Keeping our food safe entails far more than meets the eye. Genome sequencing and statistical modeling help track bacteria’s transmission and survival. (Photo Credit: Dave Burbank)

Food Safety from Farm to Table

Cornell Research and Innovation
6 min readDec 4, 2018

by Jackie Swift

Foodborne illness has been making the news recently. Lettuce, fresh fruit, hamburgers, eggs, prepared salads — the list of culprits includes both plant-based and animal-based foods. “In the United States, an estimated 50 to 60 million people get a foodborne illness in a given year,” says Martin Wiedmann, Food Science. “Most of the time, it’s mild enough that the person doesn’t have to go to the doctor, but there are 3,000 deaths annually in this country. Globally, the impact is much larger, especially among children.”

Photo Credit: Dave Burbank

Salmonella and Listeria

Wiedmann studies both microbial food safety and microbial food quality. His lab specifically focuses on the bacteria Listeria monocytogenes and salmonella, which are the first and the third most common causes, respectively, of death from foodborne pathogens in the United States.

“Our goals are to understand how these two types of microbes are transmitted, then use that knowledge to reduce food safety hazards,” he says. “We look at the big picture, all the way from primary production on the farm to the finished product.”

“In the United States, an estimated 50 to 60 million people get a foodborne illness in a given year…There are 3,000 deaths annually in this country.”

Wiedmann and his collaborators also focus on the problem from a microscopic, mechanistic level, investigating the methods these bacteria employ to survive and grow as they’re transmitted along the food chain. The researchers want to identify how the bacteria adapt to stress conditions, such as cold temperatures, sanitizers, and acid, then use that knowledge to better improve technologies used to kill the organisms.

Tracking Bacteria from Their Genesis

Whole genome sequencing of bacterial DNA is a key tool for Wiedmann. “In some processing facilities, for example, we’ve used whole genome sequencing to characterize bacteria that we found in the environment,” he explains. “We ask, ‘How did this organism cause human disease? How likely is it to be transmitted along the food chain? Where is it coming from?’ Bacteria like salmonella can come from reptiles, from warm-blooded animals, from humans. Very often the genetic material of salmonella will tell its origin. That helps us identify sources, then move to intervention.”

Like detectives, the researchers follow the leads provided by DNA fingerprinting, pinpointing not only which processing plant is the source of a particular contamination episode, for example, but which specific type of equipment is to blame. “We may even trace it to a distinct design feature or design problem that makes complete cleaning and sanitization impossible in a certain part of the facility or for a certain piece of equipment,” Wiedmann says. “If we can fix the design and the sanitization process, we can eliminate the bacteria.”

Wiedmann works with a wide range of collaborators on a multitude of projects. One of his most important long-term collaborations has been with Kathryn J. Boor, Food Science. Their research has focused on both stress response systems and dairy spoilage. Other collaborators include Yrjö T. Gröhn and Renata Ivanek, Population Medicine and Diagnostic Sciences. With Ivanek, Wiedmann has worked on statistical and machine-learning modeling approaches to develop mathematical reflections of the transmission of pathogens. “We want to quantify how likely an organism is to move from place to place and cause human disease,” Wiedmann says.

Photo Credit: Dave Burbank

Modeling can help companies strategize their responses to foodborne pathogens. For example, if bagged lettuce sold in grocery stores becomes contaminated by salmonella, the producer must decide where to focus efforts to destroy the pathogen. “The lettuce could be contaminated by irrigation water, by soil in the field, by animals that visit the field, by harvest equipment, by transport equipment, or in the processing facility,” Wiedmann explains. “It could even be contaminated at the retail level, in the consumer’s refrigerator, or as a result of consumer handling. The problem could be anywhere in that chain. By integrating all that information into our models, we hope people can model out, simulate, and predict the most effective control strategy to remove the pathogen.”

Extending the Shelf Life of Food

Wiedmann uses these same approaches to investigate microbial spoilage and to create strategies to extend the shelf life of foods. In one line of research, he and his collaborators have developed mathematical models to better predict how long a particular food will remain fresh. “Spoiled food is safe to eat; it just doesn’t taste good,” Wiedmann says. “So we put expiration dates on things. You might have a carton of milk with a date on it. But what’s the science behind that date? Is that an accurate reflection of reality? We want to find the right balance and put enough science behind it to reduce food waste while maintaining the product’s quality and safety.”

Storage techniques have a big impact on shelf life, so the Wiedmann lab is looking at ways to give details of a product’s storage history to retailers and ultimately to consumers. The idea is to include an indicator on the packaging that would give an accurate account of the food’s storage conditions over time. “If a carton of milk was stored at 38 degrees Fahrenheit since it was made, that milk has a longer shelf life than one that was stored at 48 degrees Fahrenheit for three days somewhere along the way,” Wiedmann says. “If you have a QR code you can scan with your smart phone, you can predict how long that milk will last after you buy it.”

Members of the Wiedmann Lab (Photo Credit: Dave Burbank)

Potentially retailers could even engage in what Wiedmann calls dynamic pricing. A carton of milk that has only two days of shelf life left might cost less than one that has six days left. “We’re trying to integrate all these sophisticated data sources to make these practical decision-making tools,” Wiedmann says. He is collaborating with Aaron A. Adalja, The Hotel School, on questions of dynamic pricing. Further research with Ralph D. Christie, Dyson School of Applied Economics and Management, on the business value of modeling-based approaches to shelf life prediction is also in the works.

Wiedmann is also the codirector of the New York State Food Safety Center of Excellence, a collaboration between Cornell and the State of New York Department of Health. As part of that work, his lab trains New York State health departments on the usage of whole genome sequencing to better detect and trace outbreaks of foodborne illness. In one particular case, they joined with the State of New York and the Centers for Disease Control to trace the origin of an illness back to a particular plant, which was then shut down. “If we hadn’t done that work, the outbreak would have gone on longer, and people would have died,” Wiedmann says. “Some people are alive today because of that research. That’s why I do this work. There’s the thrill of basic scientific discovery and the knowledge that my research makes a difference.”

Originally published on the Cornell Research website. All rights are reserved in the images. If you’d like to reproduce the text for noncommercial purposes, please contact us.

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