On Sunday China’s General Administration of Customs announced that it would be suspending imported shipments of poultry from a Tyson Foods plant based in Springdale, Arkansas. The suspension is reportedly due to an outbreak of coronavirus cases at the facility.
“The results across our Northwest Arkansas facilities, and the country more broadly, reflect how much is still unknown about this virus, which is why Tyson is committed to providing information to our local health officials and enhanced education to our team members,” said Tom Brower, senior vice president of health and safety for Tyson Foods stated in a company press release. “Through our inclusive approach to large-scale testing, we are finding that a very high level of team members who test positive do not show symptoms. Identifying asymptomatic cases helps the community, since other testing is often limited to people who feel unwell.”
Many food retailers are dependent on outdated methods of recording product food temperature that include pen, paper and trust given to employees to remember to complete inspections. Unfortunately, this style of inspection completion can be an outlet for foodborne Illness outbreaks. As technologies advance to offer real-time reporting, managing such vital inspections and reports has never been so simple while drastically reducing risk and increasing consumer safety.
Food service management should be asking the following questions on a daily basis:
What food items passed & failed the cooling/cooking process?
Why did these items fail and what is the monetary value of product loss?
Have safety & operational checklist logs been completed on time?
What corrective actions were issued?
Have temperature-controlled cases failed within the last 24 hours?
With recent breakthroughs in food safety technology, the answers to the above questions can be found in your email inbox, online dashboard or mobile application. There are technologies available that give food service providers the ability to efficiently track and manage their food safety efforts by digitizing any type of food safety, quality assurance and sanitation inspections. One such technology uses a dual infrared/probe Bluetooth thermometer and real-time temperature sensors to help complete food safety temperature checks as well as bringing automation to cooling, cooking, and “time as temp” logs. This kind of technology can be integrated into food safety and risk management tools such as sensor monitoring or location-driven inspection technology.
Sufficient inspection software is not just a format for checklist completion. Software developed for the food service industry is behavioral based, meaning the software will guide inspectors to their next question and corrective action; or it automates the processes all together. This includes reminding inspectors when inspections are due in addition to providing snap shots to management on the status of said inspections with the ability to easily pull all data from the cloud.
Automated Logs for Cooking, Cooling and ‘Time as Temp’
Before taking a closer look at how new technology is shaping cooling logs, cooking logs, and time as a public health control; the following are a few terms to remember:
Cooling & Cooking Logs: Recording of food product temperatures during cooking & cooling cycles that meet both time and temperature constraints outlined by the FDA.
Time as a Public Health Control: Food product whose holding compliance is measured not by temperature but by time spent in the range of 41° F – 135° F after either being cooled below 41° F or heated above 135° F, as outlined by the FDA.
Strategy: What is being done with the food product? Is it being cooked, cooled or held for Time as a Public Health Control?
Phase: Time and/or temperature constraints set within the strategy. For example, cooling product from 135° F to 70° F within two hours or cooking to 165° F before being served.
As one of the most groundbreaking forms of food safety inspections, automated cooling and cooking logs create the ability to customize strategies for such processes. Cooling and cooking logs are an important aspect of food safety for their ability to complete the product lifecycle that can often times be overlooked. Such logs also help to ensure food product is cooked to proper temperatures before it is served to customers. Cooling log strategies look for product to be cooled from 135° F to 70° F within two hours and from 70° F to 41° F within four hours. Cooking logs are built in similar fashion but may vary on the type of product.
Proactive technology allows food service personnel to automate the cooling and cooking process with sensors that record and save product temperatures during cooking and cooling strategies. Once temperature thresholds are succeeded or anticipated to be missed, customized alerts can notify employees that the food is either ready to be served or that action is needed to avoid product loss.
For example, cooling a batch of rotisserie chickens would typically require an employee to manually check the product temperature every 30 minutes to ensure the rotisserie chickens are being cooled properly. With new technology, this same employee can insert a food-grade sensor probe into one or more of the chickens and walk away. The employee can reference a mobile application and real-time push notifications to ensure the chickens are cooling from 135° F to 70° F within two hours and from 70° F to 41° F within four hours. If the software’s algorithms predict that the rotisserie chickens will not meet the conditions set in the phase, proactive push notifications will be sent to the employee for specific action to ensure proper cooling, which avoids product loss and consumer claims related to foodborne illness. Using this method also allows for overnight cooling logs in addition to saving labor hours, all while eliminating paper.
As demand for increased food safety practices continues to climb, so will the capabilities of behavioral based inspection technology. Equipped with industry leading software engineers along with dual purpose customer support and onboarding services, this space will expand on its software and hardware capabilities to replace all outdated methods of inspection processes.
The coronavirus lockdown has halted fishing operations in most Indian harbors, and now stale fish and shellfish is finding its way to the consumer. In India, 50 tons of stale and spoiled tuna fish and prawns, no longer fit for human consumption, have been seized and destroyed after inspections by the Food Safety Department. These violations can carry fines and jail sentences.
Today the FDA announced that it will begin requesting electronic records related to import records required under FSVP for Importers of Food for Humans and Animals. The agency is moving to remote inspections as a result of the COVID-19 pandemic. FDA stated that in “rare” instances it will onsite FSVP inspections—these situations include outbreaks.
“The FDA will immediately begin conducting a limited number of remote inspections, prioritizing the inspections of FSVP importers of food from foreign suppliers whose onsite food facility or farm inspections have been postponed due to COVID-19. The Agency is also planning to continue to conduct previously assigned routine and follow-up inspections remotely during this time. Importers subject to the remote inspections will be contacted by an FDA investigator who will explain the process for the remote inspection and make written requests for records.” – CFSAN Constituent Update
I know, it’s a disgusting, lazy attention-grabbing image, but if you’ve stayed with me this far it must have worked. Sadly, the story is true; it was back in the 1980s the first time that I heard of how a mouse in a bottling plant got stuck inside one of the empties ready to go onto the filling line. Unnoticed, this mouse was immersed in the beverage, was then sealed in when the bottle cap was applied, and then drowned while the bottle was packaged and palletized. While the product moved through distribution to retail, its carcass slowly dissolved and went unnoticed until an unsuspecting customer … well, you can imagine how that story ended.
After recounting this story recently, imagine my surprise to learn this is still happening today! Maybe three years ago, The Verge published a “A brief history of rodents in soda containers” and, in the present age of social media, it will surprise no one to see the video filmed by someone who spotted the mouse in their soda bottle! No surprise, there’s more than one filming of a mouse in a sealed Coca Cola bottle, the horror continues.
Let’s not pretend this is only a problem with fizzy drinks industry, every food manufacturing concern faces the risk of inadvertent contamination of their production from rodents; if not the whole animal itself, then it’s urination on raw commodity, or its fecal pellets falling into a mixer, or its hairs falling off in packaging. No wonder a well-designed and faithfully serviced pest management program and proper IPM inspections are necessary for every facility in the industry. The good news is there are digital rodent monitoring systems that can alert pest managers of a rodent capture inside a facility and rodent activity / pressure outside so they can act quickly. Perhaps the most valuable impact of this technology is that it helps automate trap checking that consumes as much as 75% of the service time. Now, that precious time can be reallocated to deeper, proactive IPM inspections to help head off infestations before they happen and root cause analysis and corrective actions if captures occur.
As machines become more intelligent, every industry on earth will find abundant new applications and ways to benefit. For the food industry, which has an incredible number of moving parts and is especially risk-averse, machine vision and machine learning are especially valuable additions to the supply chain.
The following is a look at what machine vision is, how it can play a role in manufacturing and distributing foods and beverages, and how employers can train workers to get the most out of this exciting technology.
What Is Machine Vision?
Machine vision isn’t a brand-new concept. Cameras and barcode readers with machine vision have long been capable of reading barcodes and QR codes and verifying that products have correct labels. Modern machine vision takes the concept to new levels of usefulness.
Barcodes and product identifiers have a limited set of known configurations, which makes it relatively straightforward to program an automated inspection station to recognize, sort or reject products as necessary. Instead, true machine vision means handlers don’t have to account for every potential eventuality. Machine vision instead learns over time, based on known parameters, to differentiate between degrees of product damage.
Consider the problem of appraising an apple for its salability. Is it bruised or discolored? Machine vision recognizes that no two bruises look precisely alike. There’s also the matter of identifying different degrees of packaging damage. To tackle these problems, it’s not possible to program machine vision to recognize a fixed set of visual clues. Instead, its programming must interpret its surroundings and make a judgment about what it sees.
The neural networks that power machine vision have a wide range of applications, including improving pathfinding abilities for robots. In this article, I’ll focus on how to leverage machine vision to improve the quality of edible products and the profitability of the food and beverage industry.
Applications for Machine Vision in the Food Industry
There are lots of ways to apply machine vision to a food processing environment, with new variations on the technology cropping up regularly. The following is a rundown on how different kinds of machine vision systems serve different functions in the food and beverage sector.
1. Frame Grabbing and 3-D Machine Vision
Machine vision systems require optimal lighting to carry out successful inspections. If part of the scanning environment lies in shadow, undesirable products might find their way onto shelves and into customers’ homes.
Food products sometimes have unique needs when it comes to carrying out visual inspections. It’s difficult or impossible for fallible human eyeballs to perform detailed scans of thousands of peas or nuts as they pass over a conveyor belt. 3-D machine vision offers a tool called “frame grabbing,” which takes stills of — potentially — tens of thousands of tiny, moving products at once to find flaws and perform sorting.
2. Automated Sorting for Large Product Batches
Machine vision inspection systems can easily become part of a much larger automation effort. Automation is a welcome addition to the food and beverage sector, translating into improved worker safety and efficiency and better quality control across the enterprise.
Inspection stations with machine vision cameras can scan single products or whole batches of products to detect flaws. But physically separating these products must be just as efficient a process as identifying them. For this reason, machine vision is an ideal companion to compressed air systems and others, which can carefully blow away and remove even a single grain of rice from a larger batch in preparation.
3. Near-Infrared Cameras
Machine vision takes many forms, including barcode and QR code readers. A newer technology, called near-infrared (NIR) cameras, is already substantially improving the usefulness and capabilities of machine vision.
Remember that bruised apple? Sometimes physical damage to fruits and vegetables doesn’t immediately appear on the outside. NIR technology expands the light spectrum cameras can observe, giving them the ability to detect interior damage before it shows up on the exterior. It represents a distinct advantage over previous-generation technology and human inspectors, both of which can leave flaws undiscovered.
Tips on Training Workers to Use Machine Vision
Implementing machine vision into a productive environment delivers major benefits, but it also comes with a potentially disruptive learning curve. The following are some ideas on how to navigate it.
1. Take Advantage of Third-Party Training Courses
Don’t expect employees to hit the ground running with machine vision if they’re not familiar with the fundamentals of how it works. Google has a crash course on machine learning, and Amazon offers a curriculum as well to help companies get their employees up to speed on the technology and how to use it.
2. Get the Lighting Right
Having the appropriate intensity of light shining on the food product is essential for the machine vision cameras to get a clear photo or video. The most common types of lighting for machine vision are quartz halogen, LEDs, metal halide and xenon lights. Metal halide and xenon are better for larger-scale operations because of their brightness.
Train employees to check the amount and positioning of the lighting before each inspection station starts up for the day, so that no shadows obscure products from view.
Machine vision does not involve buying a camera or two, setting them up, then slapping the “autopilot” button. As products turn over, and manufacturing and distribution environments change and grow over time, machine vision algorithms require re-training, and you might need to redesign the lighting setup.
Employers should find individuals from their ranks who show interest and aptitude in this technology and then invest in them as subject matter experts and process owners. Even if an outside vendor is the one providing libraries of algorithms and ultimately coming up with machine vision designs, every company needs a knowledgeable liaison who can align company needs with the products on the market.
It is important to remember that neither machine learning nor machine vision are about creating hardware that thinks and sees like humans do. With the right approach, these systems can roundly outperform human employees.
But first, companies need to recognize the opportunities. Then, they must match the available products to their unsolved problems and make sure their culture supports ongoing learning and the discovery of new aptitudes. Machine vision might be superior to human eyesight, but it uses decidedly human judgments as it goes about its work.
Modern food supply chains are inherently complex, with products typically passing through multiple suppliers and distributors, as well as countries and continents, before they end up on the supermarket shelf. While global supply chains offer consumers greater choice and convenience, they also make protecting the security of food products more challenging. With additional stakeholders between farm and fork, products are exposed to an elevated risk of biological or chemical contamination, as well as food counterfeiting and adulteration challenges—potentially putting consumer health and brand reputation in jeopardy.
Given the importance of maintaining the safety, quality and provenance of food products, global regulatory bodies are placing the integrity of supply chains under increased scrutiny. In the United States, for example, the adoption of FSMA moved the focus from responding to foodborne illnesses to preventing them by prioritizing comprehensive food testing measures, enforcing inspections and checks, and enabling authorities to react appropriately to safety issues through fines, recalls or permit suspensions.1 Similarly, China’s revised Food Safety Law (known as FSL 2015) is widely considered to be the strictest in the country’s history, and seeks to drive up quality standards by empowering regulators, and enhancing traceability and accountability through robust record-keeping. 2 The European Union continues to closely regulate and monitor food safety through its General Food Law, which is independently overseen by the European Food Safety Authority from a scientific perspective.
Achieving the Highest Standards of Food Security, Integrity and Traceability
For producers, manufacturers and distributors, the heightened regulatory focus on the security and integrity of the food supply chain has placed additional emphasis on accurate record-keeping, transparent accountability and end-to-end traceability. To meet the needs of the modern regulatory landscape, food chain stakeholders require robust systems and tools to manage their quality control (QC), environmental monitoring and chain of custody data. Despite this, many businesses still handle this information using paper-based approaches or localized spreadsheets, which can compromise operational efficiency and regulatory compliance.
The fundamental flaw of these traditional data management approaches is their reliance on manual data entry and transcription steps, leaving information vulnerable to human error. To ensure the accuracy of data, some companies implement resource-intensive verification or review checks. However, these steps inevitably extend workflows and delay decision-making, ultimately holding up the release of products at a high cost to businesses. Moreover, as paper and spreadsheet-based data management systems must be updated by hand, they often serve merely as a record of past events and are unable to provide insight into ongoing activities. The time lag associated with recording and accessing supply chain information means that vital insight is typically unavailable until the end of a process, and data cannot be used to optimize operations in real-time.
Furthermore, using traditional data management approaches, gathering information in the event of an audit or food safety incident can be extremely challenging. Trawling through paperwork or requesting information contained in spreadsheets saved on local computers is time-consuming and resource-intensive. When it comes to establishing accountability for actions, these systems are often unable to provide a complete audit trail of events.
Digital Solutions Transform Food Security and Compliance
Given the limitations of traditional workflows, food supply chain stakeholders are increasingly seeking more robust data management solutions that will allow them to drive efficiency, while meeting the latest regulatory expectations. For many businesses, laboratory information management systems (LIMS) are proving to be a highly effective solution for collecting, storing and sharing their QC, environmental monitoring and chain of custody data.
One of the most significant advantages of managing data using LIMS is the way in which they bring together people, instruments, workflows and data in a single integrated system. When it comes to managing the receipt of raw materials, for example, LIMS can improve overall workflow visibility, and help to make processes faster and more efficient. By using barcodes, radiofrequency identification (RFID) tags or near-field communication, samples can be tracked by the system throughout various laboratory and storage locations. With LIMS tracking samples at every stage, ingredients and other materials can be automatically released into production as soon as the QC results have been authorized, streamlining processes and eliminating costly delays.
By storing the standard operating procedures (SOPs) used for raw material testing or QC centrally in a LIMS, worklists, protocols and instrument methods can be automatically downloaded directly to equipment. In this way, LIMS are able to eliminate time-consuming data entry steps, reducing the potential for human error and improving data integrity. When integrated with laboratory execution systems (LES), these solutions can even guide operators step-by-step through procedures, ensuring SOPs are executed consistently, and in a regulatory compliant manner. Not only can these integrated solutions improve the reliability and consistency of data by making sure tests are performed in a standardized way across multiple sites and testing teams, they can also boost operational efficiency by simplifying set-up procedures and accelerating the delivery of results. What’s more, because LIMS can provide a detailed audit trail of all user interactions within the system, this centralized approach to data management is a robust way of ensuring full traceability and accountability.
This high level of operational efficiency and usability also extends to the way in which data is processed, analyzed and reported. LIMS platforms can support multi-level parameter review and can rapidly perform calculations and check results against specifications for relevant customers. In this way, LIMS can ensure pathogens, pesticides and veterinary drug residues are within specifications for specific markets. With all data stored centrally, certificates of analysis can be automatically delivered to enterprise resource planning (ERP) software or process information management systems (PIMS) to facilitate rapid decision-making and batch release. Furthermore, the sophisticated data analysis tools built into the most advanced LIMS software enable users to monitor the way in which instruments are used and how they are performing, helping businesses to manage their assets more efficiently. Using predictive algorithms to warn users when principal QC instruments are showing early signs of deterioration, the latest LIMS can help companies take preventative action before small issues turn into much bigger problems. As a result, these powerful tools can help to reduce unplanned maintenance, keep supply chains moving, and better maintain the quality and integrity of goods.
While LIMS are very effective at building more resilient supply chains and preventing food security issues, they also make responding to potential threats much faster, easier and more efficient. With real-time access to QC, environmental monitoring and chain of custody data, food contamination or adulteration issues can be detected early, triggering the prompt isolation of affected batches before they are released. And in the event of a recall or audit, batch traceability in modern LIMS enables the rapid retrieval of relevant results and metadata associated with suspect products through all stages of production. This allows the determination of affected batches and swift action to be taken, which can be instrumental in protecting consumer safety as well as brand value.
Using LIMS to Protect Security and Integrity of the Food Supply Chain
Increasingly, LIMS are helping businesses transform food security by bringing people, instruments and workflows into a single integrated system. By simplifying and automating processes, providing end-to-end visibility across the food supply chain, and protecting the integrity of data at every stage, these robust digital solutions are not only helping food supply chain stakeholders to ensure full compliance with the latest regulations; they are enabling businesses to operate more efficiently, too.
Food accounts for one-third of the 42 million products imported into the United States each year, according to Andrew J. Seaborn, supervisory consumer safety officer, division of import operations, ORA, FDA. FSMA’s risk-based FSVP rule places responsibility on importers to ensure their food is safe, yet since the rule was implemented, the most common Form 483a observation has been a failure to develop an FSVP. In fact, from FY 2017 to present, the observation was cited 552 times, outweighing any other observation, said Seaborn at the recent Food Safety Supply Chain Conference, as he shared some of the latest trends in compliance and enforcement related to FSVP.
Thus far, common citations include:
No written hazard analysis to identify and evaluate known or reasonable foreseeable hazards
No written procedures that ensure appropriate foreign supplier verification activities are occurring related to imported food
Seaborn noted several additional “significant observations” related to FSVP inspections, including incorrect entry data, and the absence of documentation in the following areas:
Approval of a foreign supplier
Evaluating foreign supplier performance, along with related risks
Establishing written procedures to ensure foreign supplier verification activities are performed
Review and assessment of another party’s evaluation of foreign supplier performance
Ensuring food was produced in compliance with low acid canned foods regulations
Related to meeting the definition of a very small importer, when applicable
Main Points of FSVP
FSVP Inspections (Completed)
U.S.-based importers responsible to ensure safety of imported food
Learn more about food fraud at the Food Labs Conference | June 2–4, 2020 | Rockville, MDThis week FDA made an announcement during a public meeting that the agency’s routine inspection to verify compliance with the FSMA Intentional Adulteration rule will start next March.
The first compliance date for the rule is this July. It is a requirement for food facilities covered under this rule to develop and implement a food defense plan that identifies vulnerabilities and the consequent mitigation plan.
FDA stated that it has received feedback on the “novel nature” of the rule’s requirements and that stakeholders want more time to develop their food defense plans. “ To allow industry time with the forthcoming materials, tools, and trainings, and because the IA rule represents new regulatory territory for all of us, we will be starting routine IA rule inspections in March 2020,” FDA stated and added that it is working on developing more resources as well as the final part of draft guidance to continue to assist industry.
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