To get to the restaurant table, food must travel great lengths to preserve that farm fresh quality and in many cases, IoT-enabled sensors are being used to do this. This is especially important as the World Health Organization estimates that one in 10 people fall ill every year from eating contaminated food.
When we think of our favorite dish, we often associate it with delicious flavors, pleasant scents and even memories of a night out with friends. What we likely don’t consider is technology, something that’s critical in ensuring the meal on our plate is safe to consume. Technology plays an essential role in guaranteeing that restaurants are serving fresh food to customers. From identifying operational deficiencies to protecting the overall brand of an organization, there are certain measures restaurants are taking—whether local or country-wide chains—to ensure food quality remains a top priority.
Restaurants are perhaps held to an even higher standard than your local supermarket when it comes to the quality of food on the table. Therefore, it’s imperative that perishables are cared for properly throughout the entirety of the food supply chain and that starts well before the food ever enters the restaurant’s front door. With long-range, low-power wireless IoT technology, farmers can get insights into a number of variables that may impact the growth of their crops. Armed with that knowledge, they can make real-time decisions to optimize crop growth and ultimately produce a greater yield. For example, farmers today can set up a series of sensors throughout their farm to measure real-time soil conditions, including humidity and pH levels. If they notice an especially high pH, for example, they can immediately remedy the situation and provide the crop with the proper nutrients or conditions it needs to grow.
For food safely to arrive at restaurants, it must be kept in a controlled environment during its journey from the farm or warehouse, and carefully monitored during that time. The temperature of refrigerated shipping units or storage facilities is an incredibly important factor, as bacteria growth can increase even by simply opening the refrigerator door or with a slight temperature shift, and employees are often tasked with managing this. With large facilities comes increased labor for employees, which can lead to inefficient temperature monitoring. To eliminate food waste and contamination, IoT sensors deployed throughout facilities can eliminate human error, and deliver more consistent monitoring, via real-time updates when temperatures enter unsafe territories.
Numerous international food handling and food safety laws have been implemented to reduce the risk of foodborne illness resulting from bacterial growth. A major component of most “farm-to-fork” regulations is the ability to track, report and maintain appropriate temperature conditions inside refrigeration and freezer units throughout the entire cold chain—including when the food finally makes it the restaurant.
This is a universal priority for restaurants around the world, including Hattie B’s Hot Chicken, a southern-style food chain, which started in Nashville and now has locations nationwide. To successfully do this, the restaurant turned to technology. They used a supplier of wireless connectivity solutions with integrated long range, low power technology for temperature monitoring sensors. The sensors, which are capable of penetrating stainless steel doors and concrete walls, can monitor temperatures in refrigerators and freezers. This is essential, as the technology eliminates possible human error in manually checking temps and other food safety procedures. In instances where refrigerator temperatures shift out of range, the technology remotely notifies restaurant managers in real-time, allowing them to act quickly, ensuring their perishables remain fresh and safe for customers at all times.
Food waste in restaurants is closely tied to food safety. In the United States alone, food waste is estimated to be between 30–40% of the food supply, according to the USDA. In the restaurant industry in particular, human error is one of the most notable reasons for food waste. To eliminate the human error when handling food and monitoring storage, an IoT solution provider for the industrial, smart city and smart energy segments, integrated long-range low power technology into smart refrigeration solutions for restaurant applications. This IoT solution is designed for humidity and temperature monitoring, delivering real-time updates to managers to ensure the shelf life of food is maximized and it remains safe to consume, ultimately leading to a decrease in food waste.
From farm to table, technology plays an essential role in ensuring restaurants are delivering the highest quality of fresh, safe food. It allows organizations to identify operational deficiencies and reduce overall food safety risk, which is imperative when maintaining a strong business in a competitive industry.
Food safety remains a top-of-mind concern for food manufacturers, especially considering some of the top recalls in 2019 were caused by bacteria contamination—including Listeria and E. coli. Every aspect of the plant operation, from maintenance to executives, to junior staff and quality control, holds both responsibility and concern in producing safe food. Unfortunately, there’s a lot at stake when plant operations’ sanitation programs run into issues, which can cause health threats.
While the rapid explosion of new innovations complements our daily lives in efficiency and convenience, plant operations may find difficulty in keeping up-to-speed with new technology such as robotics, drones and automated applications. When facilities’ equipment becomes more and more outdated, it poses food safety challenges around cleaning, maintenance and upgrades.
Luckily, in some cases, innovation is becoming much easier to deploy. Opportunities abound for food processing plants to integrate new technologies into their operations to deliver significant returns on investment while simultaneously enhancing sanitation, safety and production efficiency on the plant floor.
The Dangers with Today’s Practices
There are many pitfalls with older, more traditional cleaning techniques. In a place where cleanliness is critical to food safety and public health around the world, the industry understands sanitation means more than just scrubbing, mopping and wiping. While these are important daily practices to be done around the processing plant, there are still concerns on whether this kind of intermittent cleaning is truly enough to keep surfaces completely sanitized—knowing that continuous cleaning around the clock seems impractical in any facilities.
Unfortunately, there are many areas, some very hard to reach, for bacteria and other pathogens to live and spread around a processing plant. Zone 1, which holds the conveyor belt and other common high-touch points, consistently comes into contact with food, chemicals and humans. However, for processors to reduce the likelihood of contaminated food, they must consider areas outside of Zone 1 as well—including employee break rooms, hallways and bathrooms—to implement automated sanitation technologies. Additionally, the most common food contaminants, such as Listeria, Salmonella and E. coli, are usually invisible to the naked eye. Therefore, plants need to employ automated technology to continuously kill microscopic bacteria, mold and fungi to prevent regrowth and ensure clean food and equipment.
Looking to New Tech to Fight Germs
When looking to upgrade a plant operation facility, automated technology should be top-of-mind. Automated food production technologies solve two main problems: Food safety and sanitation efficiency. Wash-down robotic systems work to prevent food contamination, while other automated robots complete tasks on the production floor such as packaging, transporting and lifting. With the CDC estimating that roughly one in six Americans suffer from foodborne illnesses, the need for improved sanitation design is integral.
In today’s age, there are several ways to achieve heightened cleanliness by incorporating automation and robotics into production lines. Slicers, dicers and cutters are manufactured with hygienic design in mind. Smart cleaning equipment can automatically store various cleaning steps. Data tracking applications can monitor sanitation steps and ensure all boxes are checked throughout the cleaning program.
Incorporating antimicrobial LED lighting ensures sanitation is truly integrated into the facility’s design—working continually 24/7 to kill and prevent bacteria, and its growth while also serving a dual purpose of both antimicrobial protection and a proper source of illumination. As is the case with this type of technology, once these lights are installed, it becomes an easy, hands-free way of reducing labor, chemicals and, in many cases, work stoppages.
According to Meticulous Research, the global food automation market is expected to be worth $14.3 billion by 2025. With automation set to explode, it’s important for leaders in the food and beverage industry to take advantage of safety tech innovations to advance sanitation around the processing plant. Facility upgrades to improve, enhance and automate sanitation could impact food manufacturers in the long-term by decreasing costs, preventing recalls, improving brand value, gaining consumer trust, minimizing risk and impacting the bottom line.
The COVID-19 pandemic has negatively affected consumers and businesses across the globe. As the virus is now spreading throughout American soil, the food industry is faced with mitigating the risk and minimizing the impact on business while ensuring that employees and consumers are protected. On March 25, Food Safety Tech is bringing together three experts in food safety to discuss the affect that the novel coronavirus is having on food safety and the greater industry. Sponsored by RizePoint and Sterilex, this is a complimentary webinar event.
Shawn Stevens, Food Industry Attorney, Food Industry Counsel, LLC
April Bishop, Senior Director of Food Safety, TreeHouse Foods Services, LLC
Jennifer McEntire, Ph.D., VP Food Safety & Technology, United Fresh Produce Association
I know, it’s a disgusting, lazy attention-grabbing image, but if you’ve stayed with me this far it must have worked. Sadly, the story is true; it was back in the 1980s the first time that I heard of how a mouse in a bottling plant got stuck inside one of the empties ready to go onto the filling line. Unnoticed, this mouse was immersed in the beverage, was then sealed in when the bottle cap was applied, and then drowned while the bottle was packaged and palletized. While the product moved through distribution to retail, its carcass slowly dissolved and went unnoticed until an unsuspecting customer … well, you can imagine how that story ended.
After recounting this story recently, imagine my surprise to learn this is still happening today! Maybe three years ago, The Verge published a “A brief history of rodents in soda containers” and, in the present age of social media, it will surprise no one to see the video filmed by someone who spotted the mouse in their soda bottle! No surprise, there’s more than one filming of a mouse in a sealed Coca Cola bottle, the horror continues.
Let’s not pretend this is only a problem with fizzy drinks industry, every food manufacturing concern faces the risk of inadvertent contamination of their production from rodents; if not the whole animal itself, then it’s urination on raw commodity, or its fecal pellets falling into a mixer, or its hairs falling off in packaging. No wonder a well-designed and faithfully serviced pest management program and proper IPM inspections are necessary for every facility in the industry. The good news is there are digital rodent monitoring systems that can alert pest managers of a rodent capture inside a facility and rodent activity / pressure outside so they can act quickly. Perhaps the most valuable impact of this technology is that it helps automate trap checking that consumes as much as 75% of the service time. Now, that precious time can be reallocated to deeper, proactive IPM inspections to help head off infestations before they happen and root cause analysis and corrective actions if captures occur.
Traditional approaches to food safety no longer make the grade. It seems that stories of contaminated produce or foodborne illnesses dominate the headlines increasingly often. Some of the current safeguards set in place to protect consumers and ensure that companies are providing the freshest, safest food possible continue to fail across the world. Poorly regulated supply chains and food quality assurance breakdowns often sicken customers and result in recalls or lawsuits that cost money and damage reputations. The question is: What can be done to prevent these types of problems from occurring?
While outdated machinery and human vigilance continue to be the go-to solutions for these problems, cutting-edge intelligent imaging technology promises to eliminate the issues caused by old-fashioned processes that jeopardize consumer safety. This next generation of imaging will increase safety and quality by quickly and accurately detecting problems with food throughout the supply chain.
How Intelligent Imaging Works
In broad terms, intelligent imaging is hyperspectral imaging that uses cutting-edge hardware and software to help users establish better quality assurance markers. The hardware captures the image, and the software processes it to provide actionable data for users by combining the power of conventional spectroscopy with digital imaging.
Conventional machine vision systems generally lack the ability to effectively capture and relay details and nuances to users. Conversely, intelligent imaging technology utilizes superior capabilities in two major areas: Spectral and spatial resolution. Essentially, intelligent imaging systems employ a level of detail far beyond current industry-standard machinery. For example, an RGB camera can see only three colors: Red, green and blue. Hyperspectral imaging can detect between 300 and 600 real colors—that’s 100–200 times more colors than detected by standard RGB cameras.
Intelligent imaging can also be extended into the ultraviolet or infrared spectrum, providing additional details of the chemical and structural composition of food not observable in the visible spectrum. Hyperspectral imaging cameras do this by generating “data cubes.” These are pixels collected within an image that show subtle reflected color differences not observable by humans or conventional cameras. Once generated, these data cubes are classified, labeled and optimized using machine learning to better process information in the future.
Beyond spectral and spatial data, other rudimentary quality assurance systems pose their own distinct limitations. X-rays can be prohibitively expensive and are only focused on catching foreign objects. They are also difficult to calibrate and maintain. Metal detectors are more affordable, but generally only catch metals with strong magnetic fields like iron. Metals including copper and aluminum can slip through, as well as non-metal objects like plastics, wood and feces.
Finally, current quality assurance systems have a weakness that can change day-to-day: Human subjectivity. The people put in charge of monitoring in-line quality and food safety are indeed doing their best. However, the naked eye and human brain can be notoriously inconsistent. Perhaps a tired person at the end of a long shift misses a contaminant, or those working two separate shifts judge quality in slightly different ways, leading to divergent standards unbeknownst to both the food processor and the public.
Hyperspectral imaging can immediately provide tangible benefits for users, especially within the following quality assurance categories in the food supply chain:
Pathogen detection is perhaps the biggest concern for both consumers and the food industry overall. Identifying and eliminating Salmonella, Listeria, and E.coli throughout the supply chain is a necessity. Obviously, failure to detect pathogens seriously compromises consumer safety. It also gravely damages the reputations of food brands while leading to recalls and lawsuits.
Current pathogen detection processes, including polymerase chain reaction (PCR), immunoassays and plating, involve complicated and costly sample preparation techniques that can take days to complete and create bottlenecks in the supply chain. These delays adversely impact operating cycles and increase inventory management costs. This is particularly significant for products with a short shelf life. Intelligent imaging technology provides a quick and accurate alternative, saving time and money while keeping customers healthy.
Characterizing Food Freshness
Consumers expect freshness, quality and consistency in their foods. As supply chains lengthen and become more complicated around the world, food spoilage has more opportunity to occur at any point throughout the production process, manifesting in reduced nutrient content and an overall loss of food freshness. Tainted meat products may also sicken consumers. All of these factors significantly affect market prices.
Sensory evaluation, chromatography and spectroscopy have all been used to assess food freshness. However, many spatial and spectral anomalies are missed by conventional tristimulus filter-based systems and each of these approaches has severe limitations from a reliability, cost or speed perspective. Additionally, none is capable of providing an economical inline measurement of freshness, and financial pressure to reduce costs can result in cut corners when these systems are in place. By harnessing meticulous data and providing real-time analysis, hyperspectral imaging mitigates or erases the above limiting factors by simultaneously evaluating color, moisture (dehydration) levels, fat content and protein levels, providing a reliable standardization of these measures.
Foreign Object Detection
The presence of plastics, metals, stones, allergens, glass, rubber, fecal matter, rodents, insect infestation and other foreign objects is a big quality assurance challenge for food processors. Failure to identify foreign objects can lead to major added costs including recalls, litigation and brand damage. As detailed above, automated options like X-rays and metal detectors can only identify certain foreign objects, leaving the rest to pass through untouched. Using superior spectral and spatial recognition capabilities, intelligent imaging technology can catch these objects and alert the appropriate employees or kickstart automated processes to fix the issue.
Though it may not be put on the same level as pathogen detection, food freshness and foreign object detection, consumers put a premium on food uniformity, demanding high levels of consistency in everything from their apples to their zucchini. This can be especially difficult to ensure with agricultural products, where 10–40% of produce undergoes mechanical damage during processing. Increasingly complicated supply chains and progressively more automated production environments make delivering consistent quality more complicated than ever before.
Historically, machine vision systems and spectroscopy have been implemented to assist with damage detection, including bruising and cuts, in sorting facilities. However, these systems lack the spectral differentiation to effectively evaluate food and agricultural products in the stringent manner customers expect. Methods like spot spectroscopy require over-sampling to ensure that any detected aberrations are representative of the whole item. It’s a time-consuming process.
Intelligent imaging uses superior technology and machine learning to identify mechanical damage that’s not visible to humans or conventional machinery. For example, a potato may appear fine on the outside, but have extensive bruising beneath its skin. Hyperspectral imaging can find this bruising and decide whether the potato is too compromised to sell or within the parameters of acceptability.
Intelligent imaging can “see” what humans and older technology simply cannot. With the ability to be deployed at a number of locations within the food supply chain, it’s an adaptable technology with far-reaching applications. From drones measuring crop health in the field to inline or end-of-line positioning in processing facilities, there is the potential to take this beyond factory floors.
In the world of quality assurance, where a misdiagnosis can literally result in death, the additional spectral and spatial information provided by hyperspectral imaging can be utilized by food processors to provide important details regarding chemical and structural composition previously not discernible with rudimentary systems. When companies begin using intelligent imaging, it will yield important insights and add value as the food industry searches for reliable solutions to its most serious challenges. Intelligent imaging removes the subjectivity from food quality assurance, turning it into an objective endeavor.
By Benjamin A. Katchman, Ph.D., Michael E. Hogan, Ph.D., Nathan Libbey, Patrick M. Bird No Comments
The Golden Age of Bacteriology: Discovering the Unknown in a Farm-to-Market Food Supply.
The last quarter of the 19th Century was both horrific and exciting. The world had just emerged from four decades of epidemic in cholera, typhoid fever and other enteric diseases for which no cause was known. Thus, the great scientific minds of Europe sought to find understanding. Robert Koch integrated Pasteur’s Germ Theory in 1861 with the high technology of the day: Mathematical optics and the first industrialized compound microscopes (Siebert, Leiss, 1877), heterocycle chemistry, high-purity solvents (i.e., formaldehyde), availability of engineered glass suitable as microscope slides and precision-molded parts such as tubes and plates in 1877, and industrialized agar production from seaweed in Japan in 1860. The enduring fruit of Koch’s technology integration tour de force is well known: Dye staining of bacteria for sub-micron microscopy, the invention of 13 cm x 1 cm culture tubes and the invention of the “Petri” dish coupled to agar-enriched culture media. Those technologies not only launched “The Golden Age of Bacteriology” but also guided the entire field of analytical microbiology for two lifetimes, becoming bedrock of 20th Century food safety regulation (the Federal Food, Drug and Cosmetic Act in 1938) and well into the 21st century with FSMA.
Learn more about technologies in food safety testing at the Food Labs / Cannabis Labs Conference | June 2–4, 2020 | Register now!Blockchain Microbiology: Managing the Known in an International Food Supply Chain.
If Koch were to reappear in 2020 and were presented with a manual of technical microbiology, he would have little difficulty recognizing the current practice of cell fixation, staining and microscopy, or the SOPs associated with fluid phase enrichment culture and agar plate culture on glass dishes (still named after his lab assistant). The point to be made is that the analytical plate culture technology developed by Koch was game changing then, in the “farm-to-market” supply chain in Koch’s hometown of Berlin. But today, plate culture still takes about 24 to 72 hours for broad class indicator identification and 48 to 96 hours for limited species level identification of common pathogens. In 1880, life was slow and that much time was needed to travel by train from Paris to Berlin. In 2020, that is the time needed to ship food to Berlin from any place on earth. While more rapid tests have been developed such as the ATP assay, they lack the speciation and analytical confidence necessary to provide actionable information to food safety professionals.
It can be argued that leading up to 2020, there has been an significant paradigm shift in the understanding of microbiology (genetics, systems based understanding of microbial function), which can now be coupled to new Third Industrial Age technologies, to make the 2020 international food supply chain safer.
We Are Not in 1880 Anymore: The Time has Come to Move Food Safety Testing into the 21st Century.
Each year, there are more than 48 million illnesses in the United States due to contaminated food.1 These illnesses place a heavy burden on consumers, food manufacturers, healthcare, and other ancillary parties, resulting in more than $75 billion in cost for the United States alone.2 This figure, while seemingly staggering, may increase in future years as reporting continues to increase. For Salmonella related illnesses alone, an estimated 97% of cases go unreported and Listeria monocytogenes is estimated to cause about 1,600 illnesses each year in the United States with more than 1,500 related hospitalizations and 260 related deaths.1,3 As reporting increases, food producers and regulatory bodies will feel an increased need to surveil all aspects of food production, from soil and air, to final product and packaging. The current standards for pathogenic agriculture and environmental testing, culture-based methods, qPCR and ATP assays are not able to meet the rapid, multiplexed and specificity required to meet the current and future demands of the industry.
At the DNA level, single cell level by PCR, high throughput sequencing, and microarrays provide the ability to identify multiple microbes in less than 24 hours with high levels of sensitivity and specificity (see Figure 1). With unique sample prep methods that obviate enrichment, DNA extraction and purification, these technologies will continue to rapidly reduce total test turnaround times into the single digit hours while simultaneously reducing the costs per test within the economics window of the food safety testing world. There are still growing pains as the industry begins to accept these new molecular approaches to microbiology such as advanced training, novel technology and integrated software analysis.
It is easy to envision that the digital data obtained from DNA-based microbial testing could become the next generation gold standard as a “system parameter” to the food supply chain. Imagine for instance that at time of shipping of a container, a data vector would be produced (i.e., time stamp out, location out, invoice, Listeria Speciation and/or Serovar discrimination, Salmonella Speciation and/or Serovar discrimination, refer toFigure 1) where the added microbial data would be treated as another important digital attribute of the load. Though it may seem far-fetched, such early prototyping through the CDC and USDA has already begun at sites in the U.S. trucking industry, based on DNA microarray and sequencing based microbial testing.
Given that “Third Industrial Revolution” technology can now be used to make microbial detection fast, digital, internet enabled and culture free, we argue here that molecular testing of the food chain (DNA or protein based) should, as soon as possible, be developed and validated to replace culture based analysis.
Scallan, E., Hoekstra, R. M., Angulo, F. J., Tauxe, R. V., Widdowson, M. A., Roy, S. L., … Griffin, P. M. (2011). Foodborne illness acquired in the United States–major pathogens. Emerging infectious diseases, 17(1), 7–15. doi:10.3201/eid1701.p11101
Scharff, Robert. (2012). Economic Burden from Health Losses Due to Foodborne Illness in the United States. Journal of food protection. 75. 123-31. 10.4315/0362-028X.JFP-11-058.
Mead, P. S., Slutsker, L., Dietz, V., McCaig, L. F., Bresee, J. S., Shapiro, C., … Tauxe, R. V. (1999). Food-related illness and death in the United States. Emerging infectious diseases, 5(5), 607–625. doi:10.3201/eid0505.990502
Much of the attention that cybersecurity gets is on the IT or office network side of things, but recently people have begun paying more attention to operational technology (OT) systems that make up the country’s critical infrastructure. When people think of critical infrastructure, they automatically think of oil and gas, power generation, and water. Many people don’t realize that there are actually 16 critical infrastructure industries:
Water and Wastewater
Food and Agriculture
One of the easily forgotten, but perhaps most important, is food and beverage manufacturing. A cyber attack on a food and beverage company might not result in the lights going out or clouds of toxic gas, but they could result in explosions, or tainted food. We need to start paying more attention to cybersecurity in the food and beverage industry. What would happen if a hacker got into the control system at a frozen foods distribution facility? They could raise the temperature in the freezers, thaw the food and then refreeze it. This could result in food poisoning for hundreds or thousands of people. Bad actors can do a lot of harm by targeting this sector.
Many companies are pushing to combine their IT and OT departments, something they call IT/OT convergence. This can be done, but you need to first understand that IT and OT have differing goals.
It is important to review the organizational structure. You will typically find that both IT and OT report organizationally to the CEO level. We also find senior management believes IT owns the industrial control system (ICS) networks and security—mainly because IT owns support, maintenance & operational budget for network and security (basically letting OT off the hook).
IT’s primary goals are confidentiality, integrity and availability, the CIA triad. While working toward these objectives IT also tries to make it possible for users to access the network from any location from which they are working, using whatever computing device they have with them. The goal is to make it as easy to work from an airport, hotel room or coffee shop as it is to work in the office itself. Technology is updated and replaced often. Service packs are loaded, new software releases are loaded, and bugs are fixed.
OT’s primary goals are availability, integrity and confidentiality—a complete reversal of the CIA triad. They strive to keep production running, be it an electric utility, an oil rig or a pop-tart factory 24/7/365. OT is all about what works, a “We’ve always done it that way” mentality. OT will always be reluctant to make any change that might bring down the production line. Remember, they are graded on widgets per minute. There must be trust and open communication between IT and OT if things are going to work properly.
When we are talking about OT cybersecurity, we usually use terms like secure or prevent, when we really should be thinking about words like containment. Securing the network and preventing attacks is important, but at some point, an attack will get past your defenses. Then it is a matter of containment: How do we keep the problem from spreading to other networks?
One thing to definitely avoid is the desire by IT to have bi-directional communications between the IT and OT networks—this should never happen. Also, avoid the desire to connect the ICS to the Internet so that you can control the process remotely. There is no reason for the plant manager to be able to go home, have a couple beers and then log on to see if he can make things run better. If the control system is going to be connected to the corporate IT or the Internet, it should only have out-going uni-directional data transmission to allow monitoring of the system.
Building a good OT cybersecurity program, you need to do three things:
Get C-Level support and buy-in for the changes to be made.
Communicate with stakeholders and vendors.
Make decisions as a team, make sure all the stakeholders, IT, OT, engineering are all involved.
After you have set up the structure and started communicating, you need to begin cybersecurity awareness training for the OT staff. This training should be focused on educating plant personnel on what cybersecurity is, both at work and at home, and how to respond or escalate something that seems wrong. They need to be trained what needs to be dealt with immediately and what can wait. Consider doing tabletop exercises where you practice what to do when certain things occur. This can act as a stress test for your incident response plan and help find the holes in your plan and procedures. These tabletop exercises should involve C-suite individuals as well as people from the plant floor, so everyone understand their part in a cyber-attack response.
If these concepts are followed, you will be well on your way to creating a much more cyber-secure production environment.
The Netherlands Food and Consumer Product Safety Authority NVWA closed down an animal feed company that generated €4 million revenue selling contaminated feed with forged documents. Several thousand tons of waste, unsuitable to use in animal feed, was found at the facility, and three employees have been arrested.
Almost everybody loves chocolate, an ancient, basic, almost universal and primal source of pleasure. “The story of chocolate beings with cocoa trees that grew wild in the tropical rainforests of the Amazon basin and other areas in Central and South America for thousands of years… Christopher Columbus is said to have brought the first cocoa beans back to Europe from his fourth visit to the New World” between 1502 and 1504.1
Unfortunately, the production of chocolate and chocolate products today is as complex as any other global food product with supply chains that reach from one end of the world to the other. The complexity of the supply chain and production, along with the universal demand for the finished product, exposes chocolate to increasing pressure from numerous hazards, both unintentional and intentional. For example, we know that more than 70% of cocoa production takes place in West African countries, particularly the Ivory Coast and Ghana. These regions are politically unstable, and production is frequently disrupted by fighting. While production has started to expand into more stable regions, it has not yet become diversified enough to normalize the supply. About 17% of production takes place in the Americas (primarily South America) and 9% from Asia and Oceania.2
In today’s world of global commerce these pressures are not unique to chocolate. Food quality and safety experts should be armed with tools and innovations that can help them examine specific hazards and fraud pertaining to chocolate and chocolate products. In fact, the global nature of the chocolate market, requires fast reflexes that protect brand integrity and dynamic quality processes supported by informed decisions. Digital tools have become a necessity when a fast interpretation of dynamic data is needed. If a food organization is going to effectively protect the public’s health, protect their brand and comply with various governmental regulations and non-governmental standards such as GFSI, horizon scanning, along with the use of food safety intelligent digital tools, needs to be incorporated into food company’s core FSQA program.
This article pulls information from a recent industry report about chocolate products that presents an examination of the specific hazards and fraud pertaining to chocolate and chocolate products along with ways to utilize this information.
Cocoa and chocolate products rely on high quality ingredients and raw materials, strict supplier partnership schemes and conformity to clearly defined quality and safety standards. During the past 10 years there have been a significant number of food safety incidents associated with chocolate products. The presence of Salmonella enterica, Listeria monocytogenes, allergens and foreign materials in cocoa/chocolate products have been reported on a global scale. Today, information on food safety incidents and potential risks is quickly and widely available by way of the internet. However, because the pertinent data is frequently siloed, food safety professionals are unable to take full advantage of it.
Top Emerging Hazards: Chocolate Products (2013-2018)
Publicly available data, from sources such as European Union RASFF, Australian Competition and Consumer Commission, UK Food Standards Agency, FDA, Food Standards Australia New Zealand (FSANZ), shows a significant increase in identified food safety incidents for cocoa/chocolate products from 2013 to 2018. For this same time period, the top emerging hazards that were identified for chocolate products were the following:
Foreign bodies: 13.83%
Food additives & flavorings: 4.26%
Other hazards: 2.66%
By using such information to identify critical food safety protection trends, which we define to include food safety (unintentional adulteration) and food fraud (intentional adulteration, inclusive of authenticity/intentional misrepresentation) we can better construct our food protection systems to focus on the areas that present the greatest threats to public health, brand protection and compliance.
A Data Driven Approach
Monitoring Incoming Raw Materials
Assessment and identification of potential food protection issues, including food safety and fraud, at the stage of incoming raw materials is of vital importance for food manufacturers. Knowledge of the associated risks and vulnerabilities allows for timely actions and appropriate measures that may ultimately prevent an incident from occurring.
Specifically, the efficient utilization of global food safety and fraud information should allow for:
Identification of prevalent, increasing and/or emerging risks and vulnerabilities associated with raw materials
Comparative evaluation of the risk profile for different raw materials’ origins
Critical evaluation and risk-based selection of raw materials’ suppliers
A comprehensive risk assessment must start with the consideration of the identified food safety incidents of the raw material, which include the inherent characteristics of the raw material. Next, the origin-related risks must be taken into account and then the supplier-related risks must be examined. The full risk assessment is driven by the appropriate food safety data, its analysis and application of risk assessment scientific models on top of the data.
Using food safety intelligent digital tools to analyze almost 400 unique, chocolate product related food safety incidents around the globe provides us with important, useful insights about cocoa as a raw material, as a raw material from a specific origin and as a raw material being provided by specific suppliers. The graph below represents the results of the analysis illustrating the trend of incidents reported between 2002 and 2018. It can be observed that after a significant rise between 2009 and 2010, the number of incidents approximately doubled and remained at that level for the rest of the evaluated period (i.e., from 2010 to 2018), compared to the period from 2002 to 2005.
By further analyzing the data stemming from the 400 food safety incidents and breaking them down into more defined hazards, for incoming raw materials, we can clearly see that chemical hazards represent the major hazard category for cocoa.
Organoleptic aspects: 5.93%
Other Hazards: 4.38%
Foreign bodies: 2.06%
Food additives and flavorings: .77%
Food contact materials: .52%
Using the appropriate analytical tools, someone can drill down into the data and identify the specific incidents within the different hazard categories. For example, within the “chemical hazard” category specific hazards such as organophosphates, neonicotinoids, pyrethroids and organochlorines were identified.
Comparative Evaluation of Risk Profiles for Different Origins of Raw Materials
The main regions of origin for cocoa globally are Africa, Asia and South America. After collecting and analyzing all relevant data from recalls and border rejections and the frequency of pertinent incidents, we can accurately identify the top hazards for cocoa by region.
The top five specific hazards for the regions under discussion are listed in Table I.
Poor or insufficient controls
Table I. Top Five Hazards By Region
After the first level of analysis, a further interpretation of the data using the appropriate data intelligence tools can help to reach to very specific information on the nature of the incidents. This provides additional detail that is helpful in understanding how the regional risk profiles compare. For example, the prevalence of chemical contamination, as either industrial contaminants or pesticides, has been a commonly observed pattern for all three of the regions in Table I. However, beyond the general hazard category level, there are also different trends with regard to specific hazards for the three different regions. One such example is the increased presence of mold in cocoa beans coming from Africa.
The primary hazard categories for cocoa, as a raw ingredient were identified and a comparison among the primary hazards for cocoa by region (origin-specific) should take place. The next step in a data-powered supplier assessment workflow would be to incorporate our use of global food safety data in evaluating the suppliers of the raw materials.
The Role of Global Food Safety Data
This article has been focused on chocolate products but has only touched the surface in terms of the information available in the complete report, which also includes specific information about key raw materials. Let’s also be clear, that the techniques and tools used to generate this information are applicable to all food products and ingredients. As we strive to produce food safely in the 21st Century and beyond, we must adapt our methods or be left behind.
The regulatory environment the food industry must operate in has never been more intense. The threats to an organization’s brand have never been greater. This is not going to change. What must change is the way in which food companies confront these challenges.
Global food safety data can contribute to the establishment of an adaptive food safety/QA process that will provide time savings and improve a quality team’s efficiency and performance.
Based on the continuous analysis of food recalls and rejections by key national and international food authorities, a food safety / quality assurance manager could establish an adaptive supplier verification process and risk assessment process by utilizing the knowledge provided by such data. In that way, QA, procurement, food safety and quality departments can be empowered with critical supplier data that will inform the internal procedures for incoming materials and ingredients (e.g., raw materials, packaging materials) and allow for adaptive laboratory testing routines and compliance protocols. Moreover, food safety systems can become adaptive, enabling quality assurance and safety professionals to quickly update points of critical control when needed, and intervene in important stages of the chocolate manufacturing process.
Yesterday the CDC reported that the E.coli outbreak linked to romaine lettucegrown in the Salinas, CA growing region is over. The contaminated lettuce should no longer be available, and FDA states that consumers do not need to avoid romaine lettuce from Salinas. The agency will continue its investigation into the potential factors and sources that led to the outbreak.
The FDA did identify a common grower link to the E.coli O157:H7 contamination as a result of its traceback investigation. However, a statement released yesterday by FDA Deputy Commissioner for Food Policy and Response Frank Yiannas points out that “this grower does not explain all of the illnesses seen in these outbreaks.”
To be specific, the FDA, CDC and other public health agencies were tracking three outbreaks involving three separate strains of E.coli O157:H7 linked to romaine lettuce. During the course of the investigation FDA, CDC, the California Department of Food and Agriculture and the California Department of Public Health conducted sampling of the water, soil and compost of several of the fields in the lower Salinas Valley that were connected to the outbreak. “So far, sample results have come back negative for all of the three outbreak strains of E. coli O157:H7. However, we did find a strain of E. coli that is unrelated to any illnesses in a soil sample taken near a run-off point in a buffer zone between a field where product was harvested and where cattle are known to occasionally graze,” Yiannas said in the agency statement. “This could be an important clue that will be further examined as our investigation continues. However, this clue does not explain the illnesses seen in these outbreaks.”
Finding the contamination source(s) is critical, as it will aid romaine growers in putting safeguards in place to help prevent future contamination.
As for the final case count (with last illness onset on December 21, 2019) of this outbreak, there were 167 total illnesses and 85 hospitalizations across the United States. No deaths were reported.
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