I’m not sure what big data means, but it’s a catchy soundbite that is showing up more routinely.
Prof. Martin Wiedmann, food science and technology, has combined the fields of microbiology and big data to better predict disease outbreaks and preserve food safety.
Wiedmann conducted a study focused on Listeria monocytogenes bacteria and related Listeria species — a leading cause of foodborne illnesses and deaths.
“The main goal of the study was to find better ways to determine whether lettuce or similar produce grown in a field are likely to have bacteria on them that could make you sick if you eat the product,” Wiedmann said.
According to Wiedmann, there are about 1,600 cases of Listeriosis annually in the United States, with more than 20 percent of those infections resulting in death.
“It is definitely not your middle-of-the-road food poisoning disease, which makes [Listeria] so important to understand and study,” Wiedmann said.
Normally, raw and unprocessed foods will be preserved with refrigeration or salting to prevent bacterial growth. Listeria can grow under refrigeration temperatures and high salt environments, thus making these typical methods ineffective at killing off the bacteria.
Products that are taken directly from growing conditions and consumed are high risk produce. They are the foods most likely to transmit foodborne pathogens — unless necessary precautions are taken.
“Therefore, it is necessary to make sure the product is safe and free of these pathogens while it is still in the field,” Wiedmann said.
Wiedmann and colleagues collected many samples from various farms in upstate New York.
“In addition to isolating Listeria species from the sample, we also collected Geographic Information System data (GIS), which records the exact location of where the sample was collected,” Wiedmann said. “With this, we can ask questions such as how close was Sample A to water or to a major road?”
Wiedmann uses the data to understand the factors that are conducive to Listeria growth.
Analysis of the data revealed that proximity to water is a major factor of a high risk Listeria presence.
“The analysis of the data allows us to predict high and low risk areas for Listeria and also see whether different types of the bacteria behave differently,” Wiedmann said.
He has also started working on collecting data for Salmonella and Escherichia coli, two other very important foodborne pathogens. According to Wiedmann, the next steps will be to analyze different states and regions in conjunction with different pathogen species to better understand food production and the pathogens that afflict it.