How Technology is Winning the Fight Against Food-borne Illness

Posted On: July 18, 2024
How Technology Is Winning The Fight Against Food-Borne Illness

Food recalls can cost businesses millions in damages, and that is besides the significant effect it has on its credibility and reputation. More importantly, foodborne illnesses make about 48 million people sick in the US each year, and it is also responsible for 3,000 fatalities. 

However, the good news is that technological innovations are making responsible regulation a possibility, thus reducing the intensity of this epidemic each year. In this blog, we explore the different types of technology that help win the fight against foodborne illnesses. 

Technologies Helping the Fight Against Foodborne Illness

Even though freezing or cooling food can prevent it from going bad, it only slows down pathogen growth. This includes bacteria that cause food to spoil. Some may even thrive in cold temperatures, such as listeria, which can also multiply in the fridge and contaminate other food items

Plus, even if contaminated food is refrigerated during transportation, it can still spoil other food it encounters. In other words, even freezing food is not sufficient to impede the growth of bacteria. 

In fact, even if you practice safe food handling procedures to prevent a supply chain from being contaminated, it may not be enough. A single mistake can lead to large-scale foodborne disease outbreaks such as E-coli which can result in massive recalls. 

Fortunately, the rise of technology is helping fight against such situations. Here are some of the different technological advances helping create a safer food industry:

UV TECHNOLOGY 

Fortunately, technology that uses powerful pulsed Xenon light and violet-blue light can eliminate harmful pathogens that can cause deadly foodborne diseases such as Salmonella and the Norovirus. What is even better is that the solution can be implemented at any point in the supply chain, thus providing an additional layer of support against deadly foodborne conditions. 

BLOCKCHAIN TECHNOLOGY 

Blockchain technology is making significant strides in the fight against foodborne illnesses through its unique attributes of transparency, immutability, and decentralization. Here are the different ways blockchain technology works in the food industry:

Transparency and Traceability 

Blockchain creates a transparent and unalterable record of every transaction or movement of food products through the supply chain, from farm to fork. Each step of a product's journey is recorded on the blockchain, making it possible to trace the origins of all ingredients in a final product. This level of traceability is revolutionary because it allows for the quick identification of the source of contamination in the event of a foodborne illness outbreak.

Quick Response and Recall 

Once a contaminated product is identified, blockchain technology enables businesses to trace it back to its source quickly and efficiently. 

This rapid response capability means that contaminated products can be isolated and recalled before they reach consumers or cause widespread illness. It significantly reduces the time and resources typically involved in tracking down the source of a foodborne illness outbreak.

Enhanced Safety Standards Across the Supply Chain 

Blockchain fosters collaboration among all players in the supply chain, including producers, processors, distributors, retailers, and regulatory bodies. 

By providing a single, consistent record, it ensures that all parties have access to the same information, facilitating better coordination and compliance with safety standards. This collective oversight helps prevent lapses in food safety practices that could lead to contamination.

Data Integrity and Security 

The data recorded on a blockchain is secure and tamper-proof. Once information is added to the blockchain, it cannot be altered or deleted, ensuring the integrity of the food safety data recorded. This feature is crucial for maintaining trust among consumers and across the supply chain, as it guarantees that the product history is accurate and has not been manipulated.

Future Innovations 

Looking ahead, the integration of blockchain with other technologies like the Internet of Things (IoT) and artificial intelligence (AI) could enhance food safety even further. 

For example, IoT devices can monitor the conditions of food during transport and storage (e.g., temperature, humidity), with this data securely logged on the blockchain. Such real-time monitoring could prevent spoilage and detect potential safety issues before the products reach the market.

Data Analytics and Predictive Modeling 

Data analytics and predictive modeling use historical data and statistical algorithms to forecast future events, including the outbreak of foodborne illnesses. Here's how they contribute to the fight:

Identifying Patterns and Trends 

By analyzing vast amounts of data from various sources, including health reports, food production, and environmental conditions, data analytics can identify patterns and trends associated with foodborne illness outbreaks. This helps in understanding which conditions are most likely to lead to contamination. 

Predicting Outbreaks 

Predictive modeling uses the patterns identified through data analytics to forecast potential outbreaks. By predicting which food products and regions are at a higher risk of contamination, preventive measures can be taken proactively, reducing the occurrence and impact of foodborne diseases.

Enhancing Surveillance 

These technologies improve food safety surveillance by continuously monitoring and analyzing data from food production and supply chains. This real-time analysis allows for immediate action if any signs of potential contamination emerge.

Optimizing Food Safety Practices 

Analytics and modeling provide insights that help optimize food safety practices. For example, they can identify the most effective points in the supply chain to test for pathogens or determine the best storage conditions to prevent spoilage.

Artificial Intelligence 

Artificial intelligence (AI) extends the capabilities of data analytics and predictive modeling by adding layers of learning and automation. Here’s how AI plays a role:

Advanced Pattern Recognition 

AI, through machine learning algorithms, can recognize complex patterns in data that humans might not easily identify. It can analyze data from past foodborne illness outbreaks to predict future occurrences with high accuracy.

Automating Monitoring Systems 

AI can automate the monitoring of food safety parameters across the supply chain. For instance, it can analyze images from food production facilities in real-time to detect hygiene breaches or unsafe practices.

Natural Language Processing (NLP) 

AI uses NLP to monitor social media, news reports, and other online content for mentions of foodborne illness. This can serve as an early warning system, identifying outbreaks as they start to emerge, even before they are officially reported.

Optimization of Food Recall Processes 

AI algorithms can optimize recall processes by quickly tracing the contaminated product's journey through the supply chain, identifying all potentially affected products with precision and speed.

LEARN2SERVE FOOD SAFETY MANAGER PRINCIPLES TRAINING 

If you're taking your food manager exam for the first time or want to refresh your knowledge of food safety best practices, Lean2Serve by 360training has you covered! Our Food Safety Manager Principles training course covers everything you need to know to maintain a safe environment. 

In the course, you’ll learn about food safety issues, regulations, and techniques that will ensure you keep your customers and staff safe from foodborne illness. Additionally, the training reinforces how handling food the right way meets regulatory requirements, as well as lowers your food costs. Enroll in our food manager training today!

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