AI and data analytics drive Kerry’s crackdown on foodborne illnesses and recalls
19 Aug 2024 --- Kerry is tapping AI, advanced analytical tools and predictive modeling to enhance its food safety and preservation practices in response to increasing consumer demands for minimally processed foods and a fresher appeal.
This comes amid mounting pressure on the F&B industry to meet “accelerated timelines,” and as a result, investments in R&D are high.
Food Ingredients First sits down with Joyjit Saha, R&D manager, and Saurabh Kumar, senior business development director - Food Protection and Preservation at Kerry to understand how to address the challenges and opportunities in improving food safety amid the current regulatory landscape.
Focus on mitigating food waste and food hunger is driving innovation in food safety practices, says Kumar. Enhanced food protection measures are also a necessity.
“Food protection and preservation is a key strategic growth pillar for Kerry and we have been making strategic investments over the last years to create a food preservation powerhouse to meet the food industry needs, and this is underpinned by scientific investments in scientific research.”
The new research, processing and supply chain conditions have outlined various risks that need to be managed.
“Clean label and natural ingredients are also key drivers from the consumers in this area, which requires a specific set of R&D-driven science to meet the needs. There’s also a preference for fresh and refrigerated food areas, not canned and that also presents new challenges.”
The industry is looking for advanced analytical aids like AI tools, predictive modeling and scientific research to meet these needs and ultimately drive value throughout the supply chain.
Evolving food safety landscape
According to the WHO, foodborne illnesses affect 600 million people and cause 420,000 deaths annually. In 2023, meat contamination led to over 1.4 million pounds of recalled products in the US, reports the USDA Food Safety and Inspection Service (FSIS). This has ramped up food safety efforts worldwide.
Kumar acknowledges an ongoing “regulatory landscape evolution” amid these developments, which calls for a technological upgrade and manufacturers to “reassess our food safety programs.” This necessitates resource-driven programs that are sometimes “prohibitive” due to time, resource or ecosystem constraints.
To address these concerns, Kerry recently unveiled a new Food Protection and Preservation Lab in Wisconsin, US. The lab will test the effectiveness of food safety protocols, develop safer methods and “prevent real-world outbreaks of deadly bacteria.”
The lab differs from its other facilities in Europe and Asia because it is “strategically built to promote high-end and new-age instruments to reduce time and effort and increase accuracy,” Saha tells Food Ingredients First. It will use predictive model tools and host validation studies, shelf life determination and ingredient screening.
“This would also provide an accelerated solution development need, which would use a lot of predictive modeling tools along with the lab data to meet those needs.”
market, consumer and sensory insights for prototype development.
Predictive models also help F&B companies uncoverTackling foodborne illnesses and recalls
Food producers recall their products from the marketplace when the products are “mislabeled” or when the food may present a “health hazard to consumers” because it is contaminated or has caused a foodborne illness outbreak.
Robotic technologies and AI are finding a place in food manufacturing and logistics.
The US agency’s recent moves, such as warning letters to a company manufacturing fruit purees with elevated lead and cadmium levels and product recalls in dairy products due to the potential risk of Listeria monocytogenes, indicate the tightening of food safety measures globally.
According to Saha, certifications like biosafety level 2 (BSL-2), such as that received by Kerry’s new lab, enable manufacturers to safely handle food safety microorganisms and enable in-house isolation of bacteria like Listeria, Salmonella and E. coli. It also includes robotic technologies and researchers dedicated to meeting its food protection needs.
“We have an in-house lab in which we can validate all the ingredients for our customers to develop safe food and help reduce foodborne illnesses or recalls.”
“It helps our customers too, if they are thinking of any new product development, or extra food safety insurance policy. We can validate those studies using BSL-2 pathogens or organisms in our lab.”
Unlocking AI in food safety
Like predictive models, incorporating AI in logistics and manufacturing for predictive forecasting, real-time adjustments and streamlined operations is also gaining ground.
According to a study published in the journal Comprehensive Reviews in Food Science and Food Safety, AI, Internet of Things (IoT), and big data are part of early warning and emerging risk identification tools in the food safety domain.
Kerry is investing in AI tools, predictive modeling platforms and a “dedicated ecosystem of data generation” for food safety and shelf life needs for emerging platforms, underscores Kumar.
“In our labs, we generate 10,000 microbial curves every week globally to be able to analyze those, which is very difficult if you don’t have state-of-the-art data analytical architecture. Kerry has unique data architecture groups, so we can analyze those curves and generated data and convert that into predictive models, which are scientifically-backed.”
The integration of predictive modeling into food safety and hazard analysis offers various benefits, such as forecasting microbial growth, identifying critical control points and optimizing preventive measures. These tools can minimize the R&D spend and accelerate product development with “minimalistic resources.”
Meanwhile, regulators are trying to ensure safe use of AI through the EU AI Act, but some have expressed concerns over manipulation, discrimination and potential impacts of AI systems on animal welfare.
Experts also warn that while AI can support innovation, F&B companies must be careful about their data due to factors like affordability issues, “AI washing” and the susceptibility of irresponsible use. For this, employee training and documentation of AI developments can prove useful.
Accelerating food safety timelines
In light of the regulatory changes and advancement in scientific methods, Kumar highlights the need to review the current practices for food safety management systems and antimicrobials and validation studies.
“We are developing predictive models for shelf life and Listeria control food safety models, which will help our customers to do those thorough reviews with much more powerful data banks with much more efficient resource consumptions and accelerated timelines,” he concludes.
By Insha Naureen
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