Tag Archives: AI

Food Traceability and Authentication in the AI Era

By Maria-Eleni Dimitrakopoulou
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Food traceability provides comprehensive information about a product’s history and origin, facilitating efficient recalls and supply chain management. However, distinct types of food fraud, such as concealment, counterfeit, and mislabelling, pose significant challenges. The integration of Artificial Intelligence (AI) and new regulatory measures, like the FDA’s traceability rule, enhance food safety and authenticity, fostering a more transparent and reliable food supply chain.

In the intricate web of the global food supply chain, ensuring the safety and authenticity of consumables stands as a paramount concern. Food traceability, defined as the ability to provide comprehensive information about the history and origin of a product throughout its journey, emerges as a cornerstone in this endeavour. This meticulous documentation not only facilitates supply chain management but also empowers swift actions such as recalls in the event of safety or quality breaches.

Beyond its logistical benefits, food traceability assumes a pivotal role in safeguarding consumer interests. By serving as a fundamental component of food safety and quality assurance, traceability ensures transparency and accountability at every stage of production and distribution. However, the efficacy of a traceability system is inherently tied to the credibility of its origins, paving the way for the convergence of food traceability and authentication.

Unveiling the Shadows: The Challenge of Food Adulteration

In an era plagued by instances of food adulteration and mislabelling, the imperative for robust authentication mechanisms becomes increasingly apparent. Reports from international and national research bodies shed light on a myriad of cases spanning various food categories, from wine and spirits to olive oil, fish, meat, and beyond. This pervasive challenge underscores the need for stringent standards and regulatory frameworks to combat fraudulence and uphold consumer trust.

Food fraud manifests in several forms, each presenting unique challenges for detection and prevention. For example:

  • Concealment involves hiding inferior or harmful ingredients within a product to avoid detection. An example of this is the addition of melamine in milk to falsely increase protein content readings, which led to a major scandal in China.
  • Counterfeit products replicate and sell a product under the guise of a well-known brand, often with substandard quality. These fake products can range from everyday items like bottled water to high-end goods like wines and spirits. Counterfeiting not only deceives consumers but also damages brand reputations and violates intellectual property rights.
  • Botanical Authentication ensures that plant-based products are derived from the claimed species and not substituted with cheaper alternatives. This is particularly important for products like herbal supplements, teas, and spices. For instance, saffron, one of the most expensive spices in the world, is often adulterated with less expensive substances such as dyed corn stigmas or safflower.
  • Geographical Origin fraud involves misrepresenting the region from which a product originates. Certain regions are known for producing specific high-quality foods and beverages, such as Champagne from France or Parmigiano Reggiano cheese from Italy. Mislabelling products to benefit from these reputations deceives consumers and undermines genuine producers.
  • Substitution entails replacing a high-value ingredient with a lower-cost one. This is common in products like olive oil, honey, and seafood. For example, extra virgin olive oil might be diluted with cheaper oils, or expensive fish species like tuna might be replaced with less costly ones like escolar. This not only cheats consumers but can also pose health risks.
  • Mislabelling involves incorrectly listing ingredients or nutritional information on labels. An example is claiming a product is organic when it is not.
  • Dilution involves adding water or other substances to increase the volume of a product. For instance, diluting fruit juices with water and not declaring it.
  • Unapproved Enhancements involve using unauthorized substances to enhance the appearance or quality of a product. An example is adding unauthorized dyes to make a product look fresher or more appealing.
  • Theft and Resale refers to stealing products and reintroducing them into the market through unauthorized channels. For example, reselling stolen goods without proper storage conditions.
  • Artificial Additives involves using artificial ingredients to mimic the qualities of a natural product. For example, adding synthetic vanilla flavor instead of natural vanilla extraction

The New Traceability Rule of FDA

The Food and Drug Administration (FDA) has introduced a new traceability rule aimed at enhancing the ability to trace the origin of foods throughout the supply chain more efficiently. This rule mandates that companies maintain more rigorous records of their supply chains, focusing on high-risk foods. The implementation of this rule is expected to significantly improve the speed and accuracy of traceability in the event of a foodborne illness outbreak or contamination incident, thus ensuring faster recalls and reducing the risk to public health.

The Dawn of a New Era: Advancements in Food Fraud

As the spectre of food fraud looms large, there arises an urgent demand for sophisticated analytical techniques to authenticate foodstuffs with precision and reliability. Here, the advent of Artificial Intelligence (AI) heralds a new era of innovation. AI-driven algorithms can sift through vast datasets, identifying patterns and anomalies that elude traditional methods. Machine learning models can analyse complex chemical compositions, flagging deviations indicative of adulteration or mislabelling. By harnessing the power of AI, authorities can fortify their efforts in safeguarding consumer interests and preserving the integrity of the global food market.

Charting the Course Ahead: Toward a Safer, More Authentic Future

In the pursuit of food safety and quality, the symbiotic relationship between traceability and fraud, bolstered by AI technologies, emerges as a beacon of hope. By fortifying supply chain transparency and deploying cutting-edge analytical methods, stakeholders can navigate the complexities of the modern food landscape with confidence and integrity. The integration of the FDA’s new traceability rule further strengthens this endeavour, ensuring a safer and more reliable food supply chain for all.

Paul Bradley
Ask The Expert

Ask the Expert: Five Steps for Success in Digitization and Technology Selection

By Paul Bradley
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Paul Bradley

Across the food and beverage industry, organizations are undertaking a wide variety of data-oriented technology initiatives. There are a host of reasons for the trend, and indeed the convergence of multiple factors is likely behind the growing urgency for digitization within many food and beverage brands, manufacturers and supplier organizations. To be sure, ongoing supply chain instability over the last three or more years has put a focus on supply chain resilience and the need for more nimble and flexible supply networks. A dynamic and ever-changing global regulatory landscape is driving compliance and reporting requirements that are increasingly difficult to meet without a solid digital strategy in place. ESG initiatives are driving the need for increased visibility into global supply chains. Evolving consumer preferences create pressures on R&D organizations for continued product innovation, all of which needs to take place within acceptable safety, quality and risk management parameters. And of course, hovering over all of this is a tight (and increasingly costly) labor market, putting increased focus on opportunities for automation and increased efficiently.

Alongside these macro-level global trends, technology itself is moving forward at a rapid pace. The global food and beverage value chain has become more interconnected than ever before, with massive amounts of information moving around the world at remarkable speed. And of course, no discussion of technology is complete without a mention of artificial intelligence (AI). While by no means a new idea—many mature AI-based technologies have existed within the industry for years—AI is evolving quickly. Generative AI technologies, hardly known prior to 2023, are now appearing across the technology landscape, and dominating discussions around technology investment and strategy.

Confronted with all of this, food and beverage industry leaders could be forgiven for feeling a bit overwhelmed. Not only is more information (some valuable, some less so) available than ever before, but a profusion of technology solutions are vying for attention, nearly all promising new levels of insight and productivity. The landscape is complex, but there are a few basic steps that teams can take to help ensure that any potential technology investments are pointed in the right direction and are set up for long term success. Let’s examine five basic, but important steps that can help guide digitization efforts to a strong outcome.

TraceGains Five steps graphic

1. Starting with the end in mind. The objective of a technology implementation should never be to implement a platform. Usually, technology investments start with a business problem that needs to be solved. For food safety teams, this can encompass a range of possibilities, from a desire to reduce error and gain efficiencies in processes, to a need for better real-time monitoring of processes already in place, to a desire to decrease global risk exposure in an increasingly diverse supplier environment. Whatever the situation, teams can substantially de-risk technology investments by being crystal clear on the business objectives (not simply the implementation goals) of a given initiative. Clearly defining a “north star” in terms of expected business outcomes, and revisiting those goals often, can help keep projects focused, and avoid costly missteps and poor prioritization decisions along the way.

2. Defining stakeholders. Though seemingly obvious, it can be surprisingly easy for teams to launch an initiative without a clear view of impacted stakeholders. Typically, a given technology solution will have relatively well-understood functional owners within an organization. But it’s equally important to understand downstream groups that may have to interact with the solution or its outputs. Direct users, too, are a stakeholder community that can easily be overlooked. A solution that does its job on paper but doesn’t align with the working conditions of an end-user community is going to run into challenges. External stakeholders may also need to be considered, as suppliers, customers, contract manufacturers and other entities can all become obstacles to program success if their buy-in hasn’t been considered early in the process.

3. Supplementing (vs. replacing) human intelligence. With all the buzz around AI, it’s easy to get excited about the longer-term possibilities of the technology. And that’s appropriate – AI has already had notable effects on industry technologies and will continue to do so in the years to come. But it’s equally important to consider the current state of generative AI solutions, and be realistic about the limitations and risks of the technology as it exists today. A useful framework for this approach can be to think in terms of how AI can help supplement, even maximize, the intelligence and expertise of human users. Can it consolidate data that would be cumbersome to organize and collate? Can it scan information and flag likely priorities for further investigation?

In the high-stakes environment of food safety and quality, the overlay of hard-earned human knowledge and awareness is going to remain necessary for a long time to come. At the same time, AI-based solutions are already present in the space, and those who use them wisely may very well realize a significant market advantage over those who shy away entirely.

4. Getting real about data quality. Whether the discussion is about AI, data insights, analytics, compliance reporting or automation, most technologies run on data. Put another way, most technologies aren’t any better than the data they consume. The ancient saying, “garbage in, garbage out” remains depressingly current, many decades after the dawn of computing.  As a result, it’s important to take a hard look at the quality, completeness, consistency and structure of the information that a potential technology solution will need to access in order to deliver on its promise. On the positive side, qualified technology providers should be able to provide assistance and clear guidance through the data side of any implementation, and in an increasingly networked world, providers may even be able to come to the table with useful industry data and data management practices that make this part of the digitization journey easier and faster. But it’s important not to skip this step; many are the solutions that never lived up to their potential because the data they needed to consume wasn’t workable.

5. Lastly, as initiatives come together, it’s important to loop back to the original business objectives that were clarified in the first step. Have those objectives been met and, crucially, can that be measured? If it can, the project has likely succeeded, and is positioned to yield insights toward the next step in the technology journey.

The good news is that as digitization continues across the food and beverage industry, it creates a greater opportunity for brands, manufacturers and suppliers to move away from the antiquated model of static, linear supply chains, and toward a more interconnected future based both on shared data and shared values. Explore the world’s largest network of F&B brands and suppliers at TraceGains Gather™, and learn more about the growing community of committed safety professionals worldwide.

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Rodrigo Malig
Ask The Expert

Why Customized Food Safety Programs Featuring AI and Molecular Testing Are Essential

By Food Safety Tech Staff
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Rodrigo Malig

Everyone understands the importance of a robust food safety program. It should ensure the safety of the product and environment, backed by solid, traceable data. The food industry is vast, stretching from the farm all the way to our plates, and includes a diverse array of foods and drinks. Different segments of this industry have specific needs, whether it’s unique spoilage tests or specialized predictions based on distinct data. Unfortunately, current services haven’t delivered a trustworthy solution for these needs.

Rodrigo Malig is the Chief Product Officer at TAAG Genetics. He oversees both the artificial intelligence and molecular diagnostic teams. In this column, Rodrigo discusses the crucial roles of AI and molecular testing in crafting a reliable, tailored solution for food safety.

What are common deficiencies in current food safety and quality programs?

Malig: Common shortcomings in Food Safety and Quality programs (and frustrations for hardworking FSQA professionals) include:

Lack of Customization: Many programs don’t adapt or customize to specific industry needs.

Routine Sampling Issues: Environmental sampling is often random, lacking intelligent risk-based criteria. There’s also an insufficient adaptive process after each sampling cycle.

Paper files
Relying on paper files makes keeping track of data, trending it and analyzing it more difficult and time consuming.

Testing Targets: The targets for environmental and finished product testing are often insufficient. For instance, industries need specific tests for spoilage microorganisms, but many don’t have access to these tests and rely instead on general aerobic plate counts, and yeast and mold.

LIMS (Laboratory Information Management System) Limitations: These systems often don’t offer accurate digitized mapping, customization or ability to adapt, leading them to inaccurately represent a facility or its changing needs.

Outdated Methods: Some programs still rely on outdated technologies and methods. Let’s take plate counts for example. There’s a focus on mere quantitative results without the specificity of what those organisms are. This prevents facilities from taking precise corrective and preventive actions. Additionally, we all know plate counts can be time consuming with long incubation times, have limited sensitivity, lack genetic information, require manual labor (thereby creating additional risk for contamination) and increase overall costs. It is essential to determine when plate counts need additional support or substitution, such as with PCR (Polymerase Chain Reaction).

Comparison to FDA Standards: Many confirmation methods are inferior compared to the FDA’s Whole Genome Sequencing.

PCR Kit Issues: When using PCR, many kits test for only a single microorganism. This limitation requires multiple tests to be run, leading to increased turnaround times and costs.

Traceability Concerns: A significant deficiency is the lack of traceability in many programs, requiring additional documentation to be performed on paper.

Incomplete data and analysis: Antiquated data management systems result in insufficient data collection and digitization. Many in the industry still manually write on paper or use Excel spreadsheets, which makes keeping track of data, trending it and analyzing it more difficult and time consuming.

Reactive and not predictive: Because of the deficiencies detailed above, food safety programs become reactive and insufficient to address risk.

How can we improve current food safety and quality programs?

Malig: An improved food safety and quality program must become predictive (and not reactive), by embracing and implementing technology featuring customization, molecular testing and AI. Below is a basic checklist for food companies to follow:

Data analysis smartphone
An ideal food safety and quality program should be digital, implement artificial intelligence and molecular testing, be comprehensive, and most importantly be simple and mobile!

Customized Software & Testing: Utilize software and tests tailored to your unique requirements.

Advanced Environmental Sampling: Embrace sampling that’s customized, risk-based, predictive and adaptive. Employ digitization and AI to efficiently map, record, analyze and predict sampling schemes. This system should also adapt after each cycle and accommodate changes in the environment, equipment and processes.

Molecular Testing: Polymerase Chain Reaction (PCR) testing is a molecular biology technique with several advantages, including:

  • Sensitivity: PCR is highly sensitive and can detect very small amounts of genetic material (DNA or RNA) in a sample. This makes it effective for detection even when the pathogen is present in low concentrations.
  • Specificity: PCR is highly specific, meaning it can accurately identify and differentiate between different microorganisms or genetic variants. This specificity reduces the likelihood of false-positive results.
  • Speed: PCR can provide results relatively quickly, often within a few hours, depending on the type of PCR used (e.g., real-time PCR or RT-PCR). This rapid turnaround time is crucial for time sensitive decisions in the food industry.
  • Cost: PCR can be cost efficient, especially with multiplex PCR kits that detect multiple pathogens in a single reaction, which essentially cuts time, labor, use of lab equipment and space, and overall cost.

Industry-Specific Microorganism Testing: Ensure you’re testing for microorganisms relevant to your industry, processes and products. This is especially crucial if your products are susceptible to spoilage by specific microorganisms.

Adaptive LIMS: Your Laboratory Information Management System (LIMS) should be both customizable and adaptive. It should digitally represent your facility with accuracy and adapt to any changes or needs.

Dynamic Microbiological Programs: Move away from reactive and repetitive testing schemes. Most current microbiological programs tend to test the same samples repeatedly. With the help of AI algorithms, we can now implement preventive and risk-based microbiological programs.

This real-life case study illustrates how a Fortune 100 Company implemented the solutions above to improve their food safety and quality program.

TAAG Contact Us

 

Emily Newton, Revolutionized Magazine

Five Technologies Impacting the Beverage Industry

By Emily Newton
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Emily Newton, Revolutionized Magazine

The beverage industry is undergoing a period of technological transformation. As consumer demand and supply chain pressures reveal the shortcomings of older systems and processes, beverage manufacturers are embracing new technologies at an unprecedented pace. While many of these trends are promising, some are more impactful than others. With that in mind, here are the five technologies making the biggest impact in the beverage industry.

Automation

While automation isn’t necessarily new, it is reaching new heights. Automation is becoming an essential part of the beverage sector as robotic systems become more accessible and versatile, and talent becomes harder to acquire.

The food and beverage industry currently has more than 4 million open positions and could add another 370,000 by 2031. With fewer young workers entering manufacturing, beverage facilities are turning to robotics to sustain productivity. The more automated a facility is, the more it can accomplish despite having fewer employees, offsetting the labor shortage.

Automation applies to more than just physical workflows, too. Robotic process automation is seeing increased adoption in back offices, where it can be used to boost productivity and reduce errors.

Artificial Intelligence

Another impactful technology in the beverage sector is artificial intelligence (AI). As beverage workflows become increasingly digitized, they generate more data. AI algorithms can analyze that data to turn it into actionable insights, helping beverage manufacturers predict and adapt to incoming changes and optimize their operations.

Common industry thinking holds that companies can only optimize two of three key variables—time, cost and quality—simultaneously. However, it’s often difficult for humans to determine which is the most valuable area for improvement in their businesses. AI can analyze workflow data to reveal weak points and highlight changes that would have the most significant impact, helping leaders make these decisions.

AI can also help predict future changes, including shifting consumer demand. With this insight, beverage producers can adjust to minimize losses and capitalize early on new trends. Those that don’t embrace AI analytics may quickly fall behind the competition as this technology becomes increasingly common.

The Internet of Things

As AI adoption grows, the Internet of Things (IoT) can help beverage companies make the most of these algorithms. IoT devices give previously unconnected machines wireless connectivity, providing more data points for AI models to analyze, improving their accuracy. This connectivity and data collection can also improve transparency.

One of the most impactful use cases for IoT sensors is in the supply chain. Connected tracking devices can provide real-time updates on shipment locations, temperature, vibrations and other factors. If anything falls out of acceptable parameters or schedules, they can alert relevant stakeholders so they can adapt to ensure safe, timely shipments.

IoT devices can also improve machine health by alerting workers to needed repairs. This data-driven, need-based approach prevents costly breakdowns while minimizing downtime from unnecessary maintenance.

Biotechnology

While many of the most impactful technologies in the beverage industry appear within manufacturing facilities, some focus on earlier workflows. Biotechnology, such as gene editing, can optimize the farming operations that produce the ingredients beverage companies need.

Some bioengineered crops require less water to grow or are pest-resistant, minimizing the need for pesticides. These upgrades reduce farms’ ongoing expenses, making beverage ingredients cheaper for production facilities. Other bioengineering processes can make certain ingredients healthier or less environmentally impactful, both of which appeal to consumers.

Emerging biotechnology solutions let beverage companies use specially designed enzymes to gauge milk contamination and spoilage better. With these biological markers, businesses can ensure they don’t send poor-quality products to market and can trace contamination issues, leading to long-term improvements.

Renewable Energy

Another increasingly impactful technology for beverage companies today is renewable energy. As climate issues become more prominent, consumer preferences lean towards sustainable companies and products, even if that means paying more for products. Switching to renewable power helps energy-hungry beverage factories adapt to this demand and protect the environment.

Because renewables such as solar and wind are technologies, not fuel sources, they will only become cheaper and more efficient over time. Consequently, switching to these technologies is becoming an increasingly viable option for companies. They can also reduce energy costs long-term, as facilities begin to generate their own power instead of buying it from the grid.

Additionally, growing climate urgency may lead to increased regulations around industrial energy sources. Shifting to renewable power now can ensure beverage companies minimize disruption from any changing legislation.

Virtually every industry today is undergoing a tech-driven transformation. Capitalizing on this movement means being able to separate the buzzwords from the technologies that hold the most promise. These five technologies are among the most impactful for beverage companies today. As their adoption grows, they could dramatically alter the face of the industry.

Kari Hensien, RizePoint
FST Soapbox

Food Crisis Backup Planning

By Kari Hensien
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Kari Hensien, RizePoint

We were collectively shocked by the Covid-19 crisis that disrupted the food industry. We didn’t see it coming and we weren’t prepared for the long-lasting, widespread repercussions of that crisis, including product and labor shortages, supply chain disruptions and record-setting inflation.

Many food businesses were reliant on certain suppliers, and if they couldn’t deliver necessary products, companies either had to go without or scramble to find an alternate solution. As an industry, we were reactive—not proactive—to the pandemic and the ensuing fallout.

Now that we have some perspective, a big takeaway is that food businesses need to have better backup plans to address supply chain disruptions, product shortages and delays. This is especially important because:

  • Extreme weather is causing crop failures, livestock deaths and suboptimal soil conditions, resulting in more world hunger. Extreme drought conditions are destroying produce out west, including in California, a region that grows significant amounts of produce to ship nationwide. The Midwest, which produces approximately three-quarters of our country’s corn supply, is facing the opposite problem, as frequent floods wash away precious soil. Europe’s record-setting heat is torching vegetation, while India is pausing exports because of a severe heat wave.
  • The ongoing Ukraine/Russian war is predicted to give rise to a “food catastrophe.” Our global food system relies on a few big food commodity exporters, and Ukraine and Russia are two of the biggest. Together, these two countries supply approximately 60% of the global sunflower oil production—a product that goes into hundreds of consumable goods. It is a significant threat to the global food supply that so many of these exports have stalled.
  • Soaring inflation and resulting record high food prices are putting food out of the reach of many, leading to a worldwide rise in food insecurity, leading to increased hunger and malnutrition. The number of food insecure people is predicted to grow globally from 440 million to 1.6 billion, and nearly 250 million people are facing famine.
  • The ongoing labor shortage is contributing to disruptions and food waste all along the supply chain. Crates of perishable foods are being left to rot in shipping containers, warehouses and trucks because there aren’t enough workers to get them safely to their final destinations.

Below are several steps food brands can take to address and prepare for these ongoing threats to the supply chain.

Use tech tools to manage your supply chain. Today’s digital solutions allow you to audit and evaluate your supply chain’s sustainability and resilience. These innovative tools can help you get a better handle on your supply chain by organizing supplier certifications into a system that offers better visibility and is easier manage.

Embrace sophisticated technologies. Advances in artificial intelligence (AI), robotics and other technologies may help solve some of our most pressing supply chain challenges. For instance, when the Suez Canal was blocked in 2021 it halted all shipments through that major passageway, causing a supply chain crisis. AI rerouted ships to avoid the blockage, so food deliveries could continue via a detour. AI can also monitor shipments to ensure safety and quality, notifying suppliers and buyers about any safety breaches.

The FDA’s New Era of Smarter Food Safety calls for a broader approach to food safety and traceability, and AI can help achieve those goals. Moving forward, AI will be instrumental in increasing transparency all along the supply chain, providing end-to-end visibility and predicting the path of foodborne outbreaks.

Develop back up plans. How are your suppliers pivoting to manage the simultaneous threats against our global food supply? How are they preparing for climate change? What will they do if they can’t get necessary produce from California, corn from the Midwest or grain from Ukraine? How will they recruit and retain enough labor to deliver necessary products safely to their final destinations? It’s smart to find backup suppliers, especially those closer to home, to ensure an uninterrupted supply of foods. Work with suppliers that are focused on solutions, safety and quality, and keep careful track of each supplier’s safety certifications.

Consider vertical farming. Increasingly, companies are looking for alternate supplier and agriculture solutions, such as vertical farming, which grows crops closer to their final destinations. Growing foods closer to their final destination helps reduce food deserts and safety risks, boost sustainability and minimize food wastage. Vertical farms are typically indoor climate-controlled spaces. These growing conditions protect crops from severe weather, and offer a viable solution to bypass a variety of current issues from the climate crisis to supply chain headaches.

Pivot to agroecological farming. Agroecological farming practices mitigate climate change and prioritize local supply chains. Using this approach, farmers adopt agricultural techniques based on the local area and its specific social, environmental and economic conditions. Agroecology focuses on sustainability, working to reduce emissions, recycle resources and minimize waste. Those that embrace this farming approach believe that traditional farming often faces—and contributes to—a variety of problems, including soil degradation and excessive use of pollutants. Intensive, traditional farming approaches typically focus on short-term output vs. long-term sustainability, which exhausts many natural resources, local resources and wildlife. Agroecological farmers adhere to strict standards that support animal welfare, fewer pesticides and antibiotics, healthier soil and no GMOs.

Be proactive. In hindsight, we should have been more proactive during the Covid-19 crisis, developing backup plans for the huge supply chain disruptions that were headed our way. Before the pandemic, we couldn’t possibly have anticipated the ramifications of a disrupted supply chain and we didn’t understand the need to have backup plans in place for alternative food sources and waste reduction. Today, we have a more realistic perspective and recognize the need to plan ahead for any eventuality.

Our food supply is being threatened by simultaneous crises—from climate change to war—so we must be proactive, prepared, resilient and flexible in developing a solid Plan B.

 

 

Bottle tops
FST Soapbox

Five Advances in Food Processing Machinery Driving Growth

By Emily Newton
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Bottle tops

Food processing machinery is experiencing some incredible innovations, from intelligent robots to energy-efficient motors for food and beverage processing. Adopting these emerging technologies in your food and beverage processing facility can provide valuable benefits, such as improved food safety, greater efficiency and higher productivity. Following are five advances in food processing machinery that are transforming the industry.

Next Generation Energy-Efficient Motors

Energy efficiency is a growing concern across all industries, and it’s not just about reducing carbon footprints. Cutting back on emissions due to power consumption is certainly important, but food and beverage companies can also experience monetary benefits from optimizing their electricity usage.

Subscribe to the Food Safety Tech weekly newsletter to stay up-to-date on the latest news and information on food safety.Today’s next-gen motors for food and beverage processing are becoming much more energy-efficient right out of the box. The rise of soft-start and variable frequency drive engines is playing a key role in these innovations.

Soft-start motors cause less stress on machinery by protecting devices from sudden power surges. They start up using a slightly lower, limited initial charge rather than a sudden full charge. This can be compared to waking up with versus without an alarm clock—the former involves waking up abruptly while the latter is less stressful. The result is that soft-start motors allow machinery to warm up more gently and ease into operation, rather than straining electrical components with a sudden influx of energy.

Variable frequency drive motors use much less energy than other motor options. Unlike variable speed drive motors, variable frequency drive motor technology is limited specifically to AC motors. A variable frequency drive allows an AC motor to change its speed by changing the frequency of the power going through the motor. A variable frequency drive is essentially a control system for machinery engines, allowing them to start up with a lower voltage drop, similar to soft-start motors, and the speed can be adjusted to fit the unique needs of specific devices and tasks.

These energy-efficient motors also tend to be smaller in volume and weight than their conventional counterparts.

Soft Robotic Grippers

Automation, including the use of robotics, in the food and beverage industry is already happening. These technologies can deliver significant benefit as businesses struggle to keep up with demand even with fewer employees. However, processing foods like pastries, fruit or bread can be difficult with robots because their stiff grippers crush soft items when trying to pick them up. Soft grippers solve this problem.

One soft gripper designed for handling delicate food items was inspired by octopi and squids. The rubber fingers inflate and deflate using pressurized air so they open and close to precise dimensions. The gripper is nimble enough to lift items as delicate as marshmallows.

Autonomous AI Robots

Not only can automation help companies struggling with labor shortages, it can also help improve food processing efficiency. Autonomous robots, often powered by AI, are incredibly efficient at performing repetitive tasks. They can get more done in less time with fewer mistakes compared to the average employee. Food processing companies can use these robots to perform repetitive, mundane tasks that don’t appeal to employees. Workers can then be reskilled, upskilled or reassigned to more engaging and important roles.

IoT Machinery Monitoring

The Internet of Things (IoT) makes food processing machinery more intelligent and inter-connected. IoT can be used in various ways in the food and beverage industry, but it is especially helpful for monitoring and optimizing operations on the manufacturing floor. Sensors collect and relay data to a central hub in real-time. That information can be used to inform automated systems or production timelines.

IoT sensors can reveal inefficiencies and bottlenecks in production, giving companies concrete goals to act on. They can be used to monitor the health of food processing machinery, allowing for predictive maintenance, which involves performing tuneups on equipment as soon as signs of a potential malfunction appear.

The agriculture industry is exploring IoT, as well. For example, farmers and water management companies are using it in conjunction with AI algorithms to improve irrigation systems, cut energy costs and improve water usage.

Automated Food and Facility Safety

Health and safety are among the foremost priorities for every food and beverage company. Technological advances are making it easier for companies to stay on top of health and safety measures.

For example, food processing and storing companies can use AI to autonomously monitor and regulate temperature, helping prevent the growth and spread of E. coli and other diseases. This is achieved using IoT thermostats that relay real-time temperature data to an AI algorithm, which keeps an eye on temps throughout the facility and makes adjustments as needed.

Food processing machinery is in the midst of some truly exciting advancements that are helping businesses in the industry provide better service, products and working conditions. Cutting-edge motors for food and beverage equipment allow companies to save money on energy costs, while next-gen robotics open the door to a wealth of automation possibilities.

With the help of AI and IoT, food and beverage companies can ensure their operations are running as smoothly as possible. There will certainly be more incredible advancements in food processing technology in the years ahead.

James Gunn-Wilkerson, CMX
Retail Food Safety Forum

The Future Is Now: AI Takes Journey from Supply Chain to Today’s Restaurant Kitchens

By James Gunn-Wilkerson
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James Gunn-Wilkerson, CMX

Futurist Ross Dawson has said that AI and automation will shape the future of work, and it also promises to transform our lives beyond the office. According to the World Economic Forum, when AI, which provides the ability to “enable devices to learn, reason and process information like humans,” is combined with Internet of Things (IoT) devices and systems, it creates AIoT. This super duo has the potential to power smart homes, smart cities, smart industries and even our smartwatches and fitness trackers, a market estimated by Gartner to be worth $87 billion by 2023. More importantly, this “interconnectedness” will change the way we interact with our devices as well as the way we will live and work in the future.

In the restaurant industry, we’re already seeing glimpses of this interconnectedness take shape, and in the past year, we’ve experienced major technological advancements that have transformed every facet of the way food establishments work. Reflecting on those advancements, I want to take a moment to share three areas of AI impact that are bubbling up in the restaurant sector in 2021.

1: AI-powered Intelligent Kitchens

From ghost kitchens to traditional kitchens, the “back of the house” continues to be a prime target for AI and automation. While great progress has been made, in many ways it seems like we’ve only scratched the surface when it comes to how far AI can take today’s restaurants. But every now and then, we hear examples of AI powering the future of our industry. For example, Nala Robotics, Inc. will be opening what it calls “the world’s first state-of-the-art intelligent restaurant” in Naperville, Illinois this year. The company says the AI-based robotic kitchen “can create dishes from any cuisine around the world, using authentic recipes from celebrated chefs”. A press release from Nala Robotics states that its flagship restaurant is taking “the first step in the food service industry with AI-powered service, addressing many of the issues affecting restaurant owners during COVID-19,” and it will “provide consumers an endless variety of cuisine without potential contamination from human contact.” This is the new frontier in intelligent kitchens, and it couldn’t have come at a better time, with the pandemic forcing restaurants to reimagine the way they do business.

2: AI-Driven Labor Shifts.

You can’t talk about AI in the restaurant industry without also having a conversation about the implications for the modern workforce. With AI in restaurant kitchens and beyond, the impact on the labor force is undeniable. By 2024, Gartner predicts “that these technologies will replace almost 69% of the manager’s workload.” But that’s not entirely a bad thing. Instead of manually filling out forms and updating records, managers can turn to AI to automate these and other tedious tasks. “By using AI…they can spend less time managing transactions and can invest more time on learning, performance management and goal setting,” Gartner adds.Managers can also use the extra time to focus more effort on the customer and employee experience. And indeed they should: In a recent Deloitte report, 60% of guests surveyed indicated that a positive experience would influence them to dine at a restaurant more frequently.

Looking at the impact of AI on labor at all levels, from the CEO to the entry-level wage earner, the shift, at its best, will be a transition to more meaningful—and less mundane—work. The evolution of humanity has taken us to the point we’re now at now, with food production and delivery processes becoming increasingly automated. This has been an evolution generations in the making. In an ideal world, everyone at every level of the organization should benefit from this new wave of technology. For example, automation can and should be used to open the door to new training and new opportunities for low-wage earners to learn new skills that elevate career paths, increase income and improve quality of life.

3: AI and Global Supply Chain Transformation

From the farm all the way to the table, AI is now poised to transform the global supply chain. From my perspective, the biggest impact will be around driving sustainability efforts. Restaurant and grocery brands are already beginning to leverage AI to forecast their food supply needs based on customer demand, leading to less over-ordering and less food waste to support sustainability initiatives. One company in this space, FourKites, is creating what it calls “the digital supply chain of the future.” Using real-time visibility and machine learning, FourKites powers and optimizes global supply chains, making them “automated, interconnected and collaborative—spanning transportation, warehouses, stores, trucks and more.”

In addition to predictive planning, more and more brands will start to use AI to create incident risk management models to identify trends and risks in the supply chain to determine whether bad or recalled products are originating from a specific supplier, distributor, or due to an environmental variable.With all of these changes, the need for comprehensive data standards will multiply as suppliers and distributors around the world work together to bring us produce and packaged food from all corners of the globe. Data standards will be critical to traceability and the exchange of critical tracking events and key data elements, and advances in data standards will power the meta-data needed to provide better insight for food quality and regulatory compliance, crisis management, and recalls—at scale.

Research firm Forrester states that, in the end, the greatest impact resulting from an investment in robotics and other technologies that automate operational tasks is improved customer experience (CX). “Most companies believe that investment in AI, automation, and robotics for engagement will decrease operational costs. While this is true, our research shows that the revenue upside from delivering better CX could deliver a greater impact on the bottom line over time,” Forrester states.

As a business engaged in digitizing and transforming supply chain operations, our team couldn’t agree with Forrester more. But we believe it will take striking the right balance between technology and the human touch to not only drive stronger CX, but to also create a world in which AI is implemented for the greater good—a world in which people, processes, business and technology all win.

Are Traasdahl, Crisp
Retail Food Safety Forum

Is Programmatic Commerce the Next Wave in Supply Chain Tech?

By Are Traasdahl
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Are Traasdahl, Crisp

While COVID-19 exposed disconnects in the food supply chain, it also served as an overdue catalyst for rapid technology adoption. Food manufacturers, distributors and retailers were forced to grapple with consumer behaviors that—previously expected to occur over five years— changed within about five weeks. Faced with unprecedented demand, channel shifts and rapidly changing consumer purchasing behaviors, forward-looking brands and retailers have started to transform their business models to become highly responsive and agile.

A new approach called “programmatic commerce” may be the key to faster market insights and pivots. Taking cues from past attempts to digitize the supply chain from end-to-end, programmatic commerce uses artificial intelligence (AI) and machine learning (ML) to connect and unify critical business data across food manufacturers, distributors and retailers using common retail portals, BI and CRM tools as well as other data resources and platforms.

With a real-time unified view of channels and activity, programmatic commerce has the potential to create fully automated trade processes to optimize production, inventory management, logistics, promotions and more for both upstream and downstream supply chain activities.

To achieve the potential of programmatic commerce, real-time or near real-time data sources must be easily integrated, unified and displayed. This is in stark contrast to previous attempts to create end-to-end supply chain visibility, which often required custom or manual integrations, had costly and lengthy implementation requirements and necessitated custom reporting.

The programmatic approach is already gaining traction, enabling retailers to leverage AI and ML technology to optimize supply chains. But the real value is in taking it one step further—to tap into rich customer data, understand rapidly changing consumer behaviors and ultimately—to predict and personalize shopping experiences at scale.

Tracking and Adapting to Evolving Consumer Journeys

Consumers increasingly demand greater choice, control, personalization and transparency and companies must continuously create, track and manage a 360º view of customers’ shopping journeys to stay ahead of these trends. Fortunately, real-time data and analytical capabilities are available to supply the critical information they need to implement a programmatic commerce approach.

Among the shifts companies must track as a result of COVID-19 is the explosion in online grocery shopping. In November 2020, U.S. grocery delivery and pickup sales totaled $5.9 billion and a record high 83% of consumers intend to purchase groceries online again, signaling this trend continues as the pandemic lingers on.1 By 2025, online grocery sales are predicted to account for 21.5% of total grocery sales, representing more than a 60% increase over pre-pandemic estimates.2 A permanent shift toward online grocery shopping can be expected as consumers’ shopping and fulfillment experience continues to improve.

For consumers still shopping in stores, the pandemic also drove switches in primary physical store locations. In the United States, an estimated 17% of consumers shifted away from their primary store since the start of the pandemic.3 This was driven by increased work-from-home, which eliminated commuting routes and made different store locations more convenient, including ones closer to home.

Given the multitude of changes impacting consumer journeys during the pandemic, it is imperative that companies track relevant purchase drivers and considerations of each purchase occasion, while also taking into account their recent shopping experience. This creates the need for consistent, seamless and relevant experiences across both digital and physical channels that aligns all touchpoints with the consumer as part of their “total commerce experience.”

Multiple retailers are already pursuing this approach in the hope of retaining their “primary store” status across the totality of their consumers’ shopping experiences. Walmart recently launched a new store format to help achieve “seamless omni-shopping experiences” for its customers through a digitally enabled shopping environment. Customers can use the Walmart app to efficiently find what they’re looking for, discover new products, check pricing, and complete contactless checkout.4 Data tracked on these customers can eventually be used to create personalized recommendations and in-store activations and assistance based on their purchase history and in-store experience.

Conversely, the “digital store” is also being reimagined to align with consumers’ in-store experience to create a seamless shopping experience. For example, personalized meal planning service The Dinner Daily now offers the ability for its members to order recipe ingredients directly from Kroger and other Kroger-owned stores through The Dinner Daily app.5 Integrated data from multiple shopping platforms and consumer touchpoints can provide food manufacturers and retailers with shopper profiles, consumer experiences, and purchase history along with inventory status and other inputs to ultimately build personalized customer experiences and enhance shopper loyalty.

Applying Programmatic Commerce to Deliver Personalization to Consumers

Once armed with real-time data in a uniform format from sources ranging from consumer search analytics to retailer promotional pricing, a programmatic commerce approach can provide companies with predictive understanding of demand and supply to optimize decision making from raw materials through production through retail or direct-to-consumer.

Using online grocery shopping as an example, consumer personalization can be delivered through the accurate prediction and display of items relevant to each shopper based on shopping history, preferences, current cart selections, and other inputs such as real-time availability, marketing promotions and more.

Innovations are already in the market, including Halla, a data science company that developed a grocery-specific personalization algorithm that works with grocery retailer e-commerce platforms to create smart recommendations based on understanding of individual shoppers’ product usage and preferences.6 Another example is the Locai Solutions digital grocery platform, which applies AI to personalize recipe recommendations based on consumer preferences and purchase history and determines ingredients and quantities needed for easy incorporation into their shopping cart.7

The Path Ahead: Accelerating Technology Adoption in the Food Industry

AI and ML are already reducing waste across supply chains and enabling consumer personalization. However, currently only about 12% of retail decision-makers feel they are very effective at providing these experiences to customers and only 10% have access to the real-time data needed to achieve this goal.8

Modern programmatic commerce platforms (see Figure 1) can effectively bridge information gaps, improve inventory and distribution to prevent shortages or overages and help companies be data-ready to meet actual demand. Beyond this, a programmatic approach unlocks the next stage of customer satisfaction and loyalty, personalizing the experience during and after the pandemic.

Programmatic Commerce Platform visualization
Figure 1. Programmatic Commerce Platform visualization. (Courtesy of Crisp)

References

  1. Bishop, D. (2020). Tracking Online Grocery’s Growth. Brick Meets Click.
  2. Mercatus. (2020). The Evolution of the Grocery Customer.
  3.  Briedis, H., et al. (2020). Adapting to the next normal in retail: The customer experience imperative. McKinsey & Company.
  4. Whiteside, J. (2020). Reimagining Store Design to Help Customers Better Navigate the Omni-Shopping Experience. Walmart.
  5.  Corke, R. (2020). Our Online Ordering Connection for Kroger is Here. The Dinner Daily.
  6.  Halla. (2016). Halla Grocery Solutions.
  7. Locai. (2018). Locai Meal Planning.
  8. Bluecore. (2019). Align Technology, Data, And Your Organization to Deliver Customer Value.

 

Megan Nichols
FST Soapbox

Four Influential Technologies Changing Food Manufacturing

By Megan Ray Nichols
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Megan Nichols

Some impressive technologies are not only impacting the food industry right now but will also have a huge impact in the future. As their use grows to be more prevalent, the industry will change to be smarter and more efficient, with continued improvements across the board.

1. AI and Advanced Robotics

While artificial intelligence and advanced robotics are two distinct technologies, they are frequently paired together. AI, and the data it digests, is used to command robots, allowing them to be more precise, more intelligent and more aware.

Most robots on their own are capable of completing only repetitive and clearly defined tasks. Throw something unique into the mix and they’ll either fumble or fail. However, when governed by data-based intelligence solutions like AI or machine learning, those robots become something incredibly advanced.

In the food industry, machinery and robots are leveraged to improve operations, further maintaining quality and efficiency, at affordable costs. They often work alongside human laborers to augment or enhance processes. They come with several unexpected benefits as well, such as much-improved safety for workers, faster and higher product output and consistent, reliable quality.

For example, JBS, one of the world’s largest meatpacking firms, deployed robotic butchers within its plants. The robots were used to slice more challenging meats, which reduced workplace injuries.

2. Automation

Automation stands alongside AI and advanced robotics, even incorporating those technologies to create a streamlined system. As of 2017, 73% of surveyed companies in the food and beverage manufacturing industry either had or were in the process of establishing automation within their facilities.

Many systems are designed to replace or enhance repetitive tasks, boosting their speed and accuracy, to significantly improve output, without incurring a loss in quality. It’s not just about hardware, like swapping a human laborer for a robot. It’s also achieved through software. Think supply chain management solutions that help plan for various events and experiences without human input.

When many of these technologies are used side-by-side, it strengthens their application and usability. As is true of advanced robotics, for example, AI can also be used to create more intelligent automation platforms. Instead of carrying out rote or simple tasks, they can be programmed to react and engage through any number of parameters. The system might slow production, for instance, based on a decrease in product demand. Or, it might swap to an alternate component or ingredient because of a shortage somewhere.

With the right controls and support, automation technologies are game-changing. With the global population growing and demands increasing more with each year, food manufacturers will look to streamline their operations and boost output in any way possible, and automation will be a go-to.

3. Digital Twins

Digital twins in food manufacturing are essentially simulated copies or a virtual representation of a physical system. That definition might seem confusing, but think of it as a clone that can be manipulated for testing and analytics.In other words, it is a twin of the actual system and information, in every sense of the word, albeit one that is more versatile and less vulnerable. It allows manufacturers and distributors to run simulations by feeding specific information into the system to identify patterns, recognize outcomes and much more.

As the systems and controls supporting the field become smarter and more digitized, digital twins in food manufacturing will find their way into product development, testing, post-production, distribution and nearly every other facet of the industry. It will become an integral component to not only understand what’s happening in the market but also for keeping up with the ebb and flow of supply and demand.

4. Blockchain

Even well before the pandemic, people had become much more conscious about the foods they consume. They want to know the origin of their goods and whether they’ve been sourced using safe, healthy and environmentally friendly methods. The problem with such demands is that, until recently, there haven’t been many solutions for increased visibility within the food supply chain.

Growing concerns for health are now a priority, and visibility is an absolute must. Blockchain technology is the answer, providing precisely the kind of visibility, efficiency, controls and collaboration that consumers want.

With this food manufacturing technology in place, someone could trace a head of lettuce back to its initial seeding. They can see who grew the plants and where, and which methods they used to mature the crop. Then, they can follow its journey to the store shelf.

How is such a thing possible? It all has to do with the technology. In its simplest form, Blockchain is a digital ledger or complete and digitized record of a particular data set. The data that goes in is added to something called a block, and as more is added, it is tacked on to the end of that block to create a long, linked record. Every bit of information is visible across the entire chain, hence the name blockchain.

Walmart is using the technology to track potential food contamination outbreaks. It empowers them to not just find the source but also find the many branches involved — like where goods might have been shipped and who may have purchased them.

Food Manufacturing Technology for the Future

While each food manufacturing technology discussed here is incredibly influential and will have a direct impact on the future of the industry, they are not the only solutions making waves. Some additional examples include:

  • Drones and automated delivery vehicles
  • 3-D printing for edible goods
  • Smart or precision agriculture
  • High-tech packaging
  • Smarter waste disposal and recycling

The takeaway is that technology is vastly improving the operational efficiency of the food supply chain, from farmers and manufacturers to the retail stores featuring goods on their shelves. There’s no right or wrong buy-in, as any one of these technologies can be used to streamline separate processes. The biggest challenge will be deciding what to upgrade first, especially when it comes to delivering high-quality, fresh goods in a prompt manner.

Checklist

2020 FSC Episode 2 Wrap: Pest Management and How Technology Is Transforming Business

By Maria Fontanazza
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Checklist

Last week we were joined by experts in pest management for Episode 2 of the 2020 Food Safety Consortium Virtual Conference Series. Although pest management may not be seen as the most exciting topic, all food plants are required to have an integrated pest management program. In addition, the digital transformation fast-tracked by COVID-19 is also driving innovation in the remote monitoring of pests.

Barney Debnam, global agriculture strategy lead at Microsoft kicked off the conversation with some key themes driving change within the global food system, which have also been accelerated by COVID: Geopolitical forces, consumerization, democratized biology, sustainability, shifting economics and food security. As technology continues to evolve and is adopted at a faster pace (think artificial intelligence and how accessible it is now), businesses will be able to transform their outcomes by becoming more predictive. The key technology enablers in the process include:

  • Internet of Things and edge computing
  • Advanced analytics
  • Artificial intelligence and cognitive computing
  • Graph technology
  • Blockchain
  • Digital workplace
  • Mixed reality

The most significant benefit of implementing technology such as remote monitoring into an IPM program is its ability to provide visibility and the data to back up what is happening in a facility.

Get access to the presentations and points discussed during this exclusive session by registering for the 2020 Food Safety Consortium Conference Virtual Series. Attendees will have access to upcoming sessions as well as the recordings of all sessions.