Kingston University in London is mining existing food inspection data to analyze trends in food safety. Though it is currently focused on data from the European Union, the system may in the future provide a way to see which countries worldwide export the most contaminated foods as well as which countries import the highest percentage of contaminated foods.
The food safety monitoring system, which was unveiled earlier this year at a meeting of the European Food Safety Authority (EFSA) and the Association of Southeast Asian Nations, has thus far been used to analyze over 15,000 alerts from the European Union’s Rapid Alert System for Food and Feed (RASFF) database for the years 2003 to 2008, says the team’s leader, Declan Naughton, a professor in the university’s school of life sciences. RASFF generates alerts for food safety authorities in EU member states. Other countries’ food export activity is captured to the extent that food from those countries coming into the EU member states generates an alert.
The analysis found that approximately five or six countries provide the majority of the faulty foodstuffs in Europe. The program identified Iran, China, and Turkey as the top three biggest transgressors for this five-year time period. The United States was fourth, with Spain following close behind.
An analysis of European detection efforts finds that approximately five countries also do most of the policing, including Italy, Germany, the United Kingdom, Spain, and the Netherlands.
“Intriguingly, Spain is in the top tier in terms of notifications in both the detector group and in the transgressor group,” says Naughton, who is also the chairman of an independent panel to assess the quality of EFSA’s scientific activities. “So Spain is the only country that’s both policing quite well but also producing faulty foods quite well.”
In his presentation at the EFSA meeting, Naughton examined alerts on the metals and mycotoxins (toxins found in fungi) that had been found in foodstuffs in order to demonstrate the capabilities of the new tool. The analysis showed that in 2003, there were about 100 cases of metal contamination cases reported in the EU and most of the cases involved seafood. Four years later, the number of total cases involving metal contamination had doubled, and in most cases, it was seafood that was contaminated by the metal.
The program is also able to detail the type of seafood and the type of metals found. This kind of analysis enabled by the monitoring program could be used for intelligent testing, Naughton says.
Mercury was the principal heavy metal found in seafood, and seafood was the principal source of heavy metals, according to the analysis. In addition, swordfish and shark were the two fish found to contain the most mercury.
“If we look carefully at swordfish and at shark and do testing of these, then we could probably eliminate a lot of mercury from our diet,” says Naughton. “It kind of tells us what to test.”
Naughton notes that only about 3 percent of the foods that come into the United States are tested, and intelligent testing could be used to target the products most likely to be contaminated.
The monitoring system allows a variety of information to be presented at one time and provides a visual picture of the trade networks between countries for a specified time period. For example, a chart tracks two indices for each country, a transgressor index and a detector index, for the five-year period. The former is illustrated using a red line and the latter by a green line. In 2008, Spain’s transgressor index rose.
The monitoring system allows the user to click on a specified time period and determine what type of contaminant may have caused a spike on the graph. In Spain in 2008, for instance, a chart detailing mycotoxins shows a low transgressor index. However, a metals chart indicates a high transgressor index. Therefore, the system indicates that metals were likely the problem in 2008.
“In a couple of minutes, somebody working in Spain could work out immediately that they need to look very carefully at their metals and seafood, because it’s really messing up their entire export system in terms of notifications against them,” Naughton says.
The program also networks countries by connecting them in a visual format that shows the country being considered, Country A, at the center of the screen. The immediate food trading partners encircle Country A and are connected to it by a line.
All trading partner countries are connected to their trading partners by a line as well. If the transgressor index of Country A is higher than its detector index, the box with the country’s name in it is red. If the detector index is higher, the box is green.
In the Spanish metal contamination example, Spain (which is Country A) is red. Italy, a trading partner, is the only green country. Thus the tool shows that Italy detected all of the metal contamination from Spain in 2008.
The charts can also help drive decisions about where to purchase certain types of foods. “If you happen to be in one of the countries attached to Italy,” Naughton says, “I would immediately see that Italy is bright green…so if I wanted to import seafood, I’d import it from Italy and ignore Spanish seafood.”
One of the goals of the project, according to Naughton, was to provide a simple tool for monitoring patterns in global food alerts for use by developing nations. He hopes eventually to upgrade the system to analyze data from around the world in real time to warn of incidents on a weekly basis.