Every global supply chain faces constant pressures between economic shifts, tariffs, and logistics challenges. But disruptions in the food supply chain carry unique consequences. They don’t just impact bottom lines – they can lead to food insecurity, price spikes, widespread waste, and even create uncertainty about food safety. A single delay or temperature spike can mean spoiled produce, unsafe products, or empty shelves.
In the U.S. alone, food travels an average of 1,500 miles before reaching consumers – and every mile introduces risks. Managing this complexity requires more than just traditional tracking methods. Without accurate, item-level data, grocers and suppliers are forced to operate in the dark, making it difficult to respond quickly to these potential disruptions.
In a 2025 survey conducted by Impinj of supply chain leaders in the food and grocery sectors validates this challenge. While 90% of respondents believe their organization is equipped to drive accurate supply chain visibility, only one-third actually have a consistent, 360-degree, real-time view. This data accuracy gap makes it difficult to anticipate issues or respond quickly when disruptions occur, and it comes with a serious cost.
Closing the Data Accuracy Gap
To manage these challenges, many organizations are turning to item-level visibility technologies, such as RAIN RFID, which have become increasingly present across food supply chains. Unlike traditional barcodes that require manual line-of-sight scanning, RAIN RFID tags can be attached to or embedded in packaging and read in bulk. Employees can count thousands of items in seconds and generate rapid inventory reports, which increases the likelihood that they can identify errors before they become problems.
Major food retailers are already seeing results. Chipotle, for example, has adopted RFID to track food shipments to its 3,300 restaurants, while Kroger plans to deploy it enterprise-wide to support its omnichannel purchase strategy and improve inventory accuracy.
Technology like RAIN RFID isn’t just a tool, but a foundation for proactive management. More precise item-level information unlocks several opportunities for grocers, such as more targeted recalls, optimized inventory, and minimized waste. It is with this level of visibility that grocers can move from reacting to problems to strategically managing them – whether it’s responding to a major recall or reducing everyday waste.
Food Safety and the Cost of Blind Spots
Food safety has always been a top priority for grocers, especially as regulations evolve. Last year, the FDA postponed the compliance date for its Food Traceability Rule – a decision supported by many in the industry grappling with supply chain complexity. But delayed compliance requirements don’t eliminate risk.
Recalls are expensive, time-sensitive, and widely disruptive – and they illustrate how data blind spots can escalate quickly. In Q3 2025, the FDA logged 145 food recalls – its second-highest quarterly total since 2020.When grocers lack item-level visibility, even a single recall can trigger massive over-removal of products. Without knowing exactly which pallets or shipments are affected, or where those items are located on shelves, retailers may be forced to discard entire batches of product, including items that are safe. This over-removal not only amplifies financial losses but also undermines consumer trust and increases waste.
However, item-level visibility technologies like RAIN RFID enable retailers to gain a detailed record of each product’s journey from supplier to shipment to shelf. In the event of a recall, RAIN RFID can enable brands to remove only the affected items, reducing unnecessary food waste.
The Billions Lost to Everyday Waste
Routine spoilage and waste drain billions from grocery operations. Managing perishables across departments is inherently complex, and visibility gaps only make it worse.
ReFED, a US-based non-profit that works to reduce food loss and waste across the U.S. food system, estimated that the cost of surplus and wasted food for businesses and consumers reached a staggering $473 billion in 2022 alone. And last year, grocery and supply chain leaders felt the impact. According to Impinj’s 2026 report, 75% cited waste reduction as a major challenge, and respondents estimated losing an average of $79 million annually to food waste and spoilage.
Addressing these challenges requires more than just better forecasting. It demands item-level visibility into every product’s journey throughout the supply chain. RAIN RFID offers a practical way to close these visibility gaps, helping grocers track inventory and optimize it before it goes to waste.
Building a Smarter Food Supply Chain
While the food supply chain faces time-sensitive challenges and heavy regulation, innovative technologies are making it easier to manage operations, improve efficiency, and build resilience.
By leveraging item-level visibility through RAIN RFID, grocers and suppliers can close the data accuracy gap, create smart solutions for food safety, and reduce waste. The result is a smarter, more reliable food system that reduces losses and enables grocers to focus on delivering streamlined customer experiences.
Plant-based companies have to compete with themselves and animal products. Safety could be the key thing that sets them apart and allows them to become more common on grocery store shelves.
Keeping food free of contaminants, as well as preserving its taste, color and smell, are essential metrics for manufacturers to follow. It is crucial for preventing foodborne illness and crises caused by recalls. These issues have plagued almost every corner of the food sector, particularly in the meat industry. Safety slips will also pose a risk to plant-based food safety if left unchecked, especially as it grows in demand and popularity.
Countering the “Health Halo” Effect
Plant-based burger made with Boca-brand patties
For plant-based products to succeed, food safety and quality experts need to treat them with the same level of compliance and safety as any other food. Just because they do not contain animal parts does not mean they are free from potential problems, and the industry needs to keep this top of mind if they want to stay competitive.
Lund University lecturer, Jenny Schelin, warned the food industry, saying, “There is a naive belief that plant-based food is safer than animal-based food. Unfortunately, this is not the case. Plant-based foods are just as vulnerable to the same pathogens we find in meat, fish, milk and eggs.”
There is a prominent health halo surrounding plant-based options, meaning the public’s perception of them is skewed because they are free from animal products. This mentality can also transfer to food workers, making them complacent when handling food and educating customers. In reality, these products deserve as rigorous testing as any other.
The High Cost of Contamination
Outbreaks from contaminated foods can ruin a brand’s reputation. People associate them with dangerous products and stop buying from them altogether. Plant-based companies cannot afford this hit to their market standing, especially when animal products already out compete vegetarian and vegan options. Plant-based makers are contending with their niche and also battling against the meat industry.
Complex Processing Increases Risk
Cast-iron skillet with soy plant-based sausage by Like Sausage
Every food item has multiple processing steps, but plant-based alternatives could have even more. Every transition is an opportunity to invite contamination or a quality concern. This includes non-food items, such as metal or glass, entering the mix. It has made traceability a higher priority for food manufacturers, and plant-based operations must follow suit to preserve the nutritional and monetary value of their output.
Following compliance frameworks like ISO 22000 on food safety management is one of the best ways to know the industry’s top recommendations for supply chain oversight. ISO regularly updates its standards to accommodate the modern needs of the industry. For example, many plant-based foods contain fibrous elements, catching in processing equipment and making them harder to maintain. These difficulties could create more problems, but they are fixable with monitoring and robust management guidelines.
The Peril of Temperature Miscalculation
Temperature is one of the most critical factors in plant-based food safety. Manufacturers can see this in products that have been sold for years, such as pre-cut fruit cups. Researchers have observed fruit cocktails in various temperatures to see how it impacts the likelihood of Listeria. Temperatures of 8° Celsius or more were dangerous, while temperatures of 4° to 5° Celsius slowed down growth.
Animal products are vulnerable to temperature changes, but plants can be even more so. Manufacturers of meat replacements or milk alternatives, for example, need to use these prior case studies to inform their temperature management. Although plant-based products undergo processing and may contain additives to alter their properties, maintaining temperature resilience requires ongoing supervision.
The Allergen Minefield
Safety concerns extend beyond preventing the spread of illness. Competitive advantage requires plant-based foods to appeal to everyone, regardless of dietary restrictions or health conditions.
Unfortunately, many meat alternatives contain common allergens, like nuts and soy. One of the most common and dense plant protein products, seitan, is made from wheat, preventing those with Celiac disease from consuming it. If companies want to expand their market appeal, they have to prevent cross-contamination and introduce safe options for all consumers.
This means clearly labeling anything that is potentially exposed to these allergens. Stickers and safety information should be prominently displayed and easily accessible. Additionally, third-party allergen testing is vital for market competitiveness. This increases customer confidence.
Building a Brand on Trust
A latte made with Oatly branded oat milk
Ultimately, safety in plant-based food manufacturing is crucial because it enhances the brand’s visibility and desirability, making it more appealing to support. If the public associates vegetarian and vegan alternatives with health crises and recalls, manufacturers will fail to provide buyers with sustainable and diverse food options.
Regulatory changes and health issues in the meat industry could introduce more risks to those in the U.S. who eat poultry and pork. Officials are suggesting that these changes in safety will make it more dangerous to consume meat. As quality and safety become less mandated, fewer people may support the sector due to fear.
The plant-based industry cannot afford to fall into these traps to increase revenue. Reinforcing strict protocols will lead to greater business longevity rather than short-term profit gains from faster processing.
Plant-Based Food Safety Essentials for Market Friendliness
If plant-based foods are to compete with animal products and maintain market relevance, they must prioritize safety. This can enhance the workforce’s well-being while demonstrating respect for the public that supports them. Stakeholders must set this precedent early to influence the market’s future.
Ideagen’s CEO explains why binary outcomes and high stakes make compliance ideal for autonomous AI
Food and Beverage businesses will transform their operations with agentic AI* – but won’t realize its full potential until AI earns humanity’s trust, according to Ben Dorks, CEO of Ideagen. Dorks said the sector’s compliance obligation is the one domain where autonomous AI will thrive – despite leading analysts warning 40% will fail in the next two years.
Speaking at the launch of their own agentic AI platform Ideagen Mazlan, Dorks, said: “Autonomous AI will succeed in compliance because failure is measurable, stakes are high and outcomes are binary.
“AI that continuously monitors jurisdictional or industry specific compliance frameworks, detects patterns across thousands of records, raises actions for others to follow, flags gaps before audits, autonomously? That’s agentic. It will literally save lives and is the most transformative shift in protecting people, products and processes we have ever seen.
“We could have gone further, but the world isn’t ready for that yet, agentic AI still needs to earn humanity’s trust before we give it full control. But what it can do is to keep workplaces safe, reduce product recalls, keep supply chains moving, prevent harmful contaminants entering food”
Initial piloting has demonstrated significant acceleration in adoption and benefit, in some cases squeezing 30 minute-tasks down to just two minutes. Other estimates show that enterprise level implementation that could take a company six to nine months, could be achieved in around 30 days.
“In the new year, we’ll be adding things like a voice interface so workers on the frontline, who might be in heavy PPE, can just tell Mazlan what’s happened,” said Dorks.
“And it’s intuitive, people won’t need to be trained to use it. If we can break down barriers to the adoption of digital solutions, then businesses are operating with better data which in turn results in the safer products and processes and a better return on that investment.”
Dorks was also quick to stress that Ideagen Mazlan is not a bolt-on solution to increase productivity: “It’s intelligence, built in. Most ‘agentic AI’ isn’t agentic at all – it’s assistive AI with better marketing! AI that accurately answers questions when you ask them? That’s a chatbot.
“Our agentic AI works on three simple principles: it’s built into Ideagen solutions, it understands your specific industry context and appears naturally throughout your workflows.
“It knows OSHA, ISO and the legislation in your jurisdiction, it knows your own policies and data then uses this to analyze incidents, identifying risks, automating compliance tasks.
“But crucially, like autopilot technology on planes, we’ve built it to ensure that the power still sits with the human. Final oversight and approval remains with the quality managers and health and safety teams, but Mazlan is autonomously doing the heavy lifting.”
* Editors Note: Agentic AI refers to advanced AI systems that operate autonomously, setting goals, planning, and executing complex, multi-step tasks with minimal human intervention, going beyond simple command-response or content generation to proactively solve problems and adapt to dynamic environments by using tools and collaborating with other agents. These systems are goal-oriented, adaptable, and capable of independent decision-making, enabling them to handle intricate workflows in fields like finance, healthcare, and logistics, turning AI from a tool into an initiative-taking partner.
Food adulteration can be either intentional or incidental, such as heavy metal contamination, pesticide residue, or packaging-related issues. When this adulteration is deliberately carried out by addition, omission, or substitution for economic gain, it is known as economically motivated adulteration (EMA), a subset of food fraud. The motivation for both EMA and food fraud is primarily financial gain. However, food fraud extends beyond EMA to other deceptive practices such as misbranding, counterfeiting, and diversion.
In late 2023, cinnamon apple puree and apple sauce products sourced from Ecuador were recalled after testing positive for elevated levels of lead and chromium1. The FDA’s leading hypothesis was that the incident was likely due to EMA, and the contamination went undetected until it escalated into a serious public health issue. This highlights the importance of implementing robust traceability systems and conducting food authentication tests to ensure that only genuine products reach the consumer market, in compliance with all relevant food safety and quality standards.
Spectroscopy Simplified
Spectroscopic techniques such as UV-Vis Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Near-Infrared Spectroscopy (NIR), Raman Spectroscopy, and Nuclear Magnetic Resonance (NMR) Spectroscopy, when combined with chemometrics, are among the most reliable methods in verifying food authenticity. UV-Vis Spectroscopy is widely utilized in most analytical laboratories for analyzing chromophore-containing compounds, such as pigments. In the food manufacturing sector, it can be used to detect dilution of alcoholic and non-alcoholic beverages, such as juices and wines. However, it provides limited structural information, an area where FTIR performs comparatively well.
FTIR, in contrast, is ideal for routine screening in food authentication. It can be used to detect adulteration in olive oils with cheaper oils such as sunflower, palm, or soybean oils, and the addition of sugar syrup to honey2. The portability of Raman and NIR is advantageous for non-destructive on-site testing. While they can provide rapid profiling, they are typically less sensitive than FTIR for trace analysis and are most beneficial when used complementarily in a laboratory setting. Since Raman relies on light scattering, it can overcome certain challenges FTIR faces in analyzing high-moisture foods, like milk. Such foods strongly absorb infrared, which can interfere with and weaken signals, impacting detection accuracy.
Large organizations with dedicated R&D laboratories may benefit from setting up an in-house FTIR. If small and mid-size organizations were to adopt product authenticity testing as a standard practice with high testing volumes, having an in-house FTIR could turn out to be an economical choice over time. For operations with low testing frequency, outsourcing could be more cost-efficient. Finally, while NMR delivers detailed information, it is time-consuming and requires expensive equipment as well as expert handling, making it better suited for confirmatory analyses. In such cases, it is practical to use specialized third-party labs, as operating costs can outweigh the benefits.
Chromatography in Action
Chromatographic separation techniques such as Gas Chromatography (GC) and High-Performance Liquid Chromatography (HPLC) are often coupled with Mass Spectrometry (MS) for detecting trace levels of adulterants in intricate food matrices that cannot typically be detected by spectroscopic methods alone. Both GC-MS and LC-MS are powerful and selective techniques, but they come with significantly higher purchasing and operating costs than FTIR. Their preference can be driven by the need for advanced research or for regulatory compliance purposes, in addition to authentication testing.
GC-MS is ideal for volatile compounds that can withstand high temperatures and can be used for identifying synthetic flavor compounds in natural flavors and juices. Flavorings and non-alcoholic beverages are among the top 10 implicated categories of food fraud, and olive oils have been frequently associated with mislabeling incidents3. In contrast, LC-MS is better suited for non-volatile, thermally sensitive, and high-molecular weight compounds. Common applications of LC-MS include detecting melamine in milk and identifying Sudan dyes in chili powder.
To prevent fraud, testing is most effective when done at the ingredient level, and raw material suppliers should be encouraged to engage in such practices. This offers multi-ingredient food manufacturers a greater reliance on their suppliers for authenticity and, depending on the scope of their operation, may reduce the need for additional testing of incoming materials.
Decoding Mass Spectrometry
MS techniques such as Isotope Ratio Mass Spectrometry (IRMS) and Inductively Coupled-Plasma Mass Spectrometry (ICP-MS) have distinct applications. IRMS measures stable isotope ratios, whose abundance varies with environmental and agricultural factors, serving as a strong indicator of growing conditions and geographical origin. With IRMS, it is possible to ascertain whether a conventional product is mislabeled as organic or if meat has been derived from a grass-fed or grain-fed cow4. While spectroscopic methods can cover a broader spectrum in provenance mapping, IRMS is more focused and definitive in such an approximation.
Likewise, ICP-MS analyzes the elemental composition of heavy metals and trace minerals. It is often used to detect heavy metal contamination, such as arsenic in rice or lead in water, and to estimate mineral content in supplements. Since both IRMS and ICP-MS are high-precision instruments that involve considerable capital investments, internal implementation is justified for regulatory agencies where accuracy is key. For private organizations, the choice ultimately depends on their requirements, infrastructure, and budget thresholds.
Cracking the Molecular Code
Molecular techniques such as Conventional PCR and Real-time Polymerase Chain Reaction (qPCR) are popular choices for species identification due to their speed, precision, and reliance on genetic information, which is not influenced by farming conditions. Both methods detect and amplify DNA, but only qPCR can quantify genetic material in real-time by using fluorescent probes. This offers qPCR a functional advantage over conventional PCR.
Historically, meat and dairy products have been frequently implicated in food fraud incidents3. For example, conventional PCR can detect whether beef is adulterated with pork, whereas qPCR can determine the amount of pork meat present. An alarming case of fraud occurred in 2013 when horsemeat ended up in the supply chain across Europe, labeled as beef. Similarly, qPCR can distinguish whether goat milk has been diluted with cow milk, as well as the extent of dilution.
Another type of PCR, known as multiplex PCR, allows simultaneous detection of multiple species in a single assay, which can save time and expenses, but the overall process can be complex to implement. While PCR instruments are essential for biotechnological research in pharmaceutical companies and are often favored by regulatory agencies, their routine use in food manufacturing establishments might be limited unless the company participates in applied research, such as the development of bioengineered foods.
Relative cost analysis of standard analytical technologies, categorized from 1 (very low) to 6 (extremely high) based on approximate market pricing. The variations between entry-level equipment and advanced models have been accounted for in the design (Credit: B. Ghosh)
The Analytical Dilemma
The bar graph in Figure 1 demonstrates a clear trend between the equipment cost and the depth of the analysis achieved. In summary, the more comprehensive the analysis, the higher the cost of the equipment, and the greater the technical expertise required. Food manufacturers can use these observations to determine the approach best suited to their scope and budget. UV-Vis Spectroscopy requires basic operation skills and is relatively easy to handle. Given their low cost, they can be easily integrated into an existing internal lab infrastructure.
Now, the choice between FTIR and Raman can be challenging as both techniques have distinct strengths and complement each other. FTIR excels at analyzing a broad range of food matrices, while Raman offers a convenient application for field use. Among the mid-range category, qPCR requires careful handling during sample preparation to prevent false positives, and companies can evaluate outsourcing testing to accredited labs, collaborate with research institutions, or appoint trained specialists.
GC-MS, LC-MS, and ICP-MS tend to have considerable costs, making them ideal for confirmatory analyses. Whether they are used regularly or customarily, operational needs and budget thresholds are ultimately the deciding factors for an in-house infrastructure development. IRMS and NMR are superior and highly advanced instruments that are employed for specialized research rather than routine food authentication testing. When required, they can be selectively utilized through third-party labs.
From Insight to Action
Food authentication technologies like spectroscopy, chromatography, mass spectrometry, and PCR play a key role in ensuring the integrity of food products. While each technique comes with a cost and capability trade-off, strategically leveraging them within the existing safety and quality framework offers an additional layer of protection from food fraud. Figure 2 summarizes essential practices organizations should adopt and avoid to strengthen food fraud prevention and mitigation efforts.
Recommended practices for food fraud prevention (Credit: B. Ghosh)
Raw material suppliers must actively engage in product authenticity testing. Multi-ingredient or finished product manufacturers can adopt the following best practices depending on the nature of their supplier relationships.
New suppliers – Request or conduct authenticity testing before initial bulk purchase.
Domestic and/or established relationship with suppliers – Perform random raw material sampling on a rotating basis for authenticity testing.
International suppliers and/or complex supply chains – Conduct authenticity testing at least annually.
Food fraud can quickly evolve into a food safety or a food quality issue. Investing in the right authentication tools today can prevent costly recalls tomorrow. In addition to testing, it is essential to stay informed and monitor emerging trends in the rapidly evolving supply chain landscape. Building a safer global food system requires prioritizing prevention over reaction by proactively detecting and eliminating food fraud risks before they occur.
Mendes, E., & Duarte, N. (2021). Mid-infrared spectroscopy as a valuable tool to tackle food analysis: A literature review on coffee, dairies, honey, olive oil and wine. Foods, 10(2), 477. https://doi.org/10.3390/foods10020477
Everstine, K. D., Chin, H. B., Lopes, F. A., & Moore, J. C. (2024). Database of food fraud records: Summary of data from 1980 to 2022. Journal of food protection, 87(3), 100227. https://doi.org/10.1016/j.jfp.2024.100227
Hong, E., Lee, S. Y., Jeong, J. Y., Park, J. M., Kim, B. H., Kwon, K., & Chun, H. S. (2017). Modern analytical methods for the detection of food fraud and adulteration by food category. Journal of the Science of Food and Agriculture, 97(12), 3877-3896. https://doi.org/10.1002/jsfa.8364
Vinothkanna, A., Dar, O. I., Liu, Z., & Jia, A. Q. (2024). Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents. Food Chemistry, 446, 138893. https://doi.org/10.1016/j.foodchem.2024.138893
The holidays are just around the corner, and as people start planning their holiday menus, food processors have been gearing up for their busiest season. The holiday season is also a busy time for pests. As they begin their search for warmth, it’s important to be aware of their activity and help prevent your food processing facility from becoming the next holiday home for the pests this year.
According to the USDA, almost 10% of food produced in the United States is contaminated by stored product pests each year. With the overwhelming size of food processing facilities, it can be difficult to stay on top of all entry points and breeding grounds that pests take over. However, the consequences of an infestation go far beyond just damaged goods. The lack of pest care can compromise food safety, cause expensive recalls, and break customer trust. Because of this, it’s important to know which pests could be in your facilities and identify the best plan of action to remove them.
What Are the Most Common Stored Product Pests?
Food processing facilities are susceptible to a wide variety of pests, but there are several species in particular that can be problematic due to the specific foods they target:
Warehouse Beetles: Drawn to flour, feed, dried milk, and other stored grains, one of the most common signs of a warehouse beetle is the presence of their shed skin. They are not harmful to humans, but they have the ability to destroy dried pantry items, which can lead to costly damages.
Red Flour Beetle: These pests prefer flour, meal, and dirty grain bins. Female Red Flour Beetles lay up to 450 eggs that become full grown in as little as one month. Their dead bodies and shed skin cause a pungent odor in grains, affecting the quality and ability to sell to customers.
Angoumois Grain Moths: Cooler temperatures make these pests more active, causing their larvae to thrive and develop in corn and wheat kernels. They can be difficult to see to the human eye, so it is important to watch out for warning signs and get it taken care of quickly.
Indian Meal Moths: These moths are among the most common pests in stored grains in the U.S. They are attracted to flour, crackers, and nuts, and an infestation can change the taste of the products they are feasting on.
Psocids: These tiny pests, which are similar to lice, enjoy taking over grains, oats, cereals, and dried fruits. They are a magnet to moisture, so it is important to protect against any damp or humid conditions.
How Do You Avoid Pests in Food Processing Facilities?
Despite the threats that these pests pose to businesses, proactive prevention measures can greatly lessen the risk of infestation. An Integrated Pest Management (IPM) plan combines proper cleanliness, thorough inspections, and employee awareness to help ensure that your facility is prepared to prevent pests. For example:
Ensure products are stored properly: Make sure inventory does not sit in the same place for too long and choose containers that can be tightly sealed. Keep them in cool conditions and off the ground for proper cleaning. And always use the “first in, first out” method.
Locate and seal all potential entry points: Open doorways and windows create easy access for pests to enter your facility. It is important to remind employees to keep all doorways shut, and to inspect and seal any potential pest entry points such as windows, door frames, and more.
Train employees to identify signs of pest activity: Your employees are often the first to notice pest activity. Train them to recognize gnaw marks, pellets, and nests. Then, provide them with a step-by-step plan of action so the issue can be addressed quickly and effectively.
Check for hot spots: As mentioned earlier, the cold weather causes pests to seek warm shelter. It’s vital to check behind, below, and around all equipment, storage areas, shelves, and vents.
The busyness of the holiday season often causes food processing facilities to operate at full capacity, leaving little to no time for maintenance. However, taking precautions now can help avoid bigger disruptions later.
The most effective food processing facilities treat pest management as a continuous operating procedure. Creating an environment of strong communication between employees and service providers allows businesses to help exceed their production goals safely and cleanly. As your demand increases this holiday season, it’s crucial to be smart about protecting your facility and the integrity of your brand.
Food manufacturers have a significant responsibility to maintain quality and prevent foodborne illnesses. Eliminating unnecessary waste creation requires precision, compliance adherence and technology to assist the workforce. Some entities are experimenting with ways robotics can enhance conditions for better sanitation and employee well-being. Automated food manufacturing safety may yield numerous advantages and equal drawbacks, so how can stakeholders achieve balance?
The Highlights of Automated Food Manufacturing Safety
Automation technologies can include robots, artificial intelligence (AI), the Internet of Things (IoT) and more. Programming them to run on autopilot with data-driven decision-making could make food cleaner and remove staff from dangerous environments.
Enhanced Traceability for Faster Recalls
Food recalls plaster news headlines, minimizing food accessibility and spreading illness to citizens. Automated food manufacturing safety systems implement greater oversight to discourage these scenarios. AI, sensors and more collect information about every item that goes through processing.
Everything has a digital trail, and technology can catalog its critical metrics, including its grade and presence of harmful bacteria. It directly supports frameworks like the Global Food Safety Initiative, which encourages traceability. Manufacturers can identify problematic food sources and issue recalls in minutes, compared to lengthy manual intervention.
Reduced Human Error and Contamination
Humans have the potential to introduce more contaminants into the workplace than robots. Staff may compromise the product without knowing, whereas computer vision-empowered cameras and automated ultraviolet sanitation lights could process items without the possibility. Even if employees are trained in hygiene and sanitation, accidents occur.
Automation helps employees better adhere to Good Manufacturing Practices (GMP) and Hazard Analysis and Critical Control Points (HACCP) frameworks. Both guidelines stress the importance of preventing biological and chemical hazards, which automation machinery does not introduce as often as humans.
Continuous Monitoring of Critical Control Points
Lowering the risk of contamination is beneficial for multiple reasons, in addition to reinforcing the bottom line. Better food hygiene practices help organizations avoid costly legal repercussions like lawsuits and fines if they endanger the public. Automation bolsters companies by providing constant surveillance over food products, evaluating their quality before they ship to grocers.
Sensors and other tools can check critical parameters like temperature and humidity to ensure food safety in all parts of the process. Automation controls can change environmental conditions based on these ideal metrics, making sure food remains in the best environment for it to stay fresh and clean. This eliminates the need for workers to adjust thermometers constantly, as automation can trigger alerts and institute changes 24/7.
The Reality of Robot-First Workspaces
Several prominent concerns plague the discourse on automation, despite its potential to prevent foodborne illness and enhance staff workflows. The arguments have validity, though they diminish the advantages robots could deliver to food safety. Some include:
Job displacement: Automation is more effective at replicating tedious, repetitive tasks like inspections and sorting. The U.S. estimates 100 million jobs will be affected by AI and automation.
High initial investment: Even if safety is a priority, purchasing compliant, high-performing technology and software could exclude small- and medium-sized businesses from having better safety standards compared to megacorporations with more capital.
Minimal adaptability: Workers can program robots, but they have operational limitations. Humans are more flexible and responsive to changing conditions, whereas reprogramming automation tools could be unnecessarily time-consuming.
While these realities exist, workers could reimagine their roles by learning how to maintain and work alongside robotic systems. Retraining could reinvigorate an employee’s loyalty to their employer while establishing a safety-focused culture. Additionally, it will empower them to work alongside automation because it highlights their strengths.
The Pathway to Balance
Stakeholders can adopt robotics and automation to supplement the workforce, but doing so requires phased implementation to encourage buy-in. Assuring staff that their jobs are not in jeopardy is essential for establishing a culture of productive human-robot collaboration.
Installing them as a complement to their efforts rather than a replacement is vital for inspiring the critical thinking and adaptability that are unique to the workforce. These traits must empower automation tools to work to their fullest potential. Then, it will lead workers to trust automated equipment, enhancing their workflows.
Technicians can delegate them to handle the majority of contamination detection and sorting, leaving teams to review their work and reprogram them as issues arise. The improved accuracy and detection skills — even in high-speed random-batch environments — enable them to upskill and increase digital literacy for more productive collaborations. Automation removes people from unsafe conditions while providing opportunities for more engaging tasks throughout their days.
The Recipe for Blending Human Talent With Automated Precision
Food manufacturers can leverage automation to enhance safety compliance and quality control, although pros and cons exist regarding the use of robots and employees. Striking a balance to promote productive human-robot interactivity is possible while reducing food waste and the chance of recalls and illness. Managers determine the success of these working relationships by deploying machines based on their strengths and depending on the workforce to amplify their skills.
Food Safety Tech asked Fabiola Negrón what shifts are dominating the training landscape. And “why now” for a new product, SkillUp, from Registrar Corp.
We see tariffs affecting just about everything — does this reach to food safety and food safety training specifically?
Absolutely. Ingredient quality is of course a concern as a result of supply chain disruptions. But in terms of food safety training and workforce ability to follow food safety protocols, it’s all about efficiency. As ingredients, packaging materials, equipment, and shipping expenses rise due to tariffs, food manufacturers are forced to find savings elsewhere. But food safety is not something that can be skimped on. The focus then is on how to be more efficient.
eLearning has become more and more essential in our industry. This is nothing new of course, as eLearning has been around for decades, a testament to its effectiveness when done well. It’s more about streamlining. Every once in a while, a forced re-evaluation can be a good thing. We’re finding ways to save time by eliminating some bells and whistles from bloated platforms, saving admin and facilitator time with more eLearning, as well as less time away from production.
It can be difficult to get a true sense of the cost inherent in building and maintaining a training program, not to mention the outcomes. We developed a cost calculator to try and help with this, which anyone can use. It pulls from multiple databases of industry and workforce data to provide a clear picture in just a minute or two, or you could spend a few more minutes inputting your own data points.
You mentioned “when done well.” What makes a good eLearning program?
The three biggest factors are relevance, duration, and interactivity. Starting with relevance, because presenting a learner with something that doesn’t apply to them is the surest way to have them tune out or go through the motions. This means both the topic should apply to their job role, and the content should reflect their work conditions.
As for duration, the shorter the better is always true — but, again, without skimping on content and quality. This is especially true for the foundational topics like personal hygiene, cross contact, cross contamination, and so on. As career professionals, we could talk for days on one topic alone. But for a new production worker, overly complicated analysis is not going to help them keep your facility safe. Instead, it is critical to distill the curriculum into the most effective way to ensure they comprehend what they’re learning, can recall the info, and can put it into practice. A 10-minute eLearning course will almost always be sufficient to cover the fundamentals on one topic. Ensure your team members have this nailed down perfectly before introducing more complex elements.
Interactivity is just as important. This ensures trainees do things as part of the course, which is a far better way to learn than receiving information passively. This can mean drag-and-drop exercises, role-playing scenario questions, and quizzes. The key is to keep learners engaged by doing, not just listening.
What is the biggest change in how food manufacturers can execute on your advice?
It would be impossible to answer this question without talking about AI, so let’s start there. Modern training platforms should have AI course creation built in. This is extremely helpful for things that go beyond the core principles. You can enter a source document or provide a short description, and an AI course creator will do the rest. First providing an outline for you to review, then creating an actual script, even adding spot-on quizzes and knowledge checks.
You can get a glimpse of how this works on our AI Create webpage.
A must- must- must-do, of course, is to review and correct any errors or omissions. AI can save you countless hours of time, but it’s not 100% automatic. There will be mistakes that you, as the true subject matter expert, will need to correct or clarify.
But, let’s take a step back. It’s hard to think of AI utilization as overcomplicating things given its tremendous efficiency in course development. But sometimes even this is time better spent. Going back to my earlier comment on keeping things simple for workforce training, particularly when it comes to core food safety fundamentals. Food manufacturers have access to pre-built eLearning course libraries that cover these food safety training must-haves very well.
A winning formula is to use the library from a reliable training partner to cover the fundamental principles. And leverage AI for the deeper dives or unique aspects of your facility. By utilizing a pre-built library, you don’t need to reinvent the wheel for a few dozen core principles that are universal and unwavering. For example, Cleaning and Sanitizing is a topic that should be covered in any training library. Your vendor’s course will cover the basic principles, include interactive exercises to cement understanding, and have quizzes to document comprehension. Then, you may have unique aspects particular to your facility that the sanitation department must follow. With the foundation provided, you can use AI to make an eLearning course on your unique processes.
SkillUp is a new example of a training vendor as you described. Why did Registrar Corp develop this new offering now, after nearly 25 years leading the food safety compliance space?
To fill a noticeable gap in the industry. The existing training vendors were not meeting the needs of many small food manufacturers. Not every company has thousands of employees. Many companies need a solution with lighter implementation, easier management, and — perhaps most importantly — a more affordable option.
Registrar Corp provides a wide range of food safety compliance services. And we have been providing professional eLearning for advanced food safety principles, like PCQI training, HACCP certification, FSVP training, and more. So, we recognized the gap in frontline worker training for small- to medium-sized facilities. Several of our leaders who developed SkillUp have decades of experience in the food safety training space. I believe they just recognized the gap and were well positioned to provide a solution to fill it.
If your readers are interested in learning more about it, they can visit the SkillUp web page, or feel free to reach out to me on LinkedIn.
Food and beverage facilities have some of the strictest compliance protocols for cleanliness to preserve quality and integrity. This care prevents foodborne illness from spreading and products from going into landfills because of rotting or other issues. Organizations are experimenting with automation and food processing robotics to handle cleaning tasks. Is it more efficient, and does it uphold safety standards?
How Robots Clean Food Processing Facilities
The variety of available cleaning robots and tools is expansive. Whether they are as capable as humans in maintaining hygiene protocols is still being researched. However, existing case studies prove they could be invaluable assets for preventing cross-contamination, freeing up labor resources and enhancing the cleanliness of food facilities.
Robots could mop floors and spray disinfectant or execute tasks that often lead to human error or microbial contamination, such as kneading dough or washing produce. Picking and placing delicate foods is another chance to eliminate harmful influences, especially with sensitive products like meat that can more easily spread illness.
The versatility of robotics highlights how many cleanliness improvements can happen in industrial settings, as generalized janitorial tasks are not the only maintenance method. Production lines, packing equipment, and transportation tools can all employ robots that use smart materials and technological enhancements to prevent compliance concerns and detect issues early.
What Technologies Promote Hygienic Facilities?
Food quality control systems like the Good Manufacturing Practices and ISO 22000 are only a couple of examples of frameworks that demand tight quality control for production and packaging. These are the most crucial technologies enabling compliance adherence for the future.
Automated Sanitation Systems
Precision robotics and cobots can come equipped with peripherals like spray nozzles to expand cleaning and sanitation potential. They can extend their arms to hard-to-reach locations, scrubbing surfaces that were rarely touched before. Experts can program the equipment to run on a schedule, disinfecting surfaces on the most optimal timetable based on common contaminants and compliance expectations.
Ultraviolet-C (UVC) Disinfection Robots
UVC is a common component of industrial cleaning systems, but disinfection robotics can emit these wavelengths to disinfect vulnerable surfaces and tools on a consistent timer. They are even being used in agriculture to handle common pests and growths like mites and mildew. The light stops harmful DNA from replicating, making it easier to control rapidly spreading bacteria.
Deep Cleaning Robots
Deep cleaning robots have been around for decades, but they are becoming more proficient. Options like automated floor scrubbers and biofilm removers could be some of the most helpful in food operations. They remove time-consuming tasks from humans, opening their schedules for more attentive quality control measures.
To maximize the value of deep cleaning robots, manufacturers should consider the plant’s layout. Space optimization and establishment of production zones are crucial for determining the best machines to handle certain areas. Some facilities have adaptable equipment, allowing the floor plan to change depending on production needs. Robotics needs to be equally flexible, adapting to new workflows without instigating bottlenecks or safety concerns. Doing so enables decision-makers to lower labor costs and increase productivity.
Compliance and Traceability
Some robots do not have to clean to assist in hygienic compliance. Engineers can program sensor-based technologies with regulatory parameters to detect when issues arise. This encourages continuous monitoring while creating a data trail for upcoming audits. Internally, stakeholders can use this data to establish new quality assurance metrics and mitigate the company’s most persistent issues.
Real-Time Monitoring and Reporting
The reports observational robotics generates are crucial for automating compliance reporting, too. If a robot is unavailable to do certain cleaning tasks, workers will need to mend the gaps.
They can oversee data clarity from monitoring tools and use it to inform training programs, making staff-driven cleaning efforts more productive. This minimizes uncertainty about the most significant contamination sources while asserting a culture of proactive cleaning intervention.
Soft Robotics
Hygienic designs and materials are essential for making automation a staple of food processing robotics. Soft machinery made from silicone offers a flexible and hygienic option compared to traditional equipment. They prevent corrosion and are suboptimal breeding grounds for many bacteria.
These machines are better equipped to grip and transport vulnerable foods like fruits that are prone to bruising, cutting human contamination out of the production line. However, they only work in conjunction with automated robots that clean the workstations. The additional oversight is necessary, especially when staff are unable to clean the food-handling machinery themselves.
Food Processing Robotics and Automated Hygiene
Robots are assuming the responsibilities that few team members want to. Sanitation and cleanliness are vital for maintaining compliance and preserving quality, and robots are proving to be crucial components of hygiene and safety plans moving forward. Innovative facilities will experiment with these resources to empower employees, improve safety and create better products, promoting a healthy working relationship between humans and robotics.
The European Union’s Deforestation-free Regulation (EUDR) requires companies producing, importing or exporting select commodities to prove their goods did not originate from deforested land or contribute to forest degradation. EUDR compliance changes how food manufacturers’ supply chains operate.
Industry professionals should view this regulation as a business opportunity, not a burden. With the right tools, they can expand their target demographic, strengthen brand reputation and increase customer retention.
What Companies Should Know About the EUDR
The EUDR technically became legally binding in June 2023, targeting popular commodities like palm oil, cocoa, wood, soy, rubber, cattle and coffee. However, the E.U. allowed a 12-month phase-in period in December 2024, giving medium and large companies 12 months to comply. Micro and small enterprises (MSEs) have until June 2026.
While these dates are fast-approaching, businesses have more than enough time to implement the necessary interventions. They should start with the fundamentals.
Why the Coffee Supply Chain Is in the Spotlight
Coffee is not just a commodity or a morning pick-me-up but a global sensation. For some, it is a lifestyle. They spend hours and thousands of dollars to pull a perfect espresso shot. In the United States, the arrival of fall is synonymous with “pumpkin spice season,” a commercialized cultural phenomenon dedicated to seasonal lattes.
In 2025 alone, the global at-home and out-of-home coffee markets generated over $485.59 billion in revenue. This popularity is not without its costs — this acclaimed crop has a history of environmental concerns.
The EUDR spotlit this sector’s supply chain because it contributes to deforestation. In Central America alone, growers have cleared more than 2.5 million acres to establish sun-grown coffee farms, which have higher yields than the traditional farms using tree canopy shade. Farmers clear-cut forests to make room for coffee trees.
How It Adds to Coffee Supply Chain Challenges
One of the top coffee supply chain challenges is fragmentation. Communication is challenging because many smallholder farmers — who grow 60% of the world’s coffee — lack access to modern technologies.
Even if farmers have messaging apps and email addresses, they may be unable to produce geolocation data, satellite imagery or detailed descriptions of forest degradation. Field audits are a possible alternative, but traveling from the E.U. to an equatorial country is expensive, especially since the EUDR mandates annual reviews.
What It Takes to Become Compliant With the EUDR
The cut-off date for deforestation was December 31, 2020. If locals cleared a forested area for agricultural use after this date, the EUDR prohibits goods sourced there from being traded on the E.U. market.
Businesses must establish and maintain a due diligence system to ensure EUDR compliance. MSEs and lone entrepreneurs must publicly report their steps to fulfill their obligations at least once a year. The due diligence statement template is the same regardless of commodity type or industry. It includes details like contact information, harmonized system code, country of production and geolocation data.
Reviewing Little-Known Compliance Considerations
Due to complex legal jargon, laypeople may not realize compliance extends beyond ensuring goods are deforestation-free. Several sections stand out in particular.
Packaging and Packing Material
While EUDR compliance does not extend to packaging that supports, protects or carries products — as long as it is not made available on the market in its own right — the European Commission reserves the right to review and update the regulation. One day, packaging and packing material may be subject to deforestation-free standards.
Eliminating unnecessary intermediaries may help streamline the process by reducing administrative overhead and preventing circumvention risks. Take nitrogen, for example, which increases food shelf life by slowing oxidation. It protects the rich oils and aromas that are tokens of freshly roasted coffee’s popularity, safeguarding taste and freshness. Preserving food this way requires specific flow rates and purity levels. An on-site generator introduces far fewer compliance obligations than a third-party supplier.
Local Laws
Growers often work long, tiring hours to cultivate and harvest their yields. Ripening windows are usually inconsistent, so they must pick coffee cherries individually by hand. Despite being fundamental to the supply chain, many receive little to no compensation.
Many industry professionals do their best to properly compensate their growers, suppliers and vendors. Since the EUDR mandates manufacturers to produce goods according to the country of production’s local laws, this practice is now mandatory. This includes abiding by land tenure laws and human rights standards.
Simplified Due Diligence
Those sourcing from low-risk countries benefit from simplified due diligence obligations. They do not have to assess or mitigate risks unless someone informs them of substantiated concerns indicating noncompliance. However, they must still evaluate supply chain complexity to determine circumvention risks.
As of 2025, the E.U. has placed countries of origin like Brazil, Colombia, Indonesia and Honduras in the standard risk category, meaning this simplified obligation is largely unavailable for food manufacturers in the coffee industry.
Digital Tools Transforming EUDR Compliance
Traders need their farm’s exact location. They can use coordinates or a two-dimensional polygon. Apps like TerraTrac allow for basic traceability. Publicly available maps like those from the Rainforest Alliance can also guide decision-making. Medium and large enterprises may prefer a platform that integrates with their enterprise resource planning software.
Traditionally, detecting deforestation as it happens is difficult. However, modern technologies make it straightforward. Global Positioning System mapping and geospatial tools provide more than coordinates. Professionals can layer descriptive attributes on top of a real-world location, mapping events, risks or objects to guide informed decision-making.
The blockchain provides a decentralized, immutable platform for tracking such data points. Business owners can seamlessly coordinate with everyone from growers to roasters. Since no one can edit or delete a block without every participant’s permission, tampering and fraud are practically impossible.
Artificial intelligence is another cutting-edge tool that can help streamline communication and decrease administrative workloads. It can translate messages, conduct risk analyses or automate reporting.
How the Right Tools Create Business Opportunities
Facing coffee supply chain challenges like fragmentation or insufficient digitalization does not have to be intimidating. With the right tools, it can even feel exciting. Comprehensive visibility enables brands to capitalize on consumers’ increasing sustainability awareness. They can provide QR codes with tracking data or personalize labels based on the product’s origin.
People will perceive these details as value-added features, incentivizing them to purchase. Early adopters can target sustainability-minded demographics, helping them strengthen brand reputation and unlock new market opportunities.
Even people who do not feel strongly about green or climate-friendly products will appreciate being able to verify their product’s origin and authenticity. Data is a moneymaker. It could enable companies to charge a premium for ethical, traceable goods — even if they do not change their formula or suppliers.
Brands Can Use EUDR Compliance to Their Advantage
Ensuring EUDR compliance will take time, but investing in the right digital tools — some of which are free — will streamline the process and create business opportunities. Those who change now could corner the market, ensuring success despite major regulatory changes.
There is a heightened post-process contamination risk for canned goods, especially after sterilization, when mismanagement, equipment breakdowns and flawed packaging compromise product integrity by introducing pathogens and foreign materials. The most minor sanitation defects can cause food spoilage, foodborne illnesses and significant recall liability.
Canned goods manufacturers must uphold stringent protocols to comply with regulatory requirements and preserve consumer safety and trust. With more diverse inventory and packaging designs on the horizon, integrating automated vision systems is critical to ensure consistent quality.
What Are Automated Vision Systems?
Automated vision systems use high-resolution cameras, sensor technology and artificial intelligence (AI) to monitor and assess products in real time. Traditionally, post-process contamination inspections relied on fatigued human operators, which resulted in inconsistencies and errors.
Also known as machine vision, these systems perform product analyses for long hours at a low expenditure. They deliver outcomes rapidly, detecting nuanced defects and contaminants that the human eye might miss, guaranteeing maximum efficiency and accuracy. Their adaptability is ideal for handling various container and packaging line formats.
Key Drivers for Adoption in the Food Industry
The Food Safety Modernization Act (FSMA) and critical Food and Drug Administration guidelines are key drivers for adopting automated vision systems in canned goods manufacturing. The FSMA, especially, is a prevention-focused approach to food safety regulation throughout the supply chain. An emphasis on hazard analysis leaves facilities responsible for minimizing risks through proper identification and preventive control.
The food production industry has also endured labor shortages for several years, further incentivizing new technologies to fill in the gaps and alleviate supply chain pressures. Consumer demand for transparency and higher food quality standards is equally essential for automated visual system integration.
A recent National Sanitation Foundation Institute white paper found that 83% of American consumers read food labels, while 82% want more in-depth processing information. Utilizing this new technology can deliver on this expectation.
How Automated Vision Systems Prevent Post-Process Contamination
Automated vision systems prevent post-process contamination by looking for foreign objects — such as metals and biological materials — broken seals and incorrect labeling. The advanced cameras and machine learning algorithms capture images and insights about the product size, shape and characteristics, ensuring the precision of all information and packaging. In one study, the system’s detection capabilities achieved 97.88% and 88.75% efficiency and accuracy, respectively.
It also automates inspection data, enhances traceability and promotes regulatory compliance. The system’s exactness dramatically reduces human error for optimal quality assurance.
Implementation Considerations for Food Manufacturers
Canned goods manufacturing machinery must have flexible engineering, capable of rapid self-adjustment with minimal oversight, as it increasingly manages a mix of plastic, glass and aluminum containers. Lacking the proper equipment could result in product damage and reduced performance, hindering operations and customer satisfaction.
Implementing automated vision technology accommodates inspection parameters for various packaging types without manual recalibration. Their user-friendly interfaces streamline changeovers and support high-quality analysis, even with evolving packaging and stock-keeping units.
Comprehensive training is essential for deployment, so teams feel empowered to adapt to the new technology. Ongoing maintenance is also necessary to avoid operational disruptions. Predictive maintenance uses advanced sensors with embedded algorithms to detect problems before they occur or worsen, enabling technicians to gain control of the situation and avoid lost labor and revenue.
ROI and Measurable Benefits
Canned goods manufacturers benefit from a strong return on investment through reduced food waste and avoided product recalls. Research shows that recalls cost between $3 million and $72.7 million per organization, depending on firm size and type.
Contamination prevention also reduces the likelihood of foodborne illnesses and associated medical costs. In 2018, food-related pathogens posed an economic burden of $17.6 billion, up 13% from 2013.
Other direct and indirect financial impacts of unsafe food include reduced workplace productivity and absenteeism among those seeking medical treatment, increased liability insurance, legal proceedings and widespread reputational damage.
Future Trends for AI, IoT and Advanced Imaging
AI, the Internet of Things and predictive analytics are transforming automated vision systems, improving functionality for post-process contamination inspection. Advanced algorithms detect the most minor anomalies while packaging lines and regulatory standards become increasingly complex.
Adding edge computing has delivered more impressive results, although integrating it with legacy systems is challenging. Edge computing speeds up data processing, reduces latency and improves the digital security of sensitive information. These solutions are adaptive and learn new information on a decentralized network.
Machine vision cameras are also growing clearer and more precise. Zoom functions enable imaging from far distances and under varying lighting conditions, from inspection to sorting and processing. Likewise, event-based cameras react to motion in microseconds, eliminating blurring and adapting to brightness fluctuations.
Paving the Way for Safer, Smarter Canned Goods
Applying automated vision systems in canned goods manufacturing transforms how the industry addresses contamination risks with maximum efficiency. Investing in these solutions and prioritizing staff training enables seamless adoption and positions food processing plants for long-term expansion and innovation.
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