Tag Archives: allergens

Tamales

Public Health Alert for Poultry and Meat Products Containing FDA-Regulated Corn Starch

By Food Safety Tech Staff
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Tamales

The USDA Food Safety and Inspection Service (FSIS) has issued a public health alert for select La Guadalupana Foods, Inc. poultry and meat products, which contain an FDA-regulated corn starch that has been recalled due to an undeclared allergen, specifically milk.

FSIS issued the public health alert to ensure that consumers are aware that these products should not be consumed. The FSIS announcement notes that additional products may be added, as it is likely that additional meat and poultry products will be affected by the corn starch.

The list of products subject to the public health alert are available here. The tamales were shipped to warehouse, distributor and retail locations in Illinois, Indiana and Wisconsin. However, if other products are added, additional states might be affected.

FSIS and FDA are working together to determine the extent of the distribution of the corn starch to other establishments. There have been no confirmed reports of adverse reactions due to consumption of these products. FSIS urges consumers who have purchased these products not to consume them and either throw them away or return them to the place of purchase.

Allergens

FDA Issues Draft Guidance Emphasizing Increased Importance on Food Allergens

By Food Safety Tech Staff
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Allergens

Today the FDA issued a draft guidance that shines a spotlight on the importance of assessing food allergens that are not one of the nine major food allergens (milk, eggs, fish, crustacean shellfish, tree nuts, peanuts, wheat, sesame and soybeans). “The nine major food allergens don’t currently represent all foods nationwide that people are allergic to or that cause food hypersensitivities,” said CFSAN Director Susan Mayne, Ph.D., in an agency release. “This draft guidance is part of the FDA’s efforts to evaluate emerging evidence about other non-listed food allergens that can cause serious reactions in a consistent and transparent manner, which can inform potential future actions to better help protect the health of consumers.”

The draft, “Evaluating the Public Health Importance of Food Allergens Other Than the Major Food Allergens Listed in the Federal Food, Drug, and Cosmetic Act”, targets immunoglobulin E antibody (IgE)-mediated food allergies, which can cause severe and life-threatening reactions such as anaphylaxis. The document reviews the evidence that establishes a food as a cause of IgE-mediated food allergy and scientific factors, such as prevalence, severity and allergenic potency, that the FDA would consider in evaluations. It also reviews the agency’s recommendations for identifying and evidence to determine the public health importance of a non-listed food allergen.

Comments on the draft guidance can be submitted by August 17, 2022.

Plant based milk

How Advancements in Analytical Testing Are Supporting the Development of Novel Plant-Based Dairy Alternatives

By David Honigs, Ph.D.
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Plant based milk

Globally, milk and dairy products rank among the top eight allergens that affect consumers across the world. In America in particular, 32 million people suffer from some form of allergy, of which a staggering 4.7 million are allergic to milk. Additionally, it is estimated that around 70% of adults worldwide have expressed some form of lactose intolerance. As such, it is important for key stakeholders in the dairy industry to create novel products that meet the wants and needs of consumers.

Low-lactose products have been available since the 1980s. But in recent years, the demand for plant-based alternatives to dairy products has been on the rise. Some of this demand has come from individuals who cannot digest lactose or those that have an allergy to dairy. However, as all consumers continue to scrutinize their food labels and assess the environmental and ethical impact of their dietary choices, plant-based milk has become an appealing alternative to traditional dairy products.

To adapt to this changing landscape, traditional dairy processors have started to create these alternatives alongside their regular product lines. As such, they need access to instruments that are flexible enough to help them overcome the challenges of testing novel plant-based milk, while maintaining effective analysis and testing of conventional product lines.

 David Honigs, Ph.D. will share his expertise during the complimentary webinar, “Supporting the Plant-Based Boom: Applying Intuitive Analytical Methods to Enhance Plant-based Dairy Product Development” | Friday, December 17 at 12 pm ETLow in Lactose, High in Quality

Some consumers—although not allergic to dairy—lack the lactase enzyme that is responsible for breaking down the disaccharide, lactose, into the more easily digestible glucose and galactose.

Low-lactose products first started to emerge in 1985 when the USDA developed technology that allowed milk processors to produce lactose-free milk, ice cream and yogurt. This meant consumers that previously had to avoid dairy products could still reap their nutritional benefits without any adverse side effects.

Similar to conventional dairy products, routine in-process analysis in lactose-free dairy production is often carried out using infrared spectroscopy, due to its rapid reporting. Additionally, the wavelengths that are used to identify dairy components are well documented, allowing for easier determination of fats, proteins and sugars.

Fourier transform infrared (FTIR) technologies are the most popular of the infrared spectroscopy instruments used in dairy analysis. As cream is still very liquid, even at high solid levels, FTIR can still effectively be used for the determination and analysis of its components. For products with a higher percentage of solids—usually above 20%—near-infrared (NIR) spectroscopy can provide much better results. Due to its ability to penetrate pathlengths up to 20 mm, this method is more suitable for the analysis of cheeses and yogurts. For low-lactose products in particular, FTIR technology is integral to production, as it can also be used to monitor the breakdown of lactose.

Finger on the Pulse

For some consumers, dairy products must be avoided altogether. Contrary to intolerances that only affect the digestive system, allergies affect the immune system of the body. This means that allergenic ingredients, such as milk or dairy, are treated as foreign invaders and can result in severe adverse reactions, such as anaphylactic shock, when ingested.

From 2012 to 2017, U.S. sales of plant-based milk steadily rose by 61%. With this increasing demand and the need to provide alternatives for those with allergies, it has never been a more important time to get plant-based milk processing right the first time. Although the quantification of fat, protein and sugar content is still important in these products, they pose different challenges to processors.

In order to mimic traditional dairy products, plant-based milk is often formulated with additional ingredients or as a blend of two plant milks. Sunflower or safflower oil can be added to increase viscosity and cane syrup or salt may be added to enhance flavor. All of these can affect the stability of the milk, so stabilizers or acidity regulators may also be present. Additionally, no plant milk is the same. Coconut milk is very high in fat content but very low in protein and sugar; on the other hand, oat milk is naturally very high in carbohydrates. This not only makes them suitable for different uses, but also means they require different analytical procedures to quantify their components.

Although many FTIR and NIR instruments can be applied to plant-based milk in the same way as dairy milk, the constantly evolving formulation differences pose issues to processors. For example, the way that protein is determined in dairy milk will vary from the way protein is determined in almond milk. Both will follow a method of quantifying the nitrogen content but must be multiplied by a different factor. To help overcome these challenges, many companies have started to develop plant-based milk calibrations that can be used in conjunction with existing infrared instruments. Currently, universal calibrations exist to determine the protein, fat, solids, and sugar content of novel products. With more research and data, it’s likely in the future these will be expanded to generate calibrations that are specific to soy, almond and oat milk.

Even with exciting advancements in analytical testing for plant-based milk, the downtime for analysis is still a lot higher than traditional dairy. This is due to the increased solid content of plant-based milk. Many are often a suspension of solid particles in an aqueous solution, as opposed to dairy milk, which is a suspension of fat globules in aqueous solution. This means processors need to factor in additional centrifuge and cleaning steps to ensure results are as accurate and repeatable as possible.

In addition to the FTIR and NIR instruments used for traditional dairy testing, plant-based milk can also benefit from the implementation of diode array (DA) NIR instruments into existing workflows. With the ability to be placed at- and on-line, DA instruments can provide continual reporting for the constituent elements of plant-based milk as they move through the processing facility. These instruments can also produce results in about six seconds, compared to the 30 seconds of regular IR instruments, so are of great importance for rapid reporting of multiple tests across a day.

Keeping It Simple

Although the consumption of dairy-free products is on the rise, lots of plant-based milk are also made from other allergenic foods, such as soy, almonds and peanuts. Therefore, having low-lactose alternatives on the market is still valuable to provide consumers with a range of suitable options.

To do this, dairy processors and new plant-based milk processors need access to instruments that rapidly and efficiently produce accurate compositional analysis. For dairy processors who have recently started creating low-lactose or dairy-free milk alternatives, it is important that their instrumentation is flexible and used for the analysis of all their product outputs.

Looking towards the future, it’s likely both dairy products and their plant-based counterparts will have a place in consumers’ diets. Although there is some divide on which of these products is better—both for the environment and in terms of health—one thing that will become increasingly more important is the attitude towards the labeling of these products. Clean labels and transparency on where products are coming from, and the relative fat, protein and sugar content of foods, are important to many consumers. Yet another reason why effective testing and analytical solutions need to be available to food processors.

Allergens

Key Trends Reinforce Food Allergen Testing Market Across North America

By Saloni Walimbe
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Allergens

The food allergen testing industry has garnered considerable traction across North America, especially due to the high volume of processed food and beverages consumed daily. Allergens are becoming a significant cause for concern in the present food processing industry worldwide. Food allergies, which refer to abnormal reactions or hypersensitivity produced by the body’s immune system, are considered a major food safety challenge in recent years and are placing an immense burden on both personal and public health.

In 2019, the most common reason behind recalls issued by the USDA FSIS and the FDA was undeclared allergens. In light of this growing pressure, food producers are taking various steps to ensure complete transparency regarding the presence of allergenic ingredients, as well as to mitigate risk from, or possibly even prevent contact with, unintended allergens. One of these steps is food allergen testing.

Allergen detection tests are a key aspect of allergen management systems in food processing plants and are executed at nearly every step of the process. These tests can be carried out on work surfaces, as well as the products, to detect any cross contamination or allergen presence, and to test the effectiveness of a food processing unit’s cleaning measures.
There has been a surge in awareness among consumers about food allergies and tackling the risk of illnesses that may arise from consuming any ingredient. One of the key reasons for a higher awareness is efforts to educate the public. In Canada, for example, May has been designated “Food Allergy Awareness Month”. It is estimated that more than 3 million people in Canada are affected by food allergies.

The size of the global food allergen testing market is anticipated to gain significant momentum over the coming years, with consistent expansion of the dairy, processed food and confectionary segments.

Understanding the Prevailing Trends in Food Allergen Testing Industry

Food allergies risen nearly 50% in the last 10 years, with a staggering 700% increase observed in hospitalizations due to anaphylaxis. Studies also suggest that food allergies are a growing health concern, with more than 250 million people worldwide estimated to be affected.

Although more than 170 foods have been identified as causing food allergies in sensitive consumers, the USDA and the FDA have identified eight major allergenic foods, based on the 2004 FALCPA (the Food Allergen Labeling and Consumer Protection Act). These include eggs, milk, shellfish, fish, peanuts, tree nuts, soybean, and wheat, which are responsible for 90% of allergic reactions caused due to food consumption. In April 2021, the FASTER (Food Allergy Safety, Treatment, Education, and Research) Act was signed into law, which categorized sesame as the ninth major food allergen.

This ever-increasing prevalence of allergy-inducing foods has presented lucrative opportunities for the food allergen testing industry in recent years since food processing business operators are placing a strong emphasis on ensuring transparency in their products’ ingredient lists. By testing for allergens in food products, organizations can accurately mention each ingredient, and thereby allow people with specific food allergies to avoid consuming them.

Several allergen detection methods are used in the food processing industry, including mass spectrometry, DNA-based polymerase chain reaction (PCR) as well as ELISA (enzyme-linked immunosorbent assay), to name a few. The FDA, for instance, created a food allergen detection assay, called xMAP, designed to simultaneously identify 16 allergens, including sesame, within a single analysis, along with the ability to expand for the targeting of additional food allergens. Such industry advancements are improving the monitoring process for undeclared allergen presence in the food supply chain and enabling timely intervention upon detection.

Furthermore, initiatives, such as the Voluntary Incidental Trace Allergen Labelling (VITAL), created and managed by the Allergen Bureau, are also shedding light on the importance of allergen testing in food production. The VITAL program is designed to support allergen management with the help of a scientific process for risk assessment, in order to comply with food safety systems like the HACCP (Hazard Analysis and Critical Control Point), with allergen analysis playing a key role in its application.

ELISA Gains Prominence as Ideal Tool for Food Allergen Testing

In life sciences, the detection and quantification of various antibodies or antigens in a cost-effective and timely manner is of utmost importance. Detection of select protein expression on a cell surface, identification of immune responses in individuals, or execution of quality control testing—all these assessments require a dedicated tool.

ELISA is one such tool proving to be instrumental for both diagnostics as well as research). Described as an immunological assay, ELISA is used commonly for the measurement of antibodies or antigens in biological samples, including glycoproteins or proteins.

While its utility continues to grow, ELISA-based testing has historically demonstrated excellent sensitivity in food allergen testing applications, in some cases down to ppm (parts per million). It has a distinct advantage over other allergen detection methods like PCR, owing to the ability to adapt to certain foods like milk and oils, where its counterparts tend to struggle. The FDA is one of the major promoters of ELISA for allergen testing in food production, involving the testing of food samples using two different ELISA kits, prior to confirming results.

Many major entities are also taking heed of the growing interest in the use of ELISA for food allergen diagnostics. A notable example of this is laboratory analyses test kits and systems supplier, Eurofins, which introduced its SENSISpec Soy Total protein ELISA kit in September 2020. The enzyme immunoassay, designed for quantitative identification of soy protein in swab and food samples, has been developed by Eurofins Immunolab to measure residues of processed protein in various food products, including instant meals, chocolate, baby food, ice cream, cereals, sausage, and cookies, among others.

In essence, food allergens continue to prevail as high-risk factors for the food production industry. Unlike other pathogens like bacteria, allergenic proteins are heat resistant and stable, and cannot easily be removed once present in the food supply chain. In this situation, diagnostic allergen testing, complete segregation of allergenic substances, and accurate food allergen labeling are emerging as the ideal courses of action for allergen management in the modern food production ecosystem, with advanced technologies like molecular-based food allergy diagnostics expected to take up a prominent role over the years ahead.

Sesame Seeds

President Biden Signs FASTER Act, Requiring Sesame Labeling on Food Packaging

By Food Safety Tech Staff
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Sesame Seeds

Last week President Biden signed the Food Allergy Safety, Treatment, Education, and Research Act of 2021 (FASTER Act; H.R. 1202) into law. The bill is a significant victory for food allergy advocates, because it adds sesame to the list of allergens that must be labeled on food packaging. HHS must also report certain information related to food allergy research and data collection.

Sesame is the ninth food allergen that must be labeled on food packaging. According to FARE (Food Allergy & Research Education), a non-government food allergy advocacy group, about 1.6 million Americans are allergic to sesame. “Sesame is often used when a label reads ‘natural flavors’ or ‘natural spices’, adding another layer of difficulty when consumers review product labels at their local grocery store,” according to a FARE press release about the bill. “This marks the first time since 2004 that a new allergen has been added to the Food Allergen Labeling and Consumer Protection Act (FALCPA).”

Packages must include the updated labeling by January 2023.

Susanne Kuehne, Decernis
Food Fraud Quick Bites

Finding the Root Cause for Starch Fraud

By Susanne Kuehne
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Susanne Kuehne, Decernis
Food fraud, cassava starch
Find records of fraud such as those discussed in this column and more in the Food Fraud Database.
Image credit: Susanne Kuehne

Due to its lower cost, cassava starch is a common adulterant in higher priced starches, such as for potato and wheat. Tests with droplet digital polymerase chain reaction ddPCR in China uncovered that over 30% of sweet potato starch samples, 25% of cornstarch samples and 40% of potato starch samples were adulterated with cassava starch. Besides the economic impact, this kind of fraud also poses a risk to consumers allergic to cassava.

Resource

  1. Chen, J., et. al. (February 26, 2020). “Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR”. PLOS One.

The Importance Of Cleanrooms in the Food Industry

By Steve Gonzalez
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The health and well being of millions depends on manufacturers’ and packagers’ ability to maintain a safe and sterile environment during production. This is why professionals in this sector are held to much stricter standards than other industries. With such high expectations from consumers and regulatory bodies, a growing number of food companies are opting the use cleanrooms.

Cleanrooms are sealed off from the rest of a laboratory or production facility. Through stringent ventilation and filtering systems, they protect against contaminants that might be found in an unrestricted environment. Mold, mildew, dust and bacteria are sifted from the air before they can enter the space.

Personnel who work in a cleanroom are required to adhere to rigorous precautions, including clean suits and masks. These rooms also closely monitor temperature and humidity to ensure the optimal climate.

Cleanrooms can be found in numerous applications throughout the food industry. Specifically, they are used in meat and dairy facilities, as well as in the processing of foods that need to be gluten and lactose free. By creating the cleanest possible environment for production, companies can offer their customers peace of mind. Not only can they keep their products free from contamination, but they can extend shelf life and increase efficiency.

If you want to learn more about cleanrooms and their classifications, take a look at the accompanying infographic. It details the essential requirements and standards for facilities in the food industry and beyond.

Cleanroom requirements, food safety
Infographic courtesy of Technical Safety Services
Michael Bartholomeusz, TruTag
In the Food Lab

Intelligent Imaging and the Future of Food Safety

By Michael Bartholomeusz, Ph.D.
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Michael Bartholomeusz, TruTag

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

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.

Mechanical Damage

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.

Chocolate

Chocolate and Big Data: The Recipe for Food Safety Is Changing

By Steven Sklare
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Chocolate

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:

  • Allergens: 51.60%
  • Biological: 16.49%
  • Foreign bodies: 13.83%
  • Chemical: 7.45%
  • Fraud: 6.38%
  • 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.

Cocoa incidents, FOODAKAI
Graph from Case Study: Chocolate Products: lessons learned from global food safety and fraud data and the guidance it can provide to the food industry,
an industry report from FOODAKAI. Used with permission.

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.

  • Chemical: 73.46%
  • Biological: 16.49%
  • Organoleptic aspects: 5.93%
  • Other Hazards: 4.38%
  • Fraud: 2.32%
  • Foreign bodies: 2.06%
  • Food additives and flavorings: .77%
  • Allergens: .52%
  • 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.

Africa South America Asia
1 Organophosphate 2,4-dinitrophenol (DNP) 2,4-dinitrophenol (DNP)
2 Molds Pyrethroid Poor or insufficient controls
3 Neonicotinoid Aflatoxin Aflatoxin
4 Pyrethroid Cadmium Spoilage
5 Organochlorine Anilinopyrimidine Salmonella
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.

References

  1. Discovering Chocolate. The Great Chocolate Discovery. Cadbury website. Retrieved from https://www.cadbury.com.au/About-Chocolate/Discovering-Chocolate.aspx.
  2. Chocolate Industry Analysis 2020 – Cost & Trends. Retrieved from https://www.franchisehelp.com/industry-reports/chocolate-industry-analysis-2020-cost-trends/.
Sasan Amini, Clear Labs

2020 Expectations: More Artificial Intelligence and Machine Learning, Technology Advances in Food Safety Testing

By Maria Fontanazza
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Sasan Amini, Clear Labs

2018 and 2019 were the years of the “blockchain buzz”. As we enter the new decade, we can expect a stronger focus on how technology and data advances will generate more actionable use for the food industry. Food Safety Tech has highlighted many perspectives from subject matter experts in the industry, and 2020 will be no different. Our first Q&A of the year features Sasan Amini, CEO of Clear Labs, as he shares his thoughts on tech improvements and the continued rise consumer expectations for transparency.

Food Safety Tech: As we look to the year ahead, where do you see artificial intelligence, machine learning and blockchain advancing in the food industry?

Sasan Amini: AI, ML, and blockchain are making headway in the food industry through advances in supply chain management, food sorting and anomaly detection, and tracing the origin of foodborne outbreaks. On the regulatory side, FDA’s focus on its New Era of Smarter Food Safety will most likely catalyze the adoption of the above mentioned technologies. On the private side, a few of the companies leading the charge on these advancements are IBM and Google, working in partnership with food manufacturers and retailers across the world.

Along those same lines, another area that we expect to grow is the use of AI and ML in tandem with robotics—and the value of new troves of data that they collect, analyze and distribute. For example, robotics for the use of environmental monitoring of potential contaminants, sorting techniques and sterilization are valuable because they ensure that end products have been through thorough testing—and they give us even more information about the lifecycle of that food than ever before.

At the end of the day, data is only valuable when you can transform it into actionable insights in real-time with real-world applications, and we expect to see more and more of this type of data usage in the year ahead.

FST: Where do you think food safety testing technologies will stand out? What advancements can the industry expect?

Amini: In 2020, technology is going to begin to connect itself along the entire supply chain, bringing together disparate pieces and equipping supply chain professionals with action-oriented data. From testing advances that improve speed, accuracy and depth of information to modular software solutions to promote transparency, the food safety industry is finally finding its footing in a data-driven sea of technological and regulatory advances.

Right now, legacy testing solutions are limited in their ability to lead food safety and quality professionals to the source of problems, providing insights on tracking recurring issues, hence having a faster response time, and being able to anticipate problems before they occur based on a more data heavy and objective risk assessment tools. This leaves the industry in a reactive position for managing and controlling their pathogen problems.

Availability of higher resolution food safety technologies that provide deeper and more accurate information and puts them in context for food safety and quality professionals provides the food industry a unique opportunity to resolve the incidents in a timely fashion with higher rigour and confidence. This is very in-line with the “Smarter Tools and Approaches” that FDA described in their new approach to food safety.

FST: How are evolving consumer preferences changing how food companies must do business from a strategic as well as transparency perspective?

Amini: Consumers are continuing to get savvier about what’s in their food and where it comes from. Research suggests that about one in five U.S. adults believe they are food allergic, while only 1 in 20 are estimated to have physician-diagnosed food allergies. This discrepancy is important for food companies to consider when making decisions about transparency into their products. Although the research on food allergies continues to evolve, what’s important to note today is that consumers want to know the details. Radical transparency can be a differentiator in a competitive market, especially for consumers looking for answers to improve their health and nutrition.

Consumers are also increasingly interested in personalization, due in part to the rise in new digital health and testing companies looking to deliver on the promise of personalized nutrition and wellness. Again, more transparency will be key.

FST: Additional comments are welcome.

Amini: Looking ahead, we expect that smaller, multi-use, and hyper-efficient tools with reduced physical footprints will gain market share. NGS is a great example of this, as it allows any lab to gather millions of data points about a single sample without needing to run it multiple times. It moves beyond the binary yes-no response of traditional testing, and lets you get much more done, with far less. Such wealth of information not only increases the confidence about the result, but can also be mined to generate more actionable insights for interventions and root cause analysis.

This “multi-tool” will be driven by a combination of advanced software, robotics, and testing capabilities, creating a food safety system that is entirely connected, driven by data, and powerfully accurate.