Tag Archives: Testing

Crop spraying, Ellutia

From Farm to Fork: The Importance of Nitrosamine Testing in Food Safety

By Andrew James
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Crop spraying, Ellutia

N-nitroso compounds (NOCs), or nitrosamines, have once again made headline news as their occurrence in some pharmaceuticals has led to high profile product recalls in the United States.1 Nitrosamines can be carcinogenic and genotoxic and, in the food industry, can compromise a food product’s quality and safety. One nitrosamine in particular, N-nitrosodimethylamine (NDMA), is a highly potent carcinogen, traces of which are commonly detected in foods and may be used as an indicator compound for the presence of nitrosamines.2

NOCs can potentially make their way into the food chain in a number of ways, including (but not limited to): Via the crop protection products used to maximize agricultural yields; via the sodium and/or potassium salt added to preserve certain meats from bacterial contamination; as a result of the direct-fire drying process in certain foods; and via consumption of nitrates in the diet (present in many vegetables due to natural mineral deposits in the soil), which react with bacteria and acids in the stomach to form nitrosamines.3

The crop protection and food manufacturing industries are focused on ensuring that levels of nitrosamines present in foods are minimal and safe. Detection technology for quantitating the amount of nitrosamines (ppm levels) in a sample had not advanced in nearly 40 years—until recently. Now, a thermal energy analyzer (TEA) —a sensitive and specific detector—is being relied on to provide fast and sensitive analysis for players throughout the food supply chain.

Regulatory Landscape

Both NDMA and the nitrosamine N-nitrososodiethylamine (NDEA) have been classified by national and international regulatory authorities as ‘probable human carcinogens’.3 NDMA in particular is by far the most commonly encountered member of this group of compounds.7

In the United States there are limits for NDMA or total nitrosamines in bacon, barley malt, ham and malt beverages, yet there are currently no regulatory limits for N-nitroso compounds (NOC) in foods in the EU.7

Developers of crop protection products are required to verify the absence of nitrosamines or quantify the amount at ppm levels to ensure they are within the accepted guidelines.

Crop Protection

The presence of nitrosamines must be traced and risk-managed along the food’s journey from farm to fork. The issue affects testing from the very beginning – particularly at the crop protection stage, which is one of the most highly regulated industries in the world. Without crop protection, food and drink expenditures could increase by up to £70 million per year and 40% of the world’s food would not exist.7

Development of a new crop protection product (herbicide, fungicide, insecticide or seed treatment) involves several steps: Discovery and formulation of the product, trials and field development, toxicology, environmental impacts and final registration. New product registration requires demonstration of safety for all aspects of the environment, the workers, the crops that are being protected and the food that is consumed. This involves comprehensive risk assessments being carried out, based on data from numerous safety studies and an understanding of Good Agricultural Practice (GAP).

One global producer of agrochemicals uses a custom version of the TEA to verify the absence of nitrosamines or quantitate the amount of nitrosamines (ppm levels) in its active ingredients. The LC-TEA enables high selectivity for nitro, nitroso and nitrogen (when operating in nitrogen mode), which allows only the compounds of interest to be seen. Additionally, it provides very high sensitivity (<2pg N/sec Signal to Noise 3:1), meaning it is able to detect compounds of interest at extremely low levels. To gain this high sensitivity and specificity, it relies on a selective thermal cleavage of N-NO bond and detection of the liberated NO radical by the chemiluminescent signal generated by its reaction with ozone.

The customized system also uses a different interface with a furnace, rather than the standard pyrolyser, to allow for the additional energy required and larger diameter tubing for working with a liquid sample rather than gas.

The system allows a company to run five to six times more samples with increased automation. As a direct result, significant productivity gains, reduced maintenance costs and more accurate results can be realized.

Food Analysis

Since nitrite was introduced in food preservation in the 1960s, its safety has been debated. The debate continues today, largely because of the benefits of nitrite in food products, particularly processed meats.6 In pork products, such as bacon and cured ham, nitrite is mostly present in the sodium and/or potassium salt added to preserve the meat from bacterial contamination. Although the meat curing process was designed to support preservation without refrigeration, a number of other benefits, such as enhancing color and taste, have since been recognized.

Analytical methods for the determination of N-nitrosamines in foods can differ between volatile and non-volatile compounds. Following extraction, volatile N-nitrosamines can be readily separated by GC using a capillary column and then detected by a TEA detector. The introduction of the TEA offered a new way to determine nitrosamine levels at a time when GC-MS could do so only with difficulty.

To identify and determine constituent amounts of NOCs in foods formed as a direct result of manufacturing and processing, the Food Standards Agency (FSA) approached Premier Analytical Services (PAS) to develop a screening method to identify and determine constituent amounts of NOCs in foods formed as a direct result of manufacturing and processing.

A rapid and selective apparent total nitrosamine content (ATNC) food screening method has been developed with a TEA. This has also been validated for the known dietary NOCs of concern. This method, however, is reliant on semi-selective chemical denitrosation reactions and can give false positives. The results can only be considered as a potential indicator rather than definitive proof of NOC presence.

In tests, approximately half (36 out of 63) samples returned a positive ATNC result. Further analysis of these samples by GC-MS/MS detected volatile nitrosamine contamination in two of 25 samples.

A key role of the TEA in this study was to validate the alternative analytical method of GC-MS/MS. After validation of the technique by TEA, GC-MS/MS has been proven to be highly sensitive and selective for this type of testing.

The Future of Nitrosamine Testing

Many countries have published data showing that toxicological risk from preformed NOCs was no longer considered an area for concern. Possible risks may come from the unintentional addition or contamination of foods with NOCs precursors such as nitrite and from endogenous formation of NOCs and more research is being done in this area.

Research and innovation are the foundations of a competitive food industry. Research in the plant protection industry is driven by farming and the food chain’s demand for greater efficiency and safer products. Because the amount of nitrosamines in food that results in health effects in humans is still unknown, there is scope for research into the chemical formation and transportation of nitrosamines, their occurrence and their impact on our health. Newer chromatographic techniques are only just being applied in this area and could greatly benefit the quantification of nitrosamines. It is essential that these new approaches to quality and validation are applied throughout the food chain.

References

  1. Christensen, J. (2020). More popular heartburn medications recalled due to impurity. CNN.
  2. Hamlet, C, Liang, L. (2017). An investigation to establish the types and levels of N-nitroso compounds (NOC) in UK consumed foods. Premier Analytical Services, 1-79.
  3. Woodcock, J. (2019). Statement alerting patients and health care professionals of NDMA found in samples of ranitidine. Center for Drug Evaluation and Research.
  4. Scanlan, RA. (1983). Formation and occurrence of nitrosamines in food. Cancer res, 43(5) 2435-2440.
  5.  Dowden, A. (2019). The truth about nitrates in your food. BBC Future.
  6.  Park, E. (2015). Distribution of Seven N-nitrosamines in Food. Toxicological research, 31(3) 279-288, doi: 10.5487/TR.2015.31.3.279.
  7.  Crews, C. (2019). The determination of N-nitrosamines in food. Quality Assurance and Safety of Crops & Foods, 1-11, doi: 10.1111/j.1757-837X.2010.00049.x
  8. (1989) Toxicological profile for n-Nitrosodimethylamine., Agency for Toxic substances and disease registry.
  9. Rickard, S. (2010). The value of crop protection, Crop Protection Association.
Food Labs Conference

Food Labs / Cannabis Labs 2020 Agenda Announced

By Food Safety Tech Staff
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Food Labs Conference

The agenda for the 2020 Food Labs / Cannabis Labs conference has been announced. The event, which will address regulatory, compliance and risk management issues that companies face in the area of testing and food laboratory management, is scheduled to take place on June 3–4 in Rockville, MD.

Some agenda highlights include a special morning session on June 3 that discusses the proposed FSMA rule on lab accreditation: “FSMA and the Impact on Laboratories and Laboratory Data Users” and “FSMA Proposed Rule on Laboratory Accreditation: What it says and what it should say” presented by Reinaldo Figueiredo of ANSI and Robin Stombler of Auburn Health Strategies, respectively. FDA has also been invited to speak on the proposed rule. Sessions will also cover the role of labs as it relates to pathogens, with presentations from Benjamin Katchman, Ph.D. (PathogenDx) about a novel DNA microarray assay used for detecting and speciating multiple Listeria species and Dave Evanson (Merieux Nutrisciences) on pathogen detection and control. The full agenda is listed on the Food Labs / Cannabis Labs website.

The early bird discount of $395 expires on March 31.

Innovative Publishing Company, Inc., the organizer of the conference, is fully taking into considerations the travel concerns related to the coronavirus. Should any
disruption that may prevent the production of this live event at its physical location in Rockville, MD due to COVID-19, all sessions will be converted to a virtual conference on the already planned dates. More information is available on the event website.

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.

Benjamin Katchman, PathogenDx
In the Food Lab

Revolutionary Rapid Testing for Listeria Monocytogenes and Salmonella

By Benjamin A. Katchman, Ph.D., Michael E. Hogan, Ph.D., Nathan Libbey, Patrick M. Bird
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Benjamin Katchman, PathogenDx

The Golden Age of Bacteriology: Discovering the Unknown in a Farm-to-Market Food Supply.

The last quarter of the 19th Century was both horrific and exciting. The world had just emerged from four decades of epidemic in cholera, typhoid fever and other enteric diseases for which no cause was known. Thus, the great scientific minds of Europe sought to find understanding. Robert Koch integrated Pasteur’s Germ Theory in 1861 with the high technology of the day: Mathematical optics and the first industrialized compound microscopes (Siebert, Leiss, 1877), heterocycle chemistry, high-purity solvents (i.e., formaldehyde), availability of engineered glass suitable as microscope slides and precision-molded parts such as tubes and plates in 1877, and industrialized agar production from seaweed in Japan in 1860. The enduring fruit of Koch’s technology integration tour de force is well known: Dye staining of bacteria for sub-micron microscopy, the invention of 13 cm x 1 cm culture tubes and the invention of the “Petri” dish coupled to agar-enriched culture media. Those technologies not only launched “The Golden Age of Bacteriology” but also guided the entire field of analytical microbiology for two lifetimes, becoming bedrock of 20th Century food safety regulation (the Federal Food, Drug and Cosmetic Act in 1938) and well into the 21st century with FSMA.

Learn more about technologies in food safety testing at the Food Labs / Cannabis Labs Conference | June 2–4, 2020 | Register now!Blockchain Microbiology: Managing the Known in an International Food Supply Chain.

If Koch were to reappear in 2020 and were presented with a manual of technical microbiology, he would have little difficulty recognizing the current practice of cell fixation, staining and microscopy, or the SOPs associated with fluid phase enrichment culture and agar plate culture on glass dishes (still named after his lab assistant). The point to be made is that the analytical plate culture technology developed by Koch was game changing then, in the “farm-to-market” supply chain in Koch’s hometown of Berlin. But today, plate culture still takes about 24 to 72 hours for broad class indicator identification and 48 to 96 hours for limited species level identification of common pathogens. In 1880, life was slow and that much time was needed to travel by train from Paris to Berlin. In 2020, that is the time needed to ship food to Berlin from any place on earth. While more rapid tests have been developed such as the ATP assay, they lack the speciation and analytical confidence necessary to provide actionable information to food safety professionals.

It can be argued that leading up to 2020, there has been an significant paradigm shift in the understanding of microbiology (genetics, systems based understanding of microbial function), which can now be coupled to new Third Industrial Age technologies, to make the 2020 international food supply chain safer.

We Are Not in 1880 Anymore: The Time has Come to Move Food Safety Testing into the 21st Century.

Each year, there are more than 48 million illnesses in the United States due to contaminated food.1 These illnesses place a heavy burden on consumers, food manufacturers, healthcare, and other ancillary parties, resulting in more than $75 billion in cost for the United States alone.2 This figure, while seemingly staggering, may increase in future years as reporting continues to increase. For Salmonella related illnesses alone, an estimated 97% of cases go unreported and Listeria monocytogenes is estimated to cause about 1,600 illnesses each year in the United States with more than 1,500 related hospitalizations and 260 related deaths.1,3 As reporting increases, food producers and regulatory bodies will feel an increased need to surveil all aspects of food production, from soil and air, to final product and packaging. The current standards for pathogenic agriculture and environmental testing, culture-based methods, qPCR and ATP assays are not able to meet the rapid, multiplexed and specificity required to meet the current and future demands of the industry.

At the DNA level, single cell level by PCR, high throughput sequencing, and microarrays provide the ability to identify multiple microbes in less than 24 hours with high levels of sensitivity and specificity (see Figure 1). With unique sample prep methods that obviate enrichment, DNA extraction and purification, these technologies will continue to rapidly reduce total test turnaround times into the single digit hours while simultaneously reducing the costs per test within the economics window of the food safety testing world. There are still growing pains as the industry begins to accept these new molecular approaches to microbiology such as advanced training, novel technology and integrated software analysis.

It is easy to envision that the digital data obtained from DNA-based microbial testing could become the next generation gold standard as a “system parameter” to the food supply chain. Imagine for instance that at time of shipping of a container, a data vector would be produced (i.e., time stamp out, location out, invoice, Listeria Speciation and/or Serovar discrimination, Salmonella Speciation and/or Serovar discrimination, refer toFigure 1) where the added microbial data would be treated as another important digital attribute of the load. Though it may seem far-fetched, such early prototyping through the CDC and USDA has already begun at sites in the U.S. trucking industry, based on DNA microarray and sequencing based microbial testing.

Given that “Third Industrial Revolution” technology can now be used to make microbial detection fast, digital, internet enabled and culture free, we argue here that molecular testing of the food chain (DNA or protein based) should, as soon as possible, be developed and validated to replace culture based analysis.

Broad Microbial Detection
Current microbiological diagnostic technology is only able to test for broad species of family identification of different pathogens. New and emerging molecular diagnostic technology offers a highly multiplexed, rapid, sensitive and specific platforms at increasingly affordable prices. Graphic courtesy of PathogenDx.

References.

  1. Scallan, E., Hoekstra, R. M., Angulo, F. J., Tauxe, R. V., Widdowson, M. A., Roy, S. L., … Griffin, P. M. (2011). Foodborne illness acquired in the United States–major pathogens. Emerging infectious diseases, 17(1), 7–15. doi:10.3201/eid1701.p11101
  2. Scharff, Robert. (2012). Economic Burden from Health Losses Due to Foodborne Illness in the United States. Journal of food protection. 75. 123-31. 10.4315/0362-028X.JFP-11-058.
  3. Mead, P. S., Slutsker, L., Dietz, V., McCaig, L. F., Bresee, J. S., Shapiro, C., … Tauxe, R. V. (1999). Food-related illness and death in the United States. Emerging infectious diseases, 5(5), 607–625. doi:10.3201/eid0505.990502
Susanne Kuehne, Decernis
Food Fraud Quick Bites

Caught in the Whiskey Web

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

When we talk about the identification of fraudulent foods and beverages, many elaborate methods are available in analytical chemistry and food labs. The method of using “whiskey webs” is quite unusual in its simplicity; it is based on the unique residue left behind by each beverage after evaporation. American Whiskey is matured in new charred oak barrels that transfer a number of water-insoluble components into the final product, allowing each whiskey to leave behind its own unique “fingerprint”.

Resource

  1. Wilson, C. (October 29, 2019). “American whiskey leaves behind a web-like ‘fingerprint’, finds study”. Decanter.

 

Michele Pfannenstiel, Dirigo Food Safety
FST Soapbox

Quality Assurance and Food Safety in Cannabis-Infused Products

By Michele Pfannenstiel, DVM
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Michele Pfannenstiel, Dirigo Food Safety

The legal cannabis-infused products industry is growing with impressive and predictable rapidity. But because the rollout of new regulations occurs in an awkward and piecemeal fashion, with stark differences from one state to another, and sometimes even one county to another, uncertainty reigns.1 Many entrepreneurs are diving headlong into the nascent industry, hoping to take advantage of an uncertain regulatory environment where government audits and inspections are rare. These business owners will see quality assurance and product safety as burdens—costs to be avoided to the greatest extent possible.

I have seen this time and time again, even in the comparatively well-regulated food industry, and it is always a mistake.

If you find yourself thinking about quality assurance or food safety as a prohibitive cost, annoyance or distraction, I encourage you to change your thinking on this issue. The most successful businesses realize that product safety and quality assurance are inextricably linked with profitability. They are best thought of not as distractions, but as critical elements of an efficient and optimized process. Proper QA and safety are not costs, they are value.

Food safety and quality assurance should be seen as important elements of the process that you undertake to enforce the high standards and consistency that will win you repeat customers. The fact that they guard against costly recalls or satisfy meddlesome auditors is only a bonus. Realizing this will make your business smarter, faster and more profitable.

Learn more about the science, technology, regulatory compliance and quality management issues surrounding cannabis at the Food Labs / Cannabis Labs Conference | June 2–4, 2020If today you cannot clearly communicate your product standards to your employees and to your customers, then you have some work to do. That’s because quality assurance always begins with precise product specifications. (A good definition of “quality” is “conformance to specifications.”) How can you assess quality if you don’t have a definitive standard with which to evaluate it? My consulting firm works with food businesses both small and large, and this is where we begin every relationship. You might be surprised how often even a well-established business has a difficult time naming and describing every one of its products, let alone articulating objective standards for them.

This may be doubly difficult for fledgling businesses in the cannabis world. Because the market is so new, there are fewer agreed-upon standards to fall back on.

When we help businesses create specifications, we always look at the relevant regulations while keeping in mind customer expectations. In cannabis, the regulations just aren’t as comprehensive as they are for conventional food and agriculture. Laws and guidelines are still in flux, and different third-party standards are still competing for market dominance. Different states have entirely different standards, and don’t even agree, for example, whether cannabis edibles should be considered pharmaceuticals or food. To some extent, it’s the wild west of regulation, and as long as the federal government remains reluctant to impose national guidelines, it’s likely to remain so.

The wild west may be a good place for the unscrupulous, but it’s not good for business owners that care about the health of their customers and the long-term health of their brand. Don’t take advantage of confusing quality and safety standards by doing the least possible to get by. At some point there will be a scandal in this country when a novel cannabis product makes dozens of customers sick, or worse. You don’t want it to be yours.

With cannabis-infused products, there is a unique additional factor at play: The strength of THC and other psychoactive compounds. Again, there are few agreed-upon standards for potency testing, and relatively little oversight of the laboratories themselves. This allows labs to get sloppy, and even creates an incentive for them to return inflated THC counts; at the very least, results may hugely differ from one lab to another even for identical products.2 Some labs are ISO 17025 accredited, and some are not. Using an unaccredited laboratory may prevent your efforts to create consistent and homogeneous products.

Even in comparatively well-regulated states, such as Colorado, it is ultimately your responsibility to create products that are safe and consistent. And in the states where the politicians haven’t even figured out which department is regulating cannabis products, your standards should be tougher than whatever is officially required.

And so we look to the more established world of conventional food and agriculture as a guide for the best practices in the cannabis industry.

Hazards

The most constructive way to look at food safety, and the way your (eventual) auditors and regulators will view it, is to look at your product and process from the perspective of the potential hazards.

Some day, when regulation finally gets sorted out, you are likely to be asked to implement a Hazard Analysis and Critical Control Points (HACCP) safety system. HACCP framework recognizes three broad categories of hazards:

  • Physical hazards: Foreign material that is large enough to cause harm, such as glass or metal fragments.
  • Chemical hazards: Pesticides and herbicides, heavy metals, solvents and cleaning solutions.
  • Biological hazards: The pathogens that cause foodborne illness in your customers, such as E. coli, and other biological hazards, such as mycotoxins from molds.

All of these hazards are highly relevant to cannabis-infused product businesses.

The HACCP framework asks us to consider what steps in our process offer us the chance to definitively and objectively eliminate the risk of relevant hazards. In a cannabis cookie, for example, this might be a cooking step, a baking process that kills the Salmonella that could be lurking in your flour, eggs, chocolate or (just as likely!) the cannabis extracts themselves.

A good HACCP system is merely the capstone resting atop a larger foundational system of safety programs, including standard operating procedures, good manufacturing practices, and good agricultural practices. It’s important to use these agreed-upon practices and procedures in your own facility and to ensure that your suppliers and shippers are doing the same. Does your cultivator have a culture of safety and professionalism? Do they understand their own risks of hazards?

HACCP offers a rigorous perspective with which to look at a process, and to examine all of the places where it can go wrong. The safety system ultimately holds everything together because of its emphasis on scrupulous documentation. Every important step is written down, every time, and is always double-checked by a supervisor. It sounds like a lot of paperwork, but it is better viewed as an opportunity to enforce consistency and precision.

When you thoroughly document your process you’ll create a safer product, run a more efficient business, and make more money.

References

  1. Rough, L. (2016, March 4). Leafly’s State-by-State Guide to Cannabis Regulations. Retrieved from https://www.leafly.com/news/industry/leaflys-state-by-state-guide-to-cannabis-testing-regulations
  2. Jikomes, N. & Zoorob, M. (2018, March 14). The Cannabinoid Content of Legal Cannabis in Washington State Varies Systematically Across Testing Facilities and Popular Consumer Products. Retrieved from https://www.nature.com/articles/s41598-018-22755-2

Food Labs Conference Announced for Spring 2020

By Food Safety Tech Staff
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— UPDATE — March 9, 2020 – IPC and the Food Labs/Cannabis Labs Conference want to reassure you, that in case of any disruption that may prevent the production of this live event at its physical location in Rockville, MD due to COVID-19, all sessions will be converted to a virtual conference on the already planned dates. Please note that if you initially register as a virtual participant (meaning you have no intentions of traveling to the event regardless) and the on-site event is not cancelled, you will ONLY be able to listen to the General Sessions and the Cannabis Sessions. You will have not have access to the Food Labs Sessions and there will be NO recording of these sessions. If you have any questions, please contact Veronica Allen, Event Manager.

–END UPDATE —

EDGARTOWN, MA, Jan. 22, 2020 – Innovative Publishing Co., the publisher of Food Safety Tech and organizer of the Food Safety Consortium Conference & Expo is announcing the launch of the Food Labs Conference. The event will address regulatory, compliance and risk management issues that companies face in the area of testing and food laboratory management. It will take place on June 3–4 in Rockville, MD.

Some of the critical topics include discussion of FDA’s proposed FSMA rule, Laboratory Accreditation Program for Food Testing; considerations in laboratory design; pathogen testing and detection; food fraud; advances in testing and lab technology; allergen testing, control and management; validation and proficiency testing; and much more.

The event is co-located with the Cannabis Labs Conference, which will focus on science, technology, regulatory compliance and quality management. More information about this event is available on Cannabis Industry Journal.

“By presenting two industry conferences under one roof, we can provide attendees with technology, regulatory compliance and best practices that cannabis and food might share but also focused topics that are unique to cannabis or food laboratory industry needs,” said Rick Biros, president of Innovative Publishing Co., Inc. and director of the Food Labs Conference.

The call for abstracts is open until February 28.

The agenda and speakers will be announced in early March.

About Food Safety Tech
Food Safety Tech publishes news, technology, trends, regulations, and expert opinions on food safety, food quality, food business and food sustainability. We also offer educational, career advancement and networking opportunities to the global food industry. This information exchange is facilitated through ePublishing, digital and live events.

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.

Salami, plastic packaging

Using Raman Spectroscopy to Evaluate Laminated Food Packaging Films

By Ellen Link, Gary Johnson, Ph.D.
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Salami, plastic packaging

Laminated plastics are common and popular food packaging options. They are strong and flexible, making them ideal for both packing and presentation, and can be used for cooking, frozen foods, drink pouches, snack products and even pet food. Yet, unreliable plastics can create a problem for food packaging and the safety of a product.

If a grade of plastic is not what was promised or needed, there can be issues that lead to spoilage, spills and messes, crystallization, mold or other risks. Additionally, there may be concerns about how laminated films will interact with the product itself, as it could impact food safety or lifecycle. For these reasons, it is critical to have accurate information when evaluating the plastics films used in food packaging.

Raman Spectroscopy

Raman spectroscopy (RS) is a powerful method of identifying and characterizing chemical compounds based on light scattering by a sample. It can be used to identify layers in food packaging films to accurately understand the chemical makeup of the laminated plastic. The effect is named for its inventor, C.V. Raman, who was awarded the Nobel prize in physics for its discovery in 1930. It is a non-destructive method that uses an induced-dipole mechanism to probe the vibrations of the chemical bonds in a molecule. The Raman spectrum shows a pattern of molecular vibrations that represents a detailed chemical fingerprint of a material, providing insights into the product composition.

A Raman spectrum is obtained by illuminating the sample with a laser and collecting and measuring the scattered light with a spectrometer. The molecular vibrational modes vary depending on the geometry and electronic structure of the chemical compound present in the sample. By controlling the position of the laser focus point on a sample, a map of the composition can be created. This provides valuable information on the plastic film related to its composition, such as number of layers, thickness of each layer and overall make-up.

In the food packaging and safety industry, this technique can be used to evaluate laminated plastic films by examining polymers, minerals, and/or inorganic fillers and pigments present in the film. Specific food packaging products that can benefit from RS assessments include heat seals, containers, lids, films and wrappers both for durability and performance and for diffusion, permeation or other concerns.

Benefits and Limitations

There are numerous benefits to using the RS method. A major advantage is that there is virtually no sample preparation necessary; spectra can be obtained without direct contact, such as through the sides of glass vials or through windows in reaction cells. As a non-destructive technique, it allows an easy, highly accurate way to take a sample, create a chemical composition map and better understand films’ barrier properties, structural integrity and layers. It has broad applicability and works using conventional microscope optics.

There are, of course, limitations to the approach, as well. Fluorescent components or impurities in a sample can emit a photoluminescent background that overwhelms the Raman scattering. Samples can also be damaged by the laser if too much power is used, or the sample absorbs light at the laser wavelength. Samples that do fluoresce and samples that are photolabile act as common interferences for the RS method. In many cases, these interferences can be overcome with the proper choice of laser and sampling techniques. Additionally, while RS provides an accurate analysis of laminated films, the technique cannot be used on metals or metallic compounds (which can be assessed using scanning electron microscopy or light optical microscopy) or organic pigments or ink layers (which can be assessed with other infrared techniques).

Using RS for Food Packaging

RS can offer a variety of insights for food packaging films:

  • Failure analysis. If a plastic used for a heat seal in a fruit or yogurt cup fails, it could result in a mess for manufacturers, stores or the consumer. Exposure to air or elements could also lead to spoilage, particularly for refrigerated foods. Inconsistent plastic packaging could result in weak points that break, crack or puncture, which could also result in mold, mess or other spoilage concerns. If a manufacturer experiences a failure in a heat seal or packaging leading to leakage or spoilage, RS analysis can help determine why the failure occurred (was in the plastic film or something else) to help prevent future issues.
  • Supply chain validation. It is extremely important that the plastic films coming from suppliers are what they are promising and what the manufacturer needs. RS analysis can be used to determine the chemical make-up and morphology of packaging to confirm a supplier’s claims before proceeding with use of the film in food packaging and products.
  • Simple decision making. If a manufacturer is trying to decide which material to use, RS can provide answers. For example, if there is a need for moisture non-permeating films and there are multiple options available, an RS chemical map can illustrate what to expect with each option, aiding in the decision-making process when combined with other known factors such as cost or timing. If there is an additive in the food product that may diffuse into the film, RS can determine which material might best resist the potential problem.
  • Packaging appearance. If there is a swirl or haze in the packaging, RS can compare the area with the issue to a clear section to determine if the defect in the film is a foreign polymer or an inorganic pigment or filler, identifying the source of the problem.

RS analysis provides a wealth of information in a manner that is non-destructive. Giving a chemical fingerprint to identify composition with extremely good spatial resolution gives manufacturers valuable information that can be used to mitigate issues, correct problems or make important decisions. These actions in turn can help ensure food safety, which builds brand image and manufacturer equity. Ultimately, RS analysis can play an important role in the success of a product, a brand or a company.

magnifying glass

Food Fraud and Adulteration Detection Using FTIR Spectroscopy

By Ryan Smith, Ph.D.
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magnifying glass

Producers of food-based products are faced with challenges of maintaining the safety and quality of their products, while also managing rapid screening of raw materials and ingredients. Failure to adequately address both challenges can be costly, with estimated recall costs alone starting around $10 million, in addition to any litigation costs.1 Long-term costs can accumulate further as a result of damage to brand reputation. A vast array of methods has been employed to meet these challenges, and adoption continues to increase as technology becomes smaller, cheaper and more user friendly. One such technique is Fourier transform infrared (FTIR) spectroscopy, an analytical technique that is widely used for quick (typically 20–60 seconds per measurement) and non-destructive testing of both man-made and natural materials in food products. The uniformity and physical state of the sample (solid vs. liquid) will dictate the specifics of the hardware used to perform such analyses, and the algorithm applied to the identification task will depend, in part, on the expected variability of the ingredient.

Infrared spectral measurements provide a “compositional snapshot”— capturing information related to the chemical bonds present in the material. Figure 1 shows an example of a mid-infrared spectrum of peppermint oil. Typically, the position of a peak along the x-axis (wavenumber) is indicative of the type of chemical bond, while the peak height is related either to the identity of the material, or to the concentration of the material in a mixture. In the case of peppermint oil, a complex set of spectral peaks is observed due to multiple individual naturally occurring molecular species in the oil.

Mid-infrared spectrum, peppermint oil
Figure 1. Mid-infrared spectrum of peppermint oil. The spectrum represents a “chemical snapshot” of the oil, as different peaks are produced as a result of different chemical bonds in the oil.

Once the infrared spectrum of an ingredient is measured, it is then compared to a reference set of known good ingredients. It is important that the reference spectrum or spectra are measured with ingredients or materials that are known to be good (or pure)—otherwise the measurements will only represent lot-to-lot variation. The comparative analysis can assist lab personnel in gaining valuable information—such as whether the correct ingredient was received, whether the ingredient was adulterated or replaced for dishonest gain, or whether the product is of acceptable quality for use. The use of comparative algorithms for ingredient identification also decreases subjectivity by reducing the need for visual inspection and interpretation of the measured spectrum.

Correlation is perhaps the most widely used algorithm for material identification with infrared spectroscopy and has been utilized with infrared spectra for identification purposes at least as early as the 1970s.2 When using this approach, the correlation coefficient is calculated between the spectrum of the test sample and each spectrum of the known good set. Calculated values will range from 0, which represents absolutely no match (wrong or unexpected material), to 1, representing a perfect match. These values are typically sorted from highest to lowest, and the material is accepted or rejected based on whether the calculated correlation lies above or below an identified threshold. Due to the one-to-one nature of this comparison, it is best suited to identification of materials that have little or no expected variability. For example, Figure 2 shows an overlay of a mid-infrared spectrum of an ingredient compared to a spectrum of sucrose. The correlation calculated between the two spectra is 0.998, so the incoming ingredient is determined to be sucrose. Figure 3 shows an overlay of the same mid-infrared spectrum of sucrose with a spectrum of citric acid. Notable differences are observed between the two spectra, and a significant change in the correlation is observed, with a coefficient of 0.040 calculated between the two spectra. The citric acid sample would not pass as sucrose with the measurement and algorithm settings used in this example.

Mid-infrared spectrum, sucrose
Figure 2. An overlay of the mid-infrared spectrum of sucrose and a spectrum of a different sample of sucrose.
Mid-infrared spectrium, sucrose, citric acid
Figure 3: An overlay of the mid-infrared spectrum of sucrose and a spectrum of citric acid.

When testing samples with modest or high natural variability, acceptable materials can produce a wider range of infrared spectral features, which result in a correspondingly broad range of calculated correlation values. The spread in correlation values could be of concern as it may lead to modification of algorithm parameters or procedures to “work around” this variation. Resulting compromises can increase the potential for false positives, meaning the incorrect ingredient or adulterated material might be judged as passing. Multivariate algorithms provide a robust means for evaluating ingredient identity for samples with high natural variability.

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