For the last two years, we consumers have experienced the global supply chain challenges associated with a variety of items such as lack of home appliances, favorite packaged foods or paper towels. And now the Ukraine war has sparked a new supply chain crisis with projected shortages of chemicals, oilseeds, iron, steel, fertilizers, wood, palladium and nickel. It’s clear that disruptions will continue as the world endures a crippled supply chain.
Most consumers don’t consider how supply chain interruptions affect the production and safety of so many of the foods we eat. Delays in any food ingredient or packaging can disrupt production schedules, delay shipments, and lead to empty retail shelves for thousands of food processors, manufacturers and retailers across the globe.
As manufacturers cope with these challenges, they frequently have to identify new suppliers or change processes and formulas on the fly. These unanticipated changes may often lead to shortcuts that can pose significant risks to consumers and cause food recalls.
It’s often hard to imagine all the interdependencies within the global supply chain, but one missed shipment or unavailable product can produce ripple effects throughout the globe. To reduce the risks associated with supply chain delays, food processors should implement resiliency measures such as effective change management and food safety vendor audit programs, detailed product specification and vendor expectation requirements, and multi-sourced vendor strategies.
To address these issues, this article reviews three ways food manufacturers can continue to minimize delays and reduce food safety risks when the supply chain interrupts production.
It’s always important to remember that employees can be the best defense against food safety threats. They’re the ones who interact with the products day-to-day and have the most familiarity with the ingredients. Their expertise is especially important now that supply chain disruptions are introducing new issues and anomalies.
Food manufacturers should train employees to understand which ingredients and products are acceptable and encourage them to speak up when they notice any anomalies. It’s also critical that training instills in workers the idea that they share the responsibility to ensure the safety and quality of the products they produce.
When frontline employees have the authority and the autonomy to alert their supervisors when they see something unusual or unexpected, they can become a powerful weapon in the food safety risk prevention arsenal. Harnessing the eyes of all your employees as your ultimate quality control team will help prevent costly recalls, product rework and further production delays.
2. Review Supplier Specs
When food manufacturers start working with a new supplier, they should take the necessary time to review their detailed product specifications to understand the technical and functional aspects of their product. From nutritional values and potential allergens to ingredients and chemical properties, it’s critical to have a full picture of what goes into the product before incorporating it into your manufacturing process.
As a best practice, manufacturers should also ask for a copy of the supplier’s recent GFSI food safety audits or equivalent and proof of liability insurance.
It’s also critical to thoroughly review vendor product specifications to confirm that a newly sourced ingredient meets your purchase expectations, label requirements, and food safety and quality risk profile. Considering how quickly an interruption can occur, it’s important to establish new vendor expectations and develop a supplier questionnaire. In addition, always plan ahead by sourcing multiple backup suppliers prior to ingredient and packaging disruptions.
3. Examine Supplier Labels
Understanding the product specifications is a critical first step, but it’s equally important to compare the label to the specs to ensure it is compliant and expected.
When a package arrives on the dock, receivers need to know if the contracted product has arrived as specified. Is the product packaged correctly, within expected shelf life, in a sanitary condition? Receivers should answer these and other questions by looking for inconsistencies per pallet like mixed lot codes and product shelf-life variances. Employees should also check the condition of incoming products including noting unusual odors or colors that might not seem right or for packaging that looks different from prior shipments.
The ongoing supply chain disruptions are predicted to continue this year, which means they can potentially cause food safety challenges based on inconsistencies in raw materials and undocumented process changes in production. Food safety leaders must hone their change management skills to successfully lead their organizations through these challenging times.
Adhering to the strict practices detailed in this article might seem like a lot of extra work and attention, but it’s actually something food manufacturers should be doing all the time as part of a mature food safety culture.
Undeclared allergens continue to be a big cause of food recalls. For allergen management practices to be effective within food companies, there must be a shared responsibility between food manufacturers, government agencies, regulators and consumers, says Guangtao Zhang, Ph.D., director of the Mars Global Food Safety Center. In a Q&A with Food Safety Tech, Zhang discussed key concerns related to undeclared allergens in food as well as the research that Mars is conducting to improve allergen management.
Food Safety Tech: The presence of undeclared allergens continues to be a hazard in the food safety space. Specific to peanut detection, what challenges is the industry facing?
Guangtao Zhang, Ph.D.: As food materials become more varied and complicated, food allergen management becomes increasingly complex. Robust, accurate and sensitive detection methods are essential to ensure consumer safety as well as compliance with regulatory standards for allergens in the food supply chain.
When you look at the regulatory aspects, detection methods go hand in hand. Firstly, there is a need to ensure that current standard detection methods used in regulatory control of consumer goods are validated for a range of complex food matrices to ensure neither over- nor under-estimation of allergen content occurs within a food supply chain. This is important because underestimation of allergen poses a significant food safety hazard to consumers, while overestimation of allergen can result in unnecessary product recalls, driving up product costs and food waste.
Secondly, validation and monitoring of the effectiveness of cleaning and handling practices in areas of potential cross contamination with allergen containing materials depend on reliable and robust quantitative food allergen test methods for their success. The more robust the testing protocols, the more we can improve our understanding of the risks associated with cross contamination of food allergens, potentially reducing the frequency of accidental contamination events.
It is also important to note that whilst the most common cause of undeclared allergen in the global food supply chain is through accidental contamination in raw materials or finished products, this is not the only method by which undeclared allergen may be found in a product.
For example, peanut flour may be used in economically motivated adulteration (EMA) food fraud cases. In 2018 the European Commission estimated that the cost of food fraud for the global food industry is approximately €30 billion every year. Due to its high protein content, peanut flour has been used as a bulking agent to raise the overall protein content of e.g., wheat flour, thus raising the ‘quality’, and therefore price, of lower value goods. The ability to effectively quantify peanut traces within complex products therefore has the potential to enable consumers of food products to further trust the safety of the food they eat.
ELISA (Enzyme linked immunosorbent assay) is the method used most frequently for peanut allergen detection in the food manufacturing industry because of its sensitivity and ease of use. However, it has disadvantages in certain settings. It is not currently validated for complex food matrices, as it is believed that the effects of both food matrices and food processing could result in an underestimation of peanut concentrations in thermally processed foods, leading to false negatives, as well as overestimation in complex food matrices, leading to false positives which are a potential food safety hazard to consumers.
Food Safety Tech: Tell us about the research that the Mars Global Food Safety Center is doing to help the industry with effective methods for peanut quantification.
Zhang: At the Mars Global Food Safety Center (GFSC) we believe that everyone has the right to safe food and that we have a responsibility to generate and share insights to help solve for global food safety challenges. We also know we can’t tackle these alone, which is why we collaborate with external partners. One of our focus areas is advancing understanding and knowledge sharing in peanut allergen detection. As part of that work, we are exploring methods of improving food safety via the development of advanced analytical methods to detect peanut allergen content, in the hopes that it will enable the food industry to expand on current preventative management protocols, including early detection methodologies, for faster response to future food allergen contamination events.
As part of our latest published research, we investigated the accuracy and sensitivity of ELISA-based test methods on raw and cooked wheat flour, wheat flour-salt and wheat flour-salt-oil matrices, which are common ingredients in the food industry. 10 ppm peanut was doped into each matrix during sample preparation. Recovery testing demonstrated that in all matrices the current industry standard ELISA method overestimated results with recoveries ranging from 49.6 to 68.6 ppm.
These findings prompted the development of a new confirmatory method based on liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) for peanut quantification. When subjected to the same validation testing programme the HPLC-MS/MS technique was demonstrably more accurate and sensitive, with a limit of quantification of 0.3 ppm and the detected peanut concentration ranging from 6.8 to 12.8 ppm for samples doped with 10 ppm peanut.
This work is a first step in the development of a new standard method for peanut detection in complex food matrices and could ultimately inform safer manufacturing Quality & Food Safety (Q&FS) processes across global supply chains to help ensure safe food for all.
Food Safety Tech: What projects are researchers at the Center working on to enhance allergen management as a whole?
Zhang: A successful allergen management program depends on rigorous control of allergenic foods and ingredients from all other products and ingredients at every step of the food production process, from raw material development to the delivery of final products. This means that for allergen management practices to be effective, they must be a shared responsibility between food manufacturers, government agencies, regulators and consumers.
At the Mars GFSC, we take a precompetitive approach to research, knowledge sharing and collaborations—this means we openly share insights and expertise to help ensure safe food for all. This is important in driving forward innovations, helping unlock solutions that may not have previously been possible.
We have shared our latest work both through an open access publication in Food Additives & Contaminants: Part A but also directly with regulatory bodies such as the FDA in the hopes of advancing knowledge in both food safety risk management and allergen management in complex flour-based media within global supply chains. In addition to this, this research contributes to a wider Food Safety Best Practice whitepaper focused on food allergen risk management currently under draft by the Mars GFSC, which will be published in collaboration with Walmart Food Safety Collaboration Center and the Chinese Institute of Food Science and Technology (CIFST) later this year.
We believe that global collaborations such as this are essential to improving food allergen management and mitigating food safety risks. Communication, training and knowledge sharing are core principles of the Mars GFSC and as such form a large part of our ongoing activities in this space. For example, we have hosted Food Allergen Management workshops in collaboration with Danone and Romer Labs focused on helping to raise awareness of current and future food allergen trends. At one such event in 2019, 100 participants from 16 food companies came together to promote food allergen management in the industry and ensure that the next generation of food integrity testing capability is relevant, practical, and directly applicable to the real-world problems experienced by manufacturers and processors throughout the supply chain.
Representatives of the Mars GFSC have also shared our insights externally at a number of international conferences as well as during a Food Enterprise Food Allergen Management Seminar on topics including effective allergen management procedures, our guiding principles for allergen managements at Mars, and shared our approach to encourage and share knowledge with other manufactures in this area.
We continue to support requests for technical insights, for example providing insights during a global consultation session on General Principles for Labeling of Prepackaged Food. This resulted in the addition of characterization requirements for possible allergenic substances, promoting the use of a recognizable naming system in ingredient lists that contain allergen warnings.
Food Safety Tech: Can you comment on additional work your team is doing in the area of food fraud?
Zhang: Food allergen risk management forms only one part of our wider food integrity focus at the Mars GFSC. We are committed to helping ensure food authenticity in an increasingly complex, global food supply chain through collaboration with global partners to develop new and improved tools and analytical methods that help protect the integrity of raw materials and finished products.
We have collaborated with researchers at Michigan State University to develop a Food Fraud Prevention Cycle roadmap (Introducing the Food Fraud Prevention Cycle (FFPC): A dynamic information management and strategic roadmap) which answered questions such as how to detect food fraud, how to start a food fraud prevention program, what to do in terms of testing, how much testing is enough, and how to measure success. Our intention in publishing this research was that the adoption of a holistic and all-encompassing information management cycle will enable a globally harmonized approach and the continued sharing of best practices across industry partners.
More recently, we completed an international collaboration tackling rice adulteration together with Queen’s University Belfast (QUB), Agilent Technologies, International Atomic Energy Agency (IAEA), China National Center for Food Safety Risk Assessment (CFSA), and Zhejiang Yangtze Delta Institute of Tsinghua University (Yangtze Delta). This work successfully developed a two-tier testing program, capable of rapidly screening the geographical origins of rice within the global supply chain (Food Fingerprinting: Using a two-tiered approach to monitor and mitigate food fraud in rice). By developing a tiered system, we could ensure that manufacturers use the right techniques for the right occasion, to maximize the information available in investigating food fraud at the best value. As part of this work, we have helped develop hands-on training in Ghana and inform best practice guidance to help build the foundations of a strong food safety culture in rice authenticity across the global supply chain.
Is the future of food quality in the hands of machine learning? It’s a provocative question, and one that does not have a simple answer. Truth be told, it’s not for every entity that produces food, but in a resource, finance and time-constrained environment, machine learning will absolutely play a role in the food safety arena.
“We live in a world where efficiency, cost savings and sustainability goals are interconnected,” says Berk Birand, founder and CEO of Fero Labs. “No longer do manufacturers have to juggle multiple priorities and make tough tradeoffs between quality and quantity. Rather, they can make one change that optimizes all of these variables at once with machine learning.” In a Q&A with Food Safety Tech, Birand briefly discusses how machine learning can benefit food companies from the standpoint of streamlining manufacturing processes and improve product quality.
Food Safety Tech: How does machine learning help food manufacturers maximize production without sacrificing quality?
Berk Birand: Machine learning can help food manufacturers boost volume and yield while also reducing quality issues waste, and cycle time. With a more efficient process powered by machine learning, they can churn out products faster without affecting quality.
Additionally, machine learning helps food producers manage raw material variation, which can cause low production volume. In the chemicals sector, a faulty batch of raw ingredients can be returned to the supplier for a refund; in food, however, the perishable nature of many food ingredients means that they must be used, regardless of any flaws. This makes it imperative to get the most out of each ingredient. A good machine learning solution will note those quality differences and recommend new parameters to deal with them.
FST: How does integrating machine learning into software predict quality violations in real-time, and thus help prevent them?
Birand: The power of machine learning can predict quality issues hours ahead of time and recommend the optimal settings to prevent future quality issues. The machine learning software analyzes all the data produced on the factory floor and “learns” how each factor, such as temperature or length of a certain process, affects the final quality.
By leveraging these learnings, the software can then help predict quality violations in real-time and tell engineers and operators how to prevent them, whether the solution is increasing the temperature or adding more of a specific ingredient.
FST: How does machine learning technology reveal & uphold sustainability improvements?
Birand: Due to the increase in climate change, sustainability continues to become a priority for many manufacturers. Explainable machine learning software can reveal where sustainability improvements, such as reducing heat or minimizing water consumption, can be made without any effect on quality or throughput. By tapping into these recommendations, factories can produce more food with the same amount of energy.
Lead chromate, flour, curcuma, Metanil Yellow or Sudan Dye, anyone? These are just some of the possibly hazardous adulterants that may make their appearance in turmeric, a popular and pricey spice and ingredient in dietary supplements. The American Botanical Council published a laboratory guidance document to determine the proper methods for the analysis of a number of adulterants. The document gives lists of the methods with their pros and cons, grouped by type of adulterant.
The USDA estimates that foodborne illnesses cost more than $15.6 billion each year. However, biological contamination isn’t the only risk to the safety and quality of food. Food safety can also be compromised by foreign objects at virtually any stage in the production process, from contaminants in raw materials to metal shavings from the wear of equipment on the line, and even from human error. While the risk of foreign object contamination may seem easy to avoid, in 2019 alone the USDA reported 34 food recalls, impacting 17 million pounds of food due to ‘extraneous material’ which can include metal, plastic and even glass.
When FSMA went into effect, the focus shifted to preventing food safety problems, necessitating that food processors implement preventive controls to shift the focus from recovery and quarantine to proactive risk mitigation. Food producers developed Hazard Analysis and Critical Control Point (HACCP) plans focused on identifying potential areas of risk and placement of appropriate inspection equipment at these key locations within the processing line.
Metal detection is the most common detection technology used to find ferrous, non-ferrous, and stainless steel foreign objects in food. In order to increase levels of food safety and better protect brand reputation, food processors need detection technologies that can find increasingly smaller metal foreign objects. Leading retailers are echoing that need and more often stipulate specific detection performance in their codes of practice, which processors must meet in order to sell them product.
As food processors face increased consumer demand and continued price-per-unit pressures, they must meet the challenges of greater throughput demands while concurrently driving out waste to ensure maximum operational efficiencies.
Challenges Inherent in Meat Metal Detection
While some food products are easier to inspect, such as dry, inert products like pasta or grains, metal foreign object detection in meat is particularly challenging. This is due to the high moisture and salt content common in ready-to-eat, frozen and processed, often spicy, meat products that have high “product effect.” Bloody whole muscle cuts can also create high product effect.
The conductive properties of meat can mimic a foreign object and cause metal detectors to incorrectly signal the presence of a physical contaminant even when it is nonexistent. Food metal detectors must be intelligent enough to ignore these signals and recognize them as product effect to avoid false rejection. Otherwise, they can signal metal when it is not present, thus rejecting good product and thereby increasing costs through scrap or re-work.
Equipping for Success
When evaluating metal detection technologies, food processors should request a product test, which allows the processor to see how various options perform for their application. The gold standard is for the food processor to send in samples of their product and provide information about the processing environment so that the companies under consideration can as closely as possible simulate the manufacturing environment. These tests are typically provided at no charge, but care should be taken upfront to fully understand the comprehensiveness of the testing methodologies and reporting.
Among the options to explore are new technologies such as multiscan metal detection, which enables meat processors to achieve a new level of food safety and quality. This technology utilizes five user-adjustable frequencies at once, essentially doing the work of five metal detectors back-to-back in the production line and yielding the highest probability of detecting metal foreign objects in food. When running, multiscan technology allows inspectors to view all the selected frequencies in real time and pull up a report of the last 20 rejects to see what caused them, allowing them to quickly make appropriate adjustments to the production line.
Such innovations are designed for ease of use and to meet even the most rigorous retailer codes of practice. Brands, their retail and wholesale customers, and consumers all benefit from carefully considered, application-specific, food safety inspection.
The food processing industry is necessarily highly regulated. Implementing the right food safety program needs to be a top priority to ensure consumer safety and brand protection. Innovative new approaches address these safety concerns for regulatory requirements and at the same time are designed to support increased productivity and operational efficiency.
The spread and impact of the COVID-19 pandemic has been fast and furious across the globe.1 The toll on human life and the economy is being felt by everyone, everywhere. Closures of schools and restaurants, restrictions on social gatherings, the shift to working from home, and other social distancing practices have created sudden, unusually high demand spikes across a number of categories, particularly related to food.
COVID-19 in the Food Industry: Mitigating and Preparing for Supply Chain Disruptions | Attend this complimentary webinar on-demandRepercussions from these dramatic demand surges are being felt across entire supply chains. Growers, producers, processors, manufacturers, wholesalers, and retailers of all sizes are scrambling to fill immediate shortages.2,3 At the same time, foodservice operators are reassessing their needs in response to government mandated take-out/delivery-only service. Schools are consolidating preparation and pick-up points for breakfast and lunch programs, while on-campus foodservice venues have closed at colleges and universities. Food companies are scrambling to redeploy and redirect existing inventories, as well as forecast short and mid-term demand and production requirements in the face of an unprecedented situation.
In the first several days of disruption, the immediate response is all-hands-on-deck damage control. Rightfully so. But in the flurry of activity, it is critical that those responsible for demand forecasting document the disruption as it is happening. Why? Because sales history is the foundational input of sales forecasting algorithms. Outlier events, such as COVID-19, natural disasters, extreme weather, short-term international trade restrictions, etc., have the potential to distort demand trends if they aren’t recognized and weighted appropriately in forward-looking projections. Formally documenting extraordinary events allows organizations to:
Explain unusual variances to history and/or forecast
Create evergreen institutional knowledge (vs. relying on individuals, scattered notes, and memory)
Build a “disruption database” that can be used to make fact-based overrides to algorithm-generated statistical forecasts when a similar disruption is predicted or occurs in the future.
These “disruption databases” could ultimately serve as the foundation for even more sophisticated disruption forecasting models. As machine learning and artificial intelligence continue to evolve, these models could potentially be customized based on the type of event. Importantly, this annotation of events needs to occur within your forecasting platform so that it is permanent and visible to inform insights for all forecast users.
So, what information should you capture?
Timing of the event
This includes specific days or weeks as well as information across the event lifecycle, including pre, during, and post event completion.
The scale of the event should also be noted. Some events are market-specific (i.e., the 2020 Nashville tornado), while others are state or region-specific (i.e. California wildfires, Hurricane Katrina) or result in national or global level impacts (COVID-19).
The ship-to locations of your customers relative to the disruption will influence the demand impact of the event.
Customer gains & losses
During shortages, changes to current customer strategies should also be accounted for, such as potential volume reallocations. This could mean realignment of current customer distribution centers, temporarily not shipping to or losing specific customers, and/or even securing new customers based on your ability to supply when competitors cannot.
Customers may also shut down temporarily and/or delay previously scheduled new store openings. They may also reduce their hours of service and/or increase frequency of deliveries.4
The use of different channels in response to the event should also be captured. For example, in response to COVID-19, grocery retailers are seeing a significant increase in home delivery and click-and-collect orders.
Collaborate with your customers to quantify this shift. It may explain your volume trends (if your products are or aren’t typically purchased online) and/or suggest alternative product forms, packaging, etc. to meet both immediate needs and longer-term demand.
This includes both items with demand spikes as well as those realizing unexpected demand declines. Shifts may also occur between product forms. For example, some consumer concern about bulk produce has been expressed with COVID-19 since the produce is manually stocked and shopped.5 While efforts are underway to dispel this misconception, it has impacted short-term demand for both the bulk items and their pre-packed counterparts.6,7
Adjacent, complementary and/or substitutable items should also be considered.8 Focusing short-term production on core varieties, cuts, forms, etc. vs. a complete assortment may allow a faster return to category (if not item-specific) in-stock levels.
Ordered vs. filled quantities
Typically, sales reporting systems only capture what was shipped/invoiced, not what was ordered. Capturing and comparing both enables quantification of the demand “opportunity loss,” which could be factored into future “event” forecast models.
Consumer sentiment and behavioral shifts
Specific to COVID-19, NielsenIRI and Crisp DemandWatch have identified “phases” of consumer behavior and anticipated category purchase impacts. Noting when these phases occur in your forecasting system can provide insight into performance analysis and inform future projections. These consumer patterns may also have application to other extreme events, such as natural disasters.9,10
In the face of significant disruptions, look for, leverage, and annotate relevant consumer insights to inform the forecast. Link the annotation to a central archive of relevant research and data to expand access and understanding across your organization.
Raw material, ingredient, packaging, labor or other sourcing issues
Note any shortages that impacted your ability to meet demand. Your ability to satisfy demand may be impacted by your own suppliers’ ability to get you the necessary inputs and/or your ability to staff production runs.
Distribution & logistics issues
Access to truck, rail, and/or air transportation of products may also be disrupted by the event. Note any logistics constraints to delivering finished goods to customers.
New product launches, delivery systems, ownership, facility fires, labor shortages or disputes, weather patterns, and more that impact your competitors can also influence demand for your products, both in the short and long term.
In the heat of the crisis, this level of documentation may sound burdensome. Even if you start with notes on a scratch pad, email chains, and a collection of industry newsletters, set aside one morning or afternoon a week to annotate within your forecasting platform the factors that impacted demand that week. Continue to post notations in the week each specific disruption-driving factor begins and each week thereafter until its impact has dissipated. Keeping up with annotations as you go along will keep things fresher in your mind and can help inform immediate and near-term plans.
Don’t forget that pantry loading shelf-stable items early in a disruption may significantly impact post-disruption sales, as consumers work through inventory they have at home. Track this as well. Best-in-class forecasting platforms, such as the example shown in Figure 1, can effectively leverage advanced computing power and analytics to help visualize the impact of COVID-19 on supply and follow-on effects predicted to be felt in your markets. The disruption information you track can be gathered, organized, and analyzed along with trillions of data points from disparate sources to generate high-quality statistical demand forecasts and actionable insights with speed and precision.
When the dust settles on this current event, take the time to document other historical disruptions. Working in reverse chronological order, gather as much date-specific archived data and tribal knowledge as you can, and add it to the annotations in your forecasting platform. The next time a disruption occurs (and it will!), you will be equipped to draw on this “database of disruptions” to proactively predict and respond to future impacts on demand.
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.
FSMA has arrived with the launch of the first two preventive control rules – Current Good Manufacturing Practice and Hazard Analysis and Risk-Based Preventive Controls for Human and Animal Food (or cGMP and HARPC, for short). With these new FSMA rules, the food and beverage industry will now be held accountable for being more proactive versus reactive, and will be responsible for identifying and managing risk throughout their supply chain. Of course, this emphasis on risk can also be seen in other sectors of the industry (i.e., GFSI and ISO), and risk has become the focal point for a number of compliance initiatives.
These days a number of supply chain challenges are driving risk. Continued global expansion of the industry is resulting in more import and export activities. We are seeing consumer food trends shift toward riskier food/preparation options. Regulatory agencies continue to work on improving their food safety requirements. And the growing population is putting more demands on our current resources. All of these factors equates to great risk within all stages of the supply chain.
Therefore, it will be important that you understand what risk management entails and have the right tools to identify, assess and control the risks that you find throughout your supply chain.
So where do we start looking for risk? Here are a few examples of where your risk assessments should be performed:
External Partners. You need to build strategic relationships with your external partners (suppliers, contract manufacturers/co-packers, service providers, carriers, etc.) across the supply chain. Building trust through good communication and collaboration is essential to ensure that you can rely on your partners to do the right thing for both parties.
Raw Materials. Many hazards can be introduced into a facility through raw materials—whether we are talking about raw ingredients, packaging materials, chemicals, or other components used to produce your product. Some hazards to assess include pathogens, allergens, chemical residues, pests and foreign material.
Storage and Handling. When looking at risk during storage and handling, it is important to address several hazards including allergen control, temperature control, foreign material control, proper segregation and product flow.
Processing. A number of areas in processing can introduce hazards and therefore should be included in your risk assessment. These include improper sanitation, cross contamination/contact potential, foreign material contamination, critical control point deviations, pre-requisite program failures and mislabeling.
Shipping and Transport. Lastly, you must safeguard your shipping and transportation procedures in order to account for any potential risk once the product has left your facility. Areas to consider during your risk assessment include temperature control, condition and sanitation of truck and storage units, loading/unloading practices, security/tampering potential, accident/emergency recovery, and traceability.
For more information on risk management within the food and beverage supply chain, register to attend the free webinar “Supply Chain Management: Does What I Eat Put Me at Risk” on October 28, 2015. Speakers will discuss risk throughout the supply chain, focusing on supplier management and some of the new FSMA requirements. They will provide an overview of risk management and some of the tools that can be used to identify and assess risk. In addition, they will discuss how technology can help companies meet FSMA requirements.
Dr. Strong was speaking in a recent webinar onThe Importance of CAPA and Root Cause Analysis for the Food Industry, in which he discussed CAPA, Root Cause Analysis and the benefits of these quality systems. We present below the comprehensive list of questions as presented by Dr. Strong.
Questions to ask: People
Does the person know what he’s expected to do in this job?
Is he well trained?
How much experience does the person have?
Does the person have the right tools/ equipment needed to do the job?
Is the workload reasonable?
Does the person have adequate supervision and support?
Do physical conditions such as light or temperature affect their work?
Who does the person contact when problems arise?
Questions to ask: Method
How is the process used defined?
Is the process regular reviewed for adequacy?
Is the process used affected by external factors?
Have any changes been made recently in the process?
What adjustments must the operator make during the process?
How does the operator know if the process is operating effectively?
Have other methods or processes been considered?
‘What would you do if things go wrong,’ this could be the most revealing question you can ask your employees that it may identify a real issue, added Dr. Strong.
Questions to ask: Equipment
How old is the equipment or machinery?
Is preventive maintenance performed regularly on it?
Is the machine affected by heat, vibration, or other physical factors?
How does the operator know if the machine is operating correctly?
What adjustments must the operator make during the process?
Have any changes been made recently in the equipment?
How is the equipment cleaned?
What tools are used to clean the equipment?
Questions to ask: Raw materials
What is the source of the raw material?
Has there been a change in suppliers recently?
How is the raw material produced?
How is the safety of the raw material verified?
How old is the raw material?
How is safety assessed prior to your operation?
What is the level of safety and quality?
How is the raw material packaged?
Can temperature, light or humidity affect the material quality?
Questions to ask: Environment
How are environmental conditions monitored?
How are environmental conditions controlled?
How is environmental control measuring equipment calibrated?
Are there changes in conditions at different times of the day?
Does environmental change affect the processes being used?
Does environmental change affect the materials being used?
Questions to ask: Inspection System
How frequently are products inspected?
How is the measuring equipment calibrated?
Are all products measured using the same tools or equipment?
How are inspection results recorded?
Is there a set of procedures and do inspectors follow the same procedures?
Do inspectors know how to use the test equipment?
Ask your team ‘what would happen if the systems weren’t calibrated? Are they giving you valid results?’ Probably that’s why you are not in compliance, explains Dr. Strong.
All this take takes time and effort, and Dr. Strong urges management to devote the resources to go around ask these questions and get the answers.
What is your experience with Root Cause Analysis? Have your used such questions? Do you have more to add? Join the discussion by commenting below.
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