Bug Bytes

How Severe Weather Can Affect Stored Product Pest Control in Food Processing Facilities

By Shannon Sked, Ph.D., BCE
No Comments

Severe weather can increase stored product pest risks in food and beverage processing facilities by damaging building protections, disrupting routine sanitation, inspection and monitoring practices as well as causing an increase in stored product pest activity. While severe weather does not create stored product pest risks by itself, storm-related damage and operational disruptions can make existing pest activity harder to detect and manage and create conditions that are conducive to pest activity and survival.

Maintaining the processes we can control is essential. By reviewing the facility’s integrated pest management (IPM) program before storm season and verifying that protections remain in place afterward, processors can help protect ingredients, maintain audit readiness and prevent stored product pest activity from complicating recovery.¹ ² ³

Key Takeaways for Food and Beverage Processing Facilities

  • Stored product pests can threaten dry goods, ingredients and packaged products throughout the year.³ ⁴
  • Severe weather can disrupt stored product pest habitats and facility protections, while operational disruption can create gaps in routine pest prevention.¹
  • Pest management should be incorporated into a facility’s Pest Prevention Pre-Requisite as part of its FSMA Food Safety Plan.²
  • Pre-storm planning and post-storm inspections can help facilities identify changes before stored product pest activity becomes harder to manage.¹ ³

How Does Severe Weather Increase Pest Risk in Food Processing Facilities?

Severe weather can increase  stored product pest risks in food processing facilities by damaging structural protections, disrupting sanitation and monitoring routines, and changing outdoor conditions for stored product pests. For food and beverage processors in regions that face severe weather during the fall, pest prevention should remain part of preparation and recovery planning. Extreme weather can damage building materials and affect windows, roofs, machinery, cold-storage areas or HVAC systems. When outdoor stored product pest habitats are disturbed, these pests may also move toward commercial structures for shelter.¹

Stored product pests are a year-round risk within the supply chain, with higher pressures during warmer months and severe weather events.  They may already be present in ingredients, packaging, incoming shipments or overlooked areas of a facility. When severe weather disrupts normal operations, existing stored product pest activity may be more likely to go unnoticed. Long periods of rainfall followed by extreme heat or cold can also lead to an abundance of stored product pests.¹ ⁴ ⁵

During recovery, attention naturally shifts to property repairs and revised shipping or receiving logistics. If routine sanitation, inspections or monitoring are delayed, a small stored product pest issue may remain unnoticed longer than it otherwise would, allowing stored product pest infestations to grow within the facility.

Why Should Pest Control Be Part of a Pest Prevention Pre-Requisite?

In food and beverage processing facilities, a Pest Prevention Pre-Requisite is the structured pest management program used to help prevent, monitor, document and respond to pest activity as part of the facility’s FSMA Food Safety Plan. This approach treats pest control as an ongoing food safety program integral to facility operations.²

An evidence-based IPM program within a facility’s Pest Prevention Pre-Requisite defines how the facility prevents pest activity through cGMPs, monitoring, documentation and pest management. It connects the work of the pest management provider with facility practices such as sanitation, building maintenance, ingredient storage and employee reporting. Monitoring data, action thresholds and escalation plans can then guide the response when activity is detected through preventive control measures outlined in the plan.² ³ Orkin’s Food Safety Precision Protection™ program integrates pest prevention, monitoring, documentation and corrective action into a customized IPM approach designed to support food safety and audit readiness. As a national provider with local expertise, highly trained Orkin Pros can support multiple facilities after severe weather hits with consistent, reliable service.

The prerequisite also provides continuity when severe weather changes normal operations. Before storm season, facility teams can review known vulnerabilities, confirm monitoring procedures and determine how pest prevention practices will continue if storage or receiving processes change. After an event, the program provides a framework for recording damage, evaluating new conditions and verifying that existing protections are still effective.

What Are Stored Product Pests?

Stored product pests are insects that infest or feed on food-grade ingredients, commodities and goods as well as packaged food products in food processing plants and storage environments. Common examples include Indian meal moths, flour beetles, grain beetles and rice or granary weevils. These pests can enter packaging, contaminate or damage inventory and create compliance or operational concerns for food processing facilities.³ ⁴   Stored product pests cause significant adulteration and financial losses by contaminating food, causing products to be unfit for the supply chain.

The ingredients handled within a facility influence the types of pests it may encounter. Grain, cereal and flour products can be vulnerable to dry process stored product pests, such as several beetles and weevils. Nuts, dried fruit, spices and confections commonly attract warehouse beetles, cigarette beetles, drugstore beetles or Indian meal moths. Stored product beetles and moths may also infest green coffee, cocoa, chocolate and candy products.⁴

Signs of activity can appear in the food itself or in nearby storage and processing areas. Small, round exit holes in grain may indicate weevils or burrowing larvae of beetles and moths. Flour beetle activity can contribute to discoloration or an unpleasant odor. Indian meal moths may leave webbing in food products, while mature larvae may move onto walls or ceilings to pupate into the next generation of adult moths.⁴

The location where an insect is observed may not reveal where the problem began. Stored product pests can remain hidden in damaged packaging, older inventory or accumulations of grain dust. Product residue around conveyor rollers and transfer points can provide additional food and shelter. Spillage is a constant struggle to manage through sanitation, but spills are a critical source of resources for stored product pests. Stored product pests can also enter a facility through raw ingredient shipments or travel to other locations through the supply chain.⁴ ⁵

How to Help Prevent Stored Product Pests Before and After Severe Weather

1. Inspect and Restore Physical Pest Protections

Inspect the building before storm season, paying attention to windows, screens, roofs, gutters, exterior materials, HVAC areas and utility penetrations.  Areas that may not usually raise concerns can become weak spots that give pests an opening along the building exterior.  Work with your pest control provider and facility maintenance team to inspect all areas and address any existing damage to the facility’s exclusion measures, such as door sweeps and dock levelers. ¹ ⁵

After severe weather events, partner with facilities engineers to conduct a thorough inspection of the building’s integrity, looking for any signs of damage like standing water, air movement and light penetration in areas where it should not occur. These should be addressed immediately, even if temporary repairs are in place while a comprehensive facilities repair plan is developed. Clean up any standing water and debris that may have entered the facility right away.  Re-establishing effective sanitation and exclusion measures can greatly limit stored product pest threats. 1 5

2. Protect Ingredients and Packaged Products

Maintain best practices for ingredient storage after a severe weather event, particularly when products have been moved or storage areas have been affected.¹

  • Store products above floor level and provide enough space around inventory to support inspection.
  • Protect vulnerable grains and flour products by storing them in airtight containers when appropriate.
  • Prevent older products from remaining undisturbed for extended periods by following first-in, first-out practices.⁴ ⁵
  • Inspect incoming goods for pests and signs of pest activity.
  • Keep doors closed between shipments.¹ ⁵
  • Ensure the building is as secure as possible just before the weather event.
Pest management professional should inspect ingredient storage areas and provide recommendations to help prevent stored product pests. Image courtesy of Orkin

3. Maintain Sanitation and Moisture Controls

Maintaining sanitation and moisture control is critical to pest management, including stored product pests. Clean spills promptly and remove buildup around conveyor lines, transfer points and areas under or behind equipment. Even small amounts of residue can provide food for stored product pests.⁴ ⁵ In a post-storm audit, identify any areas where outdoor debris entered the facility and have these areas cleaned as soon as possible.

Moisture should also be limited. Remove standing water, inspect machinery for mold or mildew and check cold-storage areas for water accumulation. Leaking pipes, floor drains and produce-washing areas can support other pest pressures and create additional food safety concerns.¹ ⁴

4. Verify Monitoring and Response Procedures

Monitoring can help facilities identify patterns in pest activity, locate the source of issues and know whether treatments are working. After a severe weather event, verify that the monitoring program remains intact, especially where inventory or equipment was moved. Your pest control professional should conduct a full audit of the facility’s IPM plot plan to ensure that all equipment is still in place and functioning properly. Employees should also know how to report pest sightings or signs of pests like webbing, damaged packaging, exit holes in grain or unusual changes in a product’s appearance or odor.³ ⁴

Stored product pest programs may use species-specific pheromone or sticky traps to detect activity. Monitoring findings should be evaluated against established action thresholds and escalation plans so that responses reflect the pest species and level of activity observed.³ In the aftermath of a weather event,  any unusual pest activity should be documented, and immediate preventive controls should be put in place to eliminate introduced  stored product pests before they become established in the plant.

5. Document Changes and Coordinate With Partners

Documentation is an essential part of keeping food and beverage processing facilities audit-ready. Facilities should maintain a pest sighting log that records the date and time of each sighting, the pest identified and the actions taken in response. To provide a complete picture during an audit, each sighting should be paired with documentation showing the corrective measures implemented. If any changes are enacted in the equipment monitoring system, they should be reflected in an updated IPM plot plan for the facility.

Facilities should also keep detailed service reports from their pest management provider. These reports should document signs of pest activity, site vulnerabilities such as cracks or water leaks, the corrective actions taken and verification that those actions effectively resolved the issue. Together, pest sighting logs and service reports help support an audit-ready Pest Prevention Pre-Requisite. Digital reporting tools such as Orkin InSite®, which provides a comprehensive view of a facility’s pest management program in a convenient online dashboard, including any changes to the IPM plot plan, can help organize and maintain these records and support audit readiness.² ³

Schedule a post-storm inspection with the pest management provider to confirm that preventive measures remain effective. Coordination with shipping partners and building contractors can also help prevent temporary recovery measures from weakening the Pest Prevention Pre-Requisite.¹ ³

How Can Proactive Pest Management Help Food Processors Prepare for Storm Season?

The pest prevention pre-requisite of the Food Safety Plan is designed upon the foundation of proactive pest management. Proactive pest management as part of a pre-requisite program can help food processors prepare for severe weather by identifying structural vulnerabilities, reviewing stored product pest risks and establishing how essential prevention practices will continue if operations are disrupted.

After a storm, a coordinated inspection can determine whether building damage, moisture, relocated inventory or revised receiving procedures require changes to the IPM program. Documentation should reflect those findings and the corrective actions taken in response. Don’t forget to update the plan, along with validation documentation, for any corrective actions taken.

Severe weather may contribute to structural damage that creates gaps in a facility’s exclusion measures. Credit: Orkin Commercial

This approach helps keep pest management integrated into the facility’s food safety plan as part of the pest prevention prerequisite. By planning proactively and reassessing controls after severe weather, food and beverage processors can protect themselves against a range of pest pressures while reducing the chance that a year-round stored product pest risk becomes an additional recovery challenge.

Frequently Asked Questions About Stored Product Pests and Severe Weather

What are stored product pests? Stored product pests are insects, including certain beetles, weevils and moths, that target dry goods, ingredients and packaged food and food-related products. They can damage or contaminate inventory in food processing and storage environments.³

Does severe weather cause stored product pest infestations? Severe weather does not cause stored product pest infestations, but it can damage facility protections, affect pest environments and disrupt a facility’s routine prevention practices. Stored product pests are a year-round risk.¹ ³

What food products are most vulnerable to stored product pests? Grains, cereals, flour, nuts, dried fruit, spices, chocolate and other confections can attract different stored product pest species. The risk depends on the commodities, ingredients and finished products in a facility and how they are stored.⁴

What are common signs of stored product pest activity? Warning signs may include webbing, insects in or around products, small exit holes in grain, damaged packaging, discoloration or unusual odors. Indian meal moth larvae may also appear on walls or ceilings.⁴

How are stored product pests monitored? Pest management programs may use pheromone or sticky traps designed for specific pests. These stations are documented in an IPM plot plan and data is tracked for trend analysis. Monitoring data can be compared with action thresholds and escalation plans to guide an appropriate response.³

Recall
Beltway Beat

Beyond the Recall Count: A Leading-Indicator Framework for Measuring Food Safety System Health

By Santoshi Muriki
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Recall

The annual number of food recalls is a common way to judge the performance of the food safety system, but it is just as likely an increase is caused by improving data and communication capabilities as by worsening safety. This reflects the same trade of central bankers faced decades ago: No single, backward-looking stat tells a policy maker or an industry participant if a given system is healthy or in imminent failure today. The Fed doesn’t run the economy using solely the unemployment rate; instead, it monitors multiple leading and concurrent statistics so it can take pre-emptive action while a downturn can be “confirmed” in any single widely followed metric.

Here we propose just such a dual scoreboard, comprised of leading and lagging statistics taken from actual operations and the system’s output — as expressed through recall and outbreak incidents. The work is the first application of the concepts on top of a tier approach to supplier risk employed throughout a multi-supplier grocery distribution system and presented as a launch pad for further industry and regulatory comment.

1.The Problem with a Single Headline Number

When recall numbers get high there are two possible stories. One is that contamination, the nature of them is getting worse, there are more of them, they are being handled less responsibly. The second story is that your processes are working. It should be this, testing, verification of your supplier, tracking and a really rigorous verification program that catches a contamination at the receiving warehouse instead of at a retailer or finally when consumers get it home and this fact (which you are providing with a verifiable test that caught it before the goods got into the warehouse), it really should be incentivized.

However, if this contamination that you detected before the product gets into the warehouse causes an increase to a recall numbers that the consumer is seeing as failure, then you have incentivized that program to not detect the contamination, not perform the tests and so it has made your score look good on a single index scorecard, but you are actually not safe.

This isn’t just an imagined worry. If across the 1,000+ supplier network, one thing is universally reported in operations it is this: if the number of nonconformances increases, the most frequent response is that enforcement and inspections are improving rather than that the food supply is becoming riskier. Using the recall count on its own to indicate the health of a system undermines the visibility we are trying to engineer with preventative programs.

2. A Monetary Policy Analogy

Central bankers hit a variant of this a while back. Because inflation and unemployment are outcome measures-confirmable only after the fact and capable of revision-a policy regime anchored solely by them would be a policy regime always reacting to yesterday’s economy. For this reason, the Federal Reserve maintains what is now quite a long basket of measures, including leading indicators such as new orders, credit spreads and labor market churn, alongside the lagged outcome measures, so that policy can act on expected instead of confirmed economic conditions. No single number is being asked to bear this crucial burden alone.

Neither regulatory food safety governance nor in-company governance has always been as reliant on this discipline as it should be. Recall numbers and outbreak case counts are lagged outcome indicators, like an unemployment rate: they point out that a problem was experienced long after the operational decisions creating it were made. No system governed solely by examining these metrics will do anything but run the equivalent of an emergency room from 2007 to 2015.

3. A Paired Scorecard: Leading and Lagging Indicators

Here, we present a framework which links operational leading indicators, describing the day-to-day functioning of a prevention and verification system with lagging outcome indicators, describing what did or did not actually reach the consumer Table 1 shows an initial set of indicators derived from our experience in managing supplier compliance at scale.

Table 1.

No single row in Table 1 is sufficient on its own. A high verification completion rate plus an increasing root-cause recurrence rate would signal a program that is great at paperwork but poor at fixing the issues it is discovering. A decreasing time-to-corrective-action plus a flat risk-tier migration rate would signal a system that is neither catching problems nor making sure that those problems are mitigated. The power of framework is in reading those metrics as a body just as the federal reserve may look at prices, employment and credit data together instead of separately

4. Grounding the Framework in a Tiered Risk Model

The approach is not entirely theoretical. It builds on a risk-based tiered supplier compliance model designed to oversee compliance for a vast and diverse supplier population for food safety assurance, because one cannot scale manually or with a one size-fits-all verification process on one size of suppliers. The supplier. tiering is based on categories of products provided, previous compliance record and specific product hazards – and varies the frequency and rigor of documentation review accordingly. Deployment of that system realized significant operational improvements to include drastic reductions in manual follow-up, greatly reduced supplier onboarding times, and 100 percent compliance with required food-safety documentation.

Those tiering mechanisms also produce much of the raw data required for a leading-indicator scorecard: total tier verification completion, total time-to-corrective-action by tier and change in tier over time for suppliers. A national or sector-level scorecard would require less new data capture than that already produced by good supplier verification programs – including those that will exist under the FSMA Food Traceability Rule and those required under GFSI benchmarks.

5. Toward Implementation

A move from concept to action will require consensus on a handful of open questions, presented here as a point for discussion rather than a closed case. Definitions and denominators – how to come to consensus on what constitutes a ‘supplier,’ a ‘verification,’ and a closed ‘corrective action’ so that indicators are comparable across companies and, over time, across the industry. Reporting cadence – leading indicators are most useful when assessed frequently, possibly monthly or quarterly, with lagging indicators appropriate to annual assessment or triggered by events.

Aggregation and governance – should a sector level score card be held by a regulatory body such as the FDA, industry group such as the IAFP, or a public/private initiative and if so, how should supplier data be protected yet still be used in the aggregation.

Pilot the scoring card: A scorecard like this should be pilot tested at one specific slice of business for instance fresh produce distribution before applying it across all business as the indicators will be tested against actual operational and actual outbreak data rather than assumes to generalize.

6. Conclusion

One lagging number (unemployment or annual recalls count) was never meant to bear the burden of evaluating system-health, and so food safety governance can stop expecting it too. By coupling operational leading indicators, completion of verification, time-to-corrective-action, root-cause recurrence, and migration to and among risk-tiers, with lagging outcome measures, like recall severity and reduction of illness, one captures an image that is much more authentic than either single number and recognizes the transparency and speedy response of an effective preventive system.

The tiered risk model presented below illustrates that the underlying data is probably already available within well-managed supplier verification programs; what has not been provided until now is a common language for interpreting it. This paper aims at launching this language as a first draft and invites further refinement by authorities, the food sector and the academic community.

Editor’s Note: the author, Santoshi Muriki, Food Safety and Quality Assurance Manager, Affiliated Foods is presenting “Building Risk‑Based Supplier Compliance Systems for FSMA 204 and Beyond: Automation, Analytics, and Culture” This session will walk participants through a practical, end‑to‑end approach to designing and operationalizing a modern supplier compliance program that meets FSMA 204 expectations while reducing manual workload and strengthening supply chain resilience. Food Safety Consortium Conference: Agenda.

Supply chain

Towards Food Traceability Standardization: Data System Design Concepts

By John M. Ryan, Ph.D.
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Supply chain

While we are in the middle of another massive food recall exercise, many people are dreading having to implement a food traceability system as designed by the FDA in response to Food Safety Modernization Act requirements.  The FDA, after smoking some whacky weed, has burdened the food industry with a “well thought out” set of traceability rules.  Currently being delayed due to a lack of understanding, some traceability rules must surely be devised and implemented prior to the demise of the FDA regardless of how burdensome they might be.

The Goal: Create and tie lot codes to Key Data Elements (KDEs) at Critical Tracking Events (CTEs).

Food traceability is critical to the survival of innocent companies and products when the recall monster raises its head.

With so much confusion over the FDA’s FSMA food traceability requirements, companies need to begin considering standardization.  This is especially true for companies with long supplier lines.

Take for instance tomato sauce.  Boiled tomatoes may have salt, basil, garlic and other ingredients added during the cooking process and prior to bottling and labeling the sauce.  The FDA Food Traceability List below includes tomatoes and fresh herbs (basil, parsley and garlic) that are, in this case, input in a raw form prior to the cooking process.   All require identification of the specific harvest location, time and traceability lot number and all fall within traceability requirements.  From harvest, through cooling, into sorting, etc. these ingredients must be tracked.  A hundred cases of tomatoes harvested from the same field on the same day may be divided and shipped to five or more locations including distribution centers, stores or a farmer’s market.

For the tomato sauce under consideration, a kill step (cooking) is involved meaning that these Food Traceability List (FTL  Table 1) ingredients no longer need to be tracked under their original lot tracking number.  A new lot number is generated and tied to the original tracking numbers after the cook (blend) step.

It gets confusing and difficult early in the life of the tomato sauce.

The Food Traceability List

Food Traceability List Description
Cheeses, other than hard cheeses, specifically:
  • Cheese (made from pasteurized milk), fresh soft or soft unripened
 Includes soft unripened/fresh soft cheeses. Examples include, but are not limited to, cottage [1], chevre, cream cheese, mascarpone, ricotta, queso blanco, queso fresco, queso de crema, and queso de puna. Does not include cheeses that are frozen or previously frozen, shelf stable at ambient temperature, or aseptically processed and packaged.
  • Cheese (made from pasteurized milk), soft ripened or semi-soft
 Includes soft ripened/semi-soft cheeses. Examples include, but are not limited to, brie, camembert, feta, mozzarella, taleggio, blue, brick, fontina, monterey jack, and muenster. Does not include cheeses that are frozen or previously frozen, shelf stable at ambient temperature, or aseptically processed and packaged.
  • Cheese (made from unpasteurized milk), other than hard cheese[2]
 Includes all cheeses made with unpasteurized milk, other than hard cheeses. Does not include cheeses that are frozen or previously frozen, shelf stable at ambient temperature, or aseptically processed and packaged.
Shell eggs Shell egg means the egg of the domesticated chicken. Includes products (whether fresh or frozen) that contain raw, unpasteurized eggs as ingredients.[3]
Nut butters Includes all types of tree nut and peanut butters. Includes all forms of nut butters, including shelf stable, refrigerated, frozen, and previously frozen products. Examples include, but are not limited to, almond, cashew, chestnut, coconut, hazelnut, peanut, pistachio, and walnut butters. Does not include soy or seed butters.
Cucumbers (fresh)[4] Includes all varieties of fresh cucumbers.
Herbs (fresh) Includes all types of fresh herbs. Examples include, but are not limited to, parsley, cilantro, and basil. Herbs listed in 21 CFR 112.2(a)(1), such as dill, are exempt from the requirements of the rule under 21 CFR 1.1305(e).
Leafy greens (fresh) Includes all types of fresh leafy greens. Examples include, but are not limited to, arugula, baby leaf, butter lettuce, chard, chicory, endive, escarole, green leaf, iceberg lettuce, kale, red leaf, pak choi/bok choi, Romaine, sorrel, spinach, and watercress. Does not include whole head cabbages such as green cabbage, red cabbage, or savoy cabbage. Does not include banana leaf, grape leaf, and leaves that are grown on trees.  Leafy greens listed in § 112.2(a)(1), such as collards, are exempt from the requirements of the rule under § 1.1305(e).
Leafy greens (fresh-cut)[5] Includes all types of fresh-cut leafy greens, including single and mixed greens.
Melons (fresh) Includes all types of fresh melons. Examples include, but are not limited to, cantaloupe, honeydew, muskmelon, and watermelon.
Peppers (fresh) Includes all varieties of fresh peppers.
Sprouts (fresh) Includes all varieties of fresh sprouts (irrespective of seed source), including single and mixed sprouts. Examples include, but are not limited to, alfalfa sprouts, allium sprouts, bean sprouts, broccoli sprouts, clover sprouts, radish sprouts, alfalfa & radish sprouts, and other fresh sprouted grains, nuts, and seeds.
Tomatoes (fresh) Includes all varieties of fresh tomatoes.
Tropical tree fruits (fresh) Includes all types of fresh tropical tree fruit. Examples include, but are not limited to, mango, papaya, mamey, guava, lychee, jackfruit, and starfruit. Does not include non-tree fruits such as bananas, pineapple, dates, soursop, jujube, passionfruit, Loquat, pomegranate, and sapodilla. Does not include tree nuts such as coconut. Does not include pit fruits such as avocado. Does not include citrus, such as orange, clementine, tangerine, mandarins, lemon, lime, citron, grapefruit, kumquat, and pomelo. Tropical tree fruits listed in § 112.2(a)(1), such as figs, are exempt from the requirements of the rule under § 1.1305(e).
Fruits (fresh-cut) Includes all types of fresh-cut fruits. Fruits listed in § 112.2(a)(1) are exempt from the requirements of the rule under § 1.1305(e).
Vegetables other than leafy greens (fresh-cut) Includes all types of fresh-cut vegetables other than leafy greens. Vegetables listed in § 112.2(a)(1) are exempt from the requirements of the rule under § 1.1305(e).
Finfish (fresh, frozen, and previously frozen), specifically:
  • Finfish, histamine-producing species
 Includes all histamine-producing species of finfish. Examples include, but are not limited to, tuna, mahi mahi, mackerel, amberjack, jack, swordfish, and yellowtail.
  • Finfish, species potentially contaminated with ciguatoxin
 Includes all finfish species potentially contaminated with ciguatoxin. Examples include, but are not limited to, grouper, barracuda, and snapper.
  • Finfish, species not associated with histamine or ciguatoxin
 Includes all species of finfish not associated with histamine or ciguatoxin. Examples include, but are not limited to, cod, haddock, Alaska pollock, salmon, tilapia, and trout.[6] Siluriformes fish, such as catfish, are not included.[7]
Smoked finfish (refrigerated, frozen, and previously frozen) Includes all types of smoked finfish, including cold smoked finfish and hot smoked finfish.[8]
Crustaceans (fresh, frozen, and previously frozen) Includes all crustacean species. Examples include but are not limited to shrimp, crab, lobster, and crayfish.
Molluscan shellfish, bivalves (fresh, frozen, and previously frozen)[9] Includes all species of bivalve mollusks. Examples include, but are not limited to, oysters, clams, and mussels. Does not include scallop adductor muscle. Raw bivalve molluscan shellfish that are (1) covered by the requirements of the National Shellfish Sanitation Program; (2) subject to the requirements of 21 CFR part 123, subpart C, and 21 CFR 1240.60; or (3) covered by a final equivalence determination by FDA for raw bivalve molluscan shellfish are exempt from the requirements of the rule under § 1.1305(f).
Ready-to-eat deli salads (refrigerated) Includes all types of refrigerated ready-to-eat deli salads, including ready-to-eat deli salads that are frozen at some point in the supply chain prior to retail. Examples include, but are not limited to, egg salad, potato salad, pasta salad, and seafood salad. Does not include meat salads.

The tomato paste company must train and establish data input requirements for all suppliers and must assure that each supplier is in traceability compliance.  Compliance requires that each supplier and the tomato sauce company are all capable of supplying the FDA lot traceability data when any recall occurs.  The FDA, in turn, must store (electronic record keeping) take that data (spread sheet or whatever form) from all sources and somehow establish a traceability path.

The FDA cannot do that.  Someone must wonder how all this will eventually work.

The Need for Some Standardization

If you study the FDA FSMA Food Traceability requirements for any period of time, you will notice how similar requirements are repeated.  This repetition provides a basis for standardization.  Given a relatively large processor company with perhaps hundreds of suppliers and dozens of final products, the need to control and guide those suppliers in a consistent manner arises if any semblance of food traceability is to result.  Take for example the concept put forth by the illustration below.  A “Universal Input Screen” (Figure 1) sets the scene for entering food traceability data (in compliance with FDA rules) from any place in the supply chain.

Figure 1

By checking on the “Harvest” link at the top of the screen, the farm can enter data to record date, time location, lot number, product name/description, quantity, unit of measure, variety, name, and packing or cooling information.  The harvester can also record the shipper and date shipped, location of packing and other data.

Likewise a producer can, by clicking on the “Manufacture” button enter data relative to receipt from, transformation, new lot number, kill step (including date, verification and reference documents.)

If required, other input screens can be developed to incorporate such things as GS1 requirements or data (Figure 2).  GS1 identities are in use for hundreds of food products and many companies are in need of incorporating them into their own traceability systems.

In Case 1, the supplier has a kill step for a GS1 product in their process that ends traceability for the item prior to hand off to the parent production facility.  In case 2 only the parent facility has a kill step.  In both instances, maintenance and hand-off of GS1 identities is critical.

Figure 2 GS1 and Kill Steps

The system can be programmed so that whenever a “Critical Tracking Event” occurs, Key Data Element data may be entered and controlled by a smart programmer who sets up controls to only allow required data for any event.  For example, if the “Harvest” button is enabled, any data entry for “Transformation” would be unenabled.

Other controls can be established such as date checks, traceability lot number verification or comparison to Food Traceability List requirements.

Standardizing the use of a system like this would establish a single Traceability Plan for all suppliers as well as the parent company.  The ability to supply the FDA or any traceability effort would be available by entering a request using the “Traceability Data Summary Request” button.  Fast, simple and allows the computer to do the work.  Reduces response time to a minimum and maybe even saves lives and money.  That’s what food traceability should do.

Time to standardize!

Allergen Alley

Strengthening Grain and Ingredient Receiving Lines Against Fungal Contamination

By Emily Newton
No Comments

Grain receiving lines process millions of tons of raw material each year, serving as the first critical defense against fungal contamination. Oversights at this entry point can trigger costly rejections and irreversible health consequences when toxins infiltrate production runs. Mycotoxin test accuracy at the receiving stage determines whether contaminated grain enters the supply chain or is intercepted before reaching consumers.

The Growing Threat of Fungal Contamination in Cereal Production

The Food and Agriculture Organization estimates that 25% of cereal products globally harbor mycotoxins, though actual figures likely climb higher with varying detection standards and limit thresholds. When screening protocols fail to catch tainted batches, product quality deteriorates as compromised grain enters manufacturing streams. Entire harvests then face rejection or disposal, reducing food availability.

Most critically, health risks from mycotoxins remain largely irreversible once consumption occurs, as chronic exposure can lead to cirrhosis and hepatocellular carcinoma.

Fungal diseases also cause economic devastation, reducing cereal yields by 15% to 20% annually, though severe outbreaks can eliminate up to half of a harvest. Wheat growers absorbed particularly devastating losses in 2019 when fungal diseases claimed 22% of the global yield. Every percentage point of lost production translates to millions in unrealized revenue.

Environmental Factors Driving Fungal Spread

Storage environments create ideal conditions for rapid mold proliferation and toxin production when grain is at water activity levels between 0.90 and 0.995 and temperatures range from 15° to 25° Celsius — 59° to 77° Fahrenheit. Warmer conditions between 20° and 28° C specifically accelerate zearalenone production by Fusarium graminearum. This temperature sensitivity means seasonal fluctuations directly impact toxin accumulation rates in stored commodities.

Research across multiple agroecological zones identified 986 fungal isolates, with Aspergillus species accounting for 42.87% of the total, while Fusarium ranked second at 33.50%. An accurate aflatoxin test for grain becomes essential where Aspergillus thrives, while processors in Fusarium-prone regions prioritize detecting deoxynivalenol and zearalenone.

Financial Toll of Mycotoxins on the Agricultural Economy

Grain operations across the United States absorb nearly $932 million annually from crop losses and tainted harvests. Regulatory enforcement, verification infrastructure and quality control measures add another $466 million to prevent compromised products from reaching markets.

These combined expenses reach nearly $1.4 billion annually, ultimately affecting commodity prices throughout the supply chain. The economic impact extends internationally as inconsistent mycotoxin standards between nations create trade barriers that reduce international commerce and limit market access for grain exporters.

Harmonizing global verification requirements could unlock more than $6 billion in additional trade for cereals and nuts. Processors maintaining rigorous protocols at receiving lines position themselves to meet the strictest international benchmarks and capture premium market opportunities.

Overcoming Challenges in Mycotoxin Detection and Quality Control

Operations meeting compliance rely on detection technologies far more sophisticated than traditional methods, which lack the necessary speed and sensitivity. One study shows that combining multiplex polymerase chain reaction and liquid chromatography with tandem mass spectrometry allows rapid and accurate detection of mycotoxigenic species across large volumes while maintaining precision.

These advanced methods must meet rigorous regulatory standards. The U.S. Department of Agriculture (USDA) Federal Grain Inspection Service requires three separate analysts to extract seven distinct samples during validation trials. At least 95% of test results from these 21 total extractions must fall within acceptable ranges.

Kits are also evaluated using naturally contaminated corn at targeted aflatoxin concentrations of 5.0, 20, 100 and 300 parts per billion. Only systems delivering precise results across this concentration spectrum earn FGIS approval.

Implementing Accurate Testing Solutions for Regulatory Compliance

Fungal infiltration risks extend beyond storage areas into finished consumer products. According to biotechnology company Charm Sciences, “Mycotoxin organisms entering the manufacturing process of baked goods can adversely affect human health and reduce shelf-life. These concerns are becoming more prevalent as demand increases globally for more whole-grain usage.”

Recognizing these downstream implications, quality control managers prioritize precision at every checkpoint. To meet this need, industry leaders like Charm develop systems certified to mandatory USDA Federal Grain Inspection Service standards. This certification ensures diagnostic tools achieve the sensitivity required for regulatory thresholds while maintaining the exactness international buyers demand. Ultimately, these tests provide manufacturers with the assurance that their grains are safe to use as raw materials in production.

Operations equipped with FGIS-approved systems reduce the risk of false negatives that allow tainted grain to enter production streams and compromise mycotoxin test accuracy.

Best Practices for Securing Receiving Lines and Storage

Preshipment documentation should include harvest dates, storage conditions and previous screening results. Visual inspection provides the first alert when discolored kernels or musty odors signal fungal activity, while representative sampling from multiple shipment points captures toxins that concentrate unevenly.

Once stored, automated sensors enable quality teams to pinpoint conditions that favor fungal growth before contamination develops. Immediate corrective action becomes essential when readings approach critical thresholds, and grain rotation prevents batches from sitting long enough for mold to proliferate. Detailed records of conditions, results and actions support continuous improvement.

Frequently Asked Questions

The same questions arise consistently when quality control managers evaluate contamination risks and develop prevention strategies. Clear answers help processing centers implement more effective protocols.

Why is fungal contamination a major concern for grain receiving lines? Receiving lines are the final checkpoint before grain enters production systems, so toxins that pass through at this stage can affect entire batches and force costly recalls. Health hazards from mycotoxin exposure remain largely irreversible, making prevention at the point of entry essential for protecting consumers and maintaining brand reputation.

How does mycotoxin contamination impact the agricultural economy? Direct crop losses in the United States exceed $930 million annually, while regulatory compliance and verification add nearly $470 million in additional costs. International trade also faces barriers due to inconsistent benchmarks across nations, though operations that maintain rigorous screening avoid these losses and access premium markets that demand verified quality.

An accurate aflatoxin test for grain becomes a competitive advantage rather than simply a compliance requirement.

What are the most effective methods for detecting mycotoxins? Advanced molecular techniques combined with analytical procedures deliver both speed and precision for high-volume operations. Systems must meet USDA Federal Grain Inspection Service criteria, requiring that 95% of results fall within acceptable ranges across multiple analysts and concentration levels.

Certified solutions provide the sensitivity needed to detect toxins at regulatory thresholds while processing samples quickly enough to avoid bottlenecks at receiving lines.

Safeguarding the Future of Grain Handling

Receiving line vigilance remains the most cost-effective strategy for preventing toxins from entering the food supply. Investment in systems that meet rigorous regulatory criteria protects operations from costly recalls while ensuring the mycotoxin test accuracy buyers demand. Quality control begins with the first sample at the receiving dock.

Ghost Kitchens and Food Traceability: Understanding Food Safety Responsibilities in a Reinvented Operating Model

By Jeremy Schneider, Johnna Hepner
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The food service industry has undergone significant transformation since the COVID era, and few innovations have evolved as rapidly as the rise of ghost kitchens. Whether operating as delivery-only restaurants, virtual brands, commissary kitchens, multi-branded sites, or shared commercial kitchen spaces, ghost kitchens have allowed for new opportunities for food entrepreneurs while simultaneously introducing unique food safety and traceability challenges.

As regulators, customers, and supply chain partners continue to increase their focus on transparency and traceability, ghost kitchen operators must understand how food safety responsibilities apply to their business and where risks may exist within their operation. While the operating model may be different, the food safety expectations remain the same.

What is a Ghost Kitchen?

A “ghost kitchen” is generally defined as a food preparation facility that produces meals for off-premises consumption, often through third-party delivery platforms, without a traditional dine-in experience.

These operations can take several forms, including:

  • Single-brand delivery-only restaurants.
  • Virtual restaurant brands operating out of existing restaurants.
  • Shared commissary kitchens housing multiple operators.
  • Centralized production kitchens supplying multiple delivery concepts.
  • Hybrid models supporting both retail and delivery operations, which may or may not include virtual or branded concepts.

While these models offer operational flexibility, reduced overhead costs, and open the opportunity to significant new revenue streams, they also create additional complexity when it comes to supplier management, ingredient traceability, allergen control, and recall readiness.

Why Traceability Matters in Ghost Kitchens

Traditional restaurants often have relatively straightforward ingredient flows. Ingredients arrive, are prepared, served, and consumed at a single location.

Ghost kitchens, however, frequently involve multiple brands operating from one facility with shared storage areas and preparation equipment, common ingredients used across several menu concepts, a variety of delivery providers, and central commissaries supplying multiple locations.

This complexity increases the importance of maintaining accurate records that identify:

  • What ingredients were received
  • Which suppliers provided them
  • When products were received
  • How products were used
  • Which menu items contained those ingredients
  • Where finished products were distributed
  • Enhanced requirements outlined within FDA’s FSMA 204 regulations.

Without adequate traceability records, identifying affected products during a food safety incident can become extremely difficult.

Supplier Approval is More Important Than Ever

Many ghost kitchen operators focus heavily on speed and convenience when sourcing ingredients. However, rapid growth can sometimes outpace supplier verification processes.

An effective supplier approval program should include:

  • Approved supplier lists
  • Supplier food safety documentation
  • Third-party audit verification
  • Certificates of Analysis (COA) when appropriate
  • Ingredient specifications
  • Recall and crisis management procedures.

This becomes particularly important when multiple virtual brands rely on common ingredients. A single supplier issue may impact numerous menu offerings simultaneously.

The Recall Challenge for Ghost Kitchens

One of the most significant food safety concerns for ghost kitchens is recall execution.

Imagine a scenario where a contaminated ingredient is used across six virtual restaurant brands operating within the same facility. The affected ingredient may have been incorporated into dozens of menu items sold through multiple delivery platforms over several weeks.

Questions operators must be able to answer include:

  • Which supplier provided the ingredient?
  • What lot codes were received?
  • Which menu items contained the affected ingredient?
  • Which brand(s) utilized the ingredient?
  • During what dates the ingredient was used?
  • How much inventory remains on-site?

The ability to answer these critical questions rapidly can significantly reduce the scope of a recall and help protect consumers.

The Missing Ingredient: Connected Information

One of the biggest misconceptions about traceability is that organizations simply need better software. In reality, most ghost kitchens already have technology. They use procurement systems, inventory platforms, POS systems, kitchen management software, supplier portals, delivery applications, and food safety systems.

The challenge isn’t that the information doesn’t exist. The challenge is that it often lives in disconnected systems owned by different organizations.

A single meal may involve ingredients from multiple suppliers, inventory managed in one application, orders placed through another, delivery fulfilled by a third-party platform, and customer information maintained somewhere else entirely. During a food safety event, operators must quickly connect those pieces together.

The future of traceability in foodservice won’t be defined by replacing existing systems. It will be defined by connecting them, allowing information to move securely between suppliers, operators, delivery partners, and customers while each continues using the technology that best supports its business.

FSMA 204 and Ghost Kitchens

The FDA’s Food Traceability Rule (FSMA Rule 204) has largely focused industry attention on additional traceability requirements for foods appearing on the Food Traceability List (FTL). While many ghost kitchens may not fall directly under all aspects of FSMA 204, operators should pay close attention to how their suppliers and supply chain partners are implementing enhanced traceability systems.

As traceability requirements expand throughout the food industry, businesses that maintain strong receiving records, inventory controls, and ingredient tracking systems will be better positioned to meet customer, regulatory, and supply chain expectations. Many ghost kitchens already utilize digital ordering and inventory management platforms, making them well-positioned to leverage technology for improved traceability. The opportunity isn’t simply to digitize more processes. It’s to ensure the information already being captured can be shared quickly with trading partners, customers, and regulators when needed. Traceability becomes significantly more valuable when it moves beyond compliance and supports day-to-day operations, supplier collaboration, and faster decision-making.

Food Security in Mind

Ghost kitchens frequently receive orders and pickups from multiple delivery services and this can significantly increase food security risks.

Challenges often include:

  • unknown drivers and companies
  • different requirements for handling
  • multiple menu concepts using different handling expectations, or,
  • food packaged in a way that does not protect it from adulteration

Companies should implement processes that protect food during transit from the ghost kitchen to the customer. This often includes tamper evident packaging, external packaging, and other deterrents that limit driver access.

Looking Ahead

Ghost kitchens represent an exciting evolution within the foodservice industry, but they are not exempt from the food safety responsibilities required of their traditional counterparts. In many ways, the complexity of shared facilities, virtual brands, and centralized production models makes robust food safety and traceability programs even more important.

As consumer expectations for transparency continue to increase and regulatory requirements evolve, ghost kitchen operators that invest in supplier management, traceability systems, allergen controls, and recall readiness will be better positioned to protect their customers and their brands.

The question is no longer whether traceability matters in foodservice. The question is whether your operation can quickly identify where ingredients came from, where they were used, and what actions need to be taken when something goes wrong.

 

Audit

The Behavior Problem Behind Your Audit Failures

By James Glover
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Audit

Food safety audit failures are behavior problems, not protocol problems. According to AIB International,1 the most common audit findings share a consistent thread: employees who know the correct protocols but don’t consistently follow them. Facilities don’t fail because they lack documentation. They fail because employees abandon protocols when deadlines are tight, supervisors are elsewhere, and shortcuts seem harmless.

FDA inspections occur every 3-5 years.2 The behaviors that cause failures happen every day.

The Top Audit Failure Patterns

AIB International’s research1 identifies the most frequent audit failures as employee behavior issues:

  • Pest activity from inconsistent monitoring and program follow-through
  • Inadequate cleaning when staff rush or abbreviate procedures
  • Pesticide and chemical control lapses from untrained handling or off-label use
  • Food safety plan gaps when documented procedures aren’t followed
  • Equipment and utensil issues from deterioration and neglected maintenance

Each of these looks like a knowledge gap. It isn’t. Employees know what the protocols require. The problem is consistent follow-through under real conditions.

Why More Training Won’t Fix This

Compliance training teaches information, not habits.

Research on habit formation3 shows that building automatic behaviors takes approximately 10 weeks of consistent practice. Most compliance programs compress everything into a few hours or days—nowhere near the timeline required for lasting behavior change. The forgetting curve compounds the problem:4 without reinforcement, most training content is gone within a month.

Facilities fix the immediate violation, update documentation, and wait for the next audit. Without changing the underlying behaviors, the same findings resurface.

That’s not a training failure. It’s a design failure.

Embedding Safety Into Daily Work

Lasting compliance requires training that builds habits during actual operations, not separate training events.

Rather than pulling employees out for classroom sessions, an effective approach delivers short, specific practice activities during regular work. Consider chemical storage compliance. Instead of a presentation on protocols, an employee receives an activity like: “During your next chemical walkthrough, verify that every chemical in your area is stored in its correct location and labeled properly. If anything is out of place, correct it and document what you found before you leave the area.”

The activity takes less than a minute to understand. It creates immediate practice under the exact conditions where protocol adherence eventually breaks down. That authentic context is what builds habits that persist when no supervisor is present.

Personalization helps produce genuine behavior change, not just checkbox exercises. Research on behavioral skill development5 consistently shows that relevance to an employee’s actual role and work environment dramatically improves adoption. A line supervisor needs activities around monitoring and escalation. A maintenance technician needs activities integrating safety checks into repair tasks. A new hire needs foundational activities. An experienced worker needs activities addressing complex scenarios. Generic training treats everyone the same. Effective training doesn’t.

For inadequate cleaning, an activity might be: “Before signing off on your next sanitation log, walk the line and verify one piece of equipment yourself before you sign—not after. Note whether it met the standard or needed attention.”

These activities require no additional equipment or scheduling. They happen during work employees already do, with intentional focus on the specific behaviors that prevent audit failures.

Measuring What Actually Matters

Completion rates and test scores don’t predict audit performance. Behavior change does.

Before launching a training initiative, establish baseline measurements by surveying both employees and their direct supervisors. Ask specific questions about the frequency of safety behaviors, confidence following procedures under production pressure, and understanding of why each protocol matters. After a sustained practice period, repeat those same assessments and compare.

Supervisor observations provide the most valuable validation. When shift leaders report that employees complete monitoring steps without prompting, maintain storage compliance between audits, and finish documentation on their own, you’re capturing the Level 3 behavior change that directly predicts audit outcomes. Connect those behavioral improvements to results: track violations across audit cycles, measure the frequency of repeat findings, and document the time required for corrective actions.

Compliance as Competitive Advantage

Audit failures are expensive. Beyond the audit and re-audit fees themselves, facilities absorb the cost of remediation, corrective documentation, and business disruption—and the deeper cost is the cycle that repeats when daily behaviors don’t change.

Facilities that break that cycle gain something beyond avoided costs. Following protocols consistently reduces incidents, accelerates certifications, and builds a workforce that treats compliance as automatic rather than effortful. Your employees already know what they should do. Give them the practice they need to do it consistently.

References

  1. AIB International. “The Top Five Reasons Manufacturers Fail Audits.” https://blog.aibinternational.com/the-top-five-reasons-manufacturers-fail-audits
  2. U.S. Food & Drug Administration. “How Does FDA Prioritize Domestic Human Food Facility Inspections?” https://www.fda.gov/food/inspections-protect-food-supply/how-does-fda-prioritize-domestic-human-food-facility-inspections
  3. Lally, P., et al. “Making health habitual: the psychology of ‘habit-formation’ and general practice.” British Journal of General Practice, 2012. https://pmc.ncbi.nlm.nih.gov/articles/PMC3505409/
  4. Murre, J.M.J., & Dros, J. “Replication and Analysis of Ebbinghaus’ Forgetting Curve.” PLOS ONE, 2015. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0120644
  5. Glover, James. “Leverage The Science Of Behavior To Improve Leadership Development.” Forbes, July 21, 2025. https://www.forbes.com/councils/forbeshumanresourcescouncil/2025/07/21/leverage-the-science-of-behavior-to-improve-leadership-development/

Beyond the Survey: What Supplier Compliance Behavior Reveals About Food Safety Culture — Before It Becomes a Recall

By Santoshi Muriki
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Most food safety culture assessments still lean on annual surveys and self-reported audit responses — snapshots of what people say, taken once or twice a year. Supplier compliance behavior tells a more current story: how fast a vendor answers a document request, how often the same corrective action keeps coming back, and how long a supplier sits in an at-risk tier before anything changes. This article lays out a practical way to read that behavior as a culture signal, based on firsthand work redesigning a risk-tiered supplier verification system across a network of more than 1,000 suppliers.

The Blind Spot in How We Measure Culture

Food safety culture finally has a seat at the leadership table. GFSI’s latest position paper defines culture as the shared values, behaviors, awareness of risks and organizational learning that should be measurable and continuously improved, not just part of crisis communication1. That’s progress. The problem? The tools most organizations use to measure food safety culture haven’t kept up with the definition.

Ask any quality team how they’re measuring culture, and you’ll get some variation on a survey: a yearly questionnaire, a maturity scale, an audit-tied score, a self-assessment. These tools are valuable in many ways, but they all suffer from the same structural limitation. They offer a snapshot of the present, and a representation of what someone has been encouraged to claim, not a reliable indicator of their past and future behavior.

One recent systematic review of food safety culture questionnaires found that respondents can suffer from lack of time or clarity to provide valid responses, and that survey questionnaires capture biased accounts rather than the actual behaviors they purport to represent2. Other industry experts and researchers have voiced the exact same concern about survey results, pointing out that they represent recency bias and can create an impression of a food safety culture that differs from a company’s long-term, lived reality3.

This isn’t to say these instruments are useless. It simply means they answer a more specific, and often more limited, question than they are often perceived to answer. They provide insights into a food safety organization’s intentions or public image. They do not accurately or reliably assess what happens in a food supply chain when no one is there to fill out a form.

Behavior Is Harder to Fake Than a Survey Answer

This is where it all goes off the rails: Many existing compliance platforms are already leveraging a treasured trove of behavioral data on an ongoing basis, and it has zero to do with a survey. Supplier verification programs generate tons of it, as a matter of course.

Under the FSMA Foreign Supplier Verification Programs rule, for example, importers are expected to assess risk and performance on a continued basis and to maintain verification records,4 but regardless of whether the rule applies to a particular supplier, there is an underlying obligation that drives exactly the kind of evidence a culture survey never can: a history-complete with timestamps-of how a supplier acts when it is called to task in compliance.

That history might include things such as: How long it takes for a supplier to respond to an information request (e.g. Requesting an updated COA, corrective action response, and updated specification). Whether it appears to take two rounds of corrective action on a single nonconformance issue. How long does a supplier remain in at-risk status before its rating changes. Whether a serious incident is resolved before it becomes a near-miss or an open hold.

These aren’t opinions; they are objective records that the supplier produces because it had to, not because anyone asked a question that someone felt obliged to answer honestly.

Table 1 below shows how to interpret those kinds of signals and what happens typically when you don’t.

What This Looked Like in Practice

One of the most useful first observations we had during the process of redesigning an automated, risk-tiered system for verification of a supplier network of over 1,000 suppliers was entirely unrelated to tiering logic itself. This was an observation related to the movement (or lack thereof) of suppliers through the system over time.

A few of our suppliers seemed to continually generate the exact same corrective action, closed and reopened using slightly different phrasing. In terms of system reporting, each of these corrective actions were closed. The underlying problem is that it is simple as an allergen changeover step or a labeling control never actually gets fixed. It wasn’t reflected by tier status because our current tiering is dependent on the open/closed status of the corrective action, not the recurrence of the same underlying cause.

Once we began to also track the recurrences – a single nonconformance code against a single supplier within a specified period of time – we observed a pattern, not necessarily derivable from a survey: there was a select group of suppliers with a disproportionate number of recurrences, and a select group of suppliers which seemed to be consistently slower at responding to basic document requests than the remainder of the network. These two are not two different issues; they’re just two perspectives of the same underlying behavior.

This reframe altered the escalation process significantly; instead of escalating a supplier after a single audit or missed document request deadline, they now escalate automatically, prior to the hold, because they have two correlated issues.

From Lagging to Leading: Making the Shift

This difference matters because most food safety teams’ already existing metrics are backward-looking, they measure what’s already happened. Complaint totals and audit scores don’t predict whether we failed. Data from audits, complaints, and recalls tell us about the past, not what’s next5. They don’t give warnings about repeated mistakes.

Conversely, leading indicators were designed to signal what’s about to happen6. And supplier behavior is among the most readily available, and currently ignored, sources of leading intelligence organizations possess without purchase.

This shift in practice is achievable without new software. It just requires a new attitude toward the information organizations already possess:

Instead of, “Has the corrective action been closed?” the questions becomes, “Have these specific nonconformances ever come up for this supplier before-and if so, how often?”

Instead of, “What’s the supplier’s current tier?” the question is, “How long has the supplier been in this tier-is this time frame unusual?”

Instead of, “Was the audit finding addressed?” the question is, “How long has the closure of these findings taken relative to what other suppliers take on these same issues?”

Instead of, “Was the escalation resolved?” the question is, “What did it take for resolution to happen-and did that resolution occur before or after the occurrence of a near-miss?

These aren’t complex questions. Many compliance systems have this information at their disposal; it just is not being pulled to highlight trends because the reporting mechanisms were created to track status, not behavior.

Culture Shows Up in the Data You Already Have

Your survey is how you learn what your organization and its suppliers think about food safety, one to two times a year. Your supplier’s compliance behavior is what they do, day in and day out, because of the verification activity that is mandated by everyone anyway. It does not replace a culture survey, root cause analysis or a GFSI-based framework – it gives them an earlier, less easily “gamed” input signal.

The suppliers who get ahead of food recalls related to suppliers, usually aren’t those who had the most eloquently written survey.

They usually are the organizations who recognized a trend in response times, frequency and tier status, many months before a lab or customer alert became the warning. They aren’t just sitting there in some database; someone simply failed to connect the dots as culture, not forms.

References

  1. Global Food Safety Initiative. “A Culture of Food Safety,” Position Paper, Version 2.0. GFSI, March 26, 2026.
  2. Wang, Y., et al. “Measuring Food Safety Culture: A Systematic Review of Questionnaire Dimensions and Validation Practices.” Comprehensive Reviews in Food Science and Food Safety, 2026.
  3. Alliance to Stop Foodborne Illness. “Assessing Food Safety Culture: What Works Best?” stopfoodborneillness.org, March 2026.
  4. U.S. Food and Drug Administration. “FSMA Final Rule on Foreign Supplier Verification Programs (FSVP) for Importers of Food for Humans and Animals.” FDA.gov.
  5. LRQA. “Food Safety Performance Indicators.” LRQA.com, March 23, 2022.
  6. SafetyChain. “Food Safety KPIs: The Six Leading Indicators.” SafetyChain.com, June 4, 2026.
  7. FoodSafetyTech. “Effective Root Cause Analysis for CAPA Management.” FoodSafetyTech.com, Dec. 5, 2023.

 

Why Automated Data Management is the Foundation of Preventative Food Safety Testing

By Emily Newton
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The modern food industry operates under an increasingly stringent mandate to prevent contamination before it occurs rather than react to incidents after they happen. This shift requires manufacturers to adopt robust, automated data management systems that transform testing protocols from reactive checkpoints into proactive risk mitigation tools.

Automated data management serves as the critical infrastructure that enables preventive food safety programs, turning raw test results into actionable intelligence to protect consumers and preserve brand integrity.

The Regulatory Shift Driving the Need for Better Data

The regulatory landscape has pushed food safety programs toward documented prevention, verification and risk-based controls. The Food Safety Modernization Act (FSMA) shifts focus from responding to contamination to preventing it, demanding a more rigorous, data-driven approach to compliance that manual paper-based systems cannot support.

FSMA introduced the Hazard Analysis and Risk-Based Preventive Controls (HARPC) framework, which requires manufacturers to proactively identify and control potential hazards throughout their operations. Unlike the older Hazard Analysis and Critical Control Points model, HARPC expands beyond critical control points to encompass the entire production environment.

Facilities must now document preventive controls, monitor their effectiveness and maintain comprehensive records that demonstrate compliance. Automated data management systems provide a practical way to meet these expanded requirements while maintaining operational efficiency.

Defining Data Integrity in Food Manufacturing

Data analytics interface. Photo by Deng Xiang on Unsplash

Not all data holds equal value in a regulatory environment. Data integrity refers to the completeness, consistency and reliability of information throughout its life cycle. Quality control managers rely on the ALCOA+ principles to evaluate their data systems, which demand that records be attributable, legible, contemporaneous, original and accurate. Without integrity, data becomes not just useless but dangerous, creating a false sense of security that can mask emerging contamination risks.

Digital transformation has become essential for achieving true data integrity in manufacturing environments. Manual logging systems introduce human error, transcription mistakes and after-the-fact entries that undermine the contemporaneous requirement.

Companies like SafetyChain demonstrate how facilities can transition from paper-based workflows to digital systems that capture real-time data through mobile devices. The platform replaces manual logs with digital forms and automated notifications, ensuring that quality control teams document deviations as they occur.

What Are the Main Advantages of Using Software for Food Safety Data?

Food safety software platforms centralize testing data, eliminate transcription errors and accelerate response times when results fall out of specification.

Environmental monitoring systems like Charm Sciences’ Charm eBacMap capture contamination patterns over time through trend visualization, revealing how issues evolve across testing cycles rather than showing isolated snapshots.

This temporal perspective helps quality teams distinguish between one-time incidents and systemic problems, enabling more targeted interventions. Additional capabilities include streamlined audit preparation, real-time alert systems and supplier compliance tracking.

1. Streamlined Compliance and Audit Readiness

Analysis using a laptop and paper. Photo by Scott Graham on Unsplash

Automated systems dramatically reduce the time and effort required to prepare for regulatory audits. Quality assurance managers who rely on paper logs must manually collect records from multiple locations, verify their completeness and compile them into coherent reports.

This process can take days or weeks, pulling staff away from their primary responsibilities. Digital systems maintain all records in a centralized database, allowing managers to generate comprehensive compliance reports in minutes rather than days.

The software company Safefood 360° illustrates how manufacturers can maintain continuous audit readiness through automated compliance workflows. The platform features more than 35 modules covering Global Food Safety Initiative and FSMA requirements.

Facilities can schedule standard reports to generate automatically, ensuring that compliance documentation remains current without manual intervention. When auditors arrive, quality teams can instantly pull records showing temperature logs, sanitation verifications, corrective actions and supplier approvals rather than scrambling to assemble paper files.

2. Enhanced Traceability for Faster Recall Management

The speed and scope of a recall directly correlate with the quality of traceability data. Manual systems require quality teams to search through paper records to identify affected lot codes, trace ingredients back to suppliers and determine which distribution channels received potentially contaminated products.

This investigation can take days, during which additional contaminated product reaches consumers. The financial and brand reputation impacts of food recalls can devastate manufacturers, making rapid response essential to limiting damage.

Automated traceability systems link product testing results directly to lot identifiers and production lines. For instance, Neogen Analytics demonstrates this capability through automated alerts that identify affected lots immediately when test results indicate contamination.

Quality managers can pinpoint the exact production window and distribution scope with high efficiency, reducing product recalls and associated remediation costs. This lot-level precision prevents the costly scenario of recalling entire production runs when contamination affects only a subset of output.

3. Proactive Insights Through Trend Analysis

Collecting data serves purposes beyond regulatory compliance. Large datasets reveal recurring issues, seasonal patterns and emerging trends that predict where contamination risks concentrate. Quality teams can shift from reactive problem-solving to proactive prevention by systematically analyzing historical test data. This analytical capability transforms food safety programs from defensive operations into strategic advantages.

Hot spot visualization represents one of the most powerful applications of trend analysis. These tools map contamination events to specific locations within a facility, revealing areas where sanitation protocols fail or where environmental conditions favor microbial growth.

Quality managers can target enhanced cleaning procedures, modify traffic patterns or adjust environmental controls in these high-risk zones. This targeted approach delivers better results than generic facility-wide interventions while requiring fewer resources.

The Future of a Data-Driven Food Safety Culture

The current generation of automated data management systems represents only the foundation for future innovation. Artificial intelligence and machine learning technologies promise to transform food safety from a reactive discipline into a predictive science.

These systems can analyze millions of data points to identify subtle patterns that human analysts might miss, flagging emerging contamination risks before they manifest in positive test results. Quality managers will shift from responding to problems to preventing them through predictive interventions guided by algorithmic insights.

Frequently Asked Questions

Food safety professionals often ask similar questions when evaluating automated data management systems.

How does automated data management integrate with existing ERP systems?

Most modern food safety platforms offer application programming interfaces (APIs) that connect with enterprise resource planning software through standard protocols. These integrations allow bidirectional data flow, ensuring that production schedules, ingredient traceability and quality control data remain synchronized across systems without manual data entry.

What is the first step to transitioning from manual to automated data collection?

Manufacturers should begin by identifying their highest-value use case, typically the area where manual processes create the most risk or consume the most staff time. Starting with a focused pilot program allows teams to develop expertise and demonstrate return on investment before expanding to additional processes.

Building a Resilient, Proactive Food Safety Ecosystem

Moving to an automated, data-driven model represents a strategic necessity rather than an optional enhancement. Regulatory requirements continue to expand, consumer expectations for transparency increase, and the consequences of contamination incidents grow more severe. Manufacturers who invest in robust data management infrastructure position themselves to meet these challenges while competitors struggle with outdated manual systems.

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Food Safety as Business Infrastructure Series (Article 3 of 5): Can your system absorb growth without losing control?

By Azure Edwards, M.S.
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Can Your System Absorb Growth Without Losing Control?

Growth is one of those business “problems” that arrives looking like a reward. Purchase orders get larger, customers become steadier, and a team that once stretched to meet demand grows into one carrying a level of production that gives the business real momentum. It also changes the load. Growing success brings more decisions, handoffs, documentation, requirements, and moments where delay or ambiguity has larger consequences. When those demands land on a structure designed for a less complex operation, the company can keep performing while it begins spending more to do the work—more time, more money, and more management attention than the same work used to require.

That is where growth can become instructive. It shows whether the business is carrying its recurring demands as a known condition, or absorbing them through people, margin, and momentum. At first, the signs point one way: a rising number of data findings suggests sharper detection, a corrective action log full of closed items implies responsiveness, and a team consistently delivering product looks like proof the system is working. All may be true; the question is what else the record is saying at the same time. This is where familiar responses like more training, reminders, and supervision warrant a closer look. Those interventions may be needed, but when the same type of issue keeps returning across a range of people, shifts, and locations, the question shifts from whether people know what to do, to what the system is requiring them to carry.

At one level of complexity, proximity can appear to function like infrastructure. Leaders close to the floor know which decision needs to move. Quality understands the history behind repeat holds for the same or similar products; operations knows where the procedure and the actual work performed have parted ways and which one is keeping the product moving. Growth changes that geometry. More shifts, products, customers, interfaces, and pressure on the same decision pathways create distance the earlier structure did not have to span. Knowledge that once moved because everyone was in the room now has to travel through a structure not yet equipped to carry it, much less deliver it to the decision-makers intact.

Food safety is one of the clearest places to see these pressures surface because so much of the work is explicit. Expectations are set by regulation and customer requirements. Outcomes are measured. Performance is documented. The record shows not only what happened, but what the system is repeatedly being asked to absorb. In one operation I worked with, deviations in a single control area multiplied roughly sevenfold between the second year and the fourth. The team read that increase as evidence they were catching more, recording more, and staying ahead of the work. They weren’t wrong; however, reading it in context made it clear that the same people, with the same hours and resources, were now identifying, investigating, and documenting several times the volume of administrative work to keep pace with the recurrence rather than resolving what produces it. The detection was accurate. What it cost to sustain the load is what remained unseen.

That cost is paid either way, counted or not. Whether the increase reflects more events, better capture, or both, the operation is spending more attention to keep the same part of the system from giving way. That attention has a cost before it ever shows up as failure: time, rework, decision delay, management bandwidth, compressed verification windows, and the effort people put into making the system appear smoother than it feels from inside the work.

Under that pressure, workarounds emerge as the relief valve. When allowed to persist long enough, the workaround stops being a workaround and becomes the informal procedure. At first, the escalation may be visible in the record. Left unaddressed, it can drop out of it — handled on the floor and no longer reported to the people who would need to act on it. That is the danger in normalizing deviations between work-as-done and work-as-imagined: the record stops registering the strain because the strain stopped being surfaced. Absorbed strain finds a harborage, a place to settle, concentrate, and integrate into the environment until it reads as part of normal operation. It behaves like a biofilm: not a single problem, but a network bonded to the operation, fed by the conditions around it, and protected by them. A pass with the sanitizer clears what shows on the surface and the verification comes back clean, while the network underneath is never reached, and keeps compounding. A schedule can flex and a customer conversation can buy time, but a food safety control cannot bend to the pace of growth without cost — to the operation, to the business, and to the people the product reaches.

The same system strain looks different depending on where it is read. On the floor, it may appear as variation, delay, or rework. In the governance structure, it may appear as authority that stalls, escalation that depends on relationships, or roles that have not caught up to scale. At the business level, it may appear as margin pressure, capacity uncertainty, customer strain, or the question of whether the next stage can be supported without exhausting the system that made the growth possible. Food safety gives the organization something concrete to organize around. When those three perspectives can step into the same room, growth strain stops looking like separate fires and becomes a map of what the next stage requires.

That is the distinction between a system that performs and a system that can bear the weight of its own expansion. Performance under familiar conditions proves less than it appears to. Growth tests something harder: whether the structure beneath that performance is coherent enough to carry what comes next — at a greater scale, with global supply-chain challenges, increased consumer demands, and perpetually shifting regulatory requirements. That capacity is the ability to carry the next demand without making people the permanent bridge between what the system requires and what the structure has been designed to support: expectations clear enough to travel, authority distributed enough that decisions move instead of stacking up, escalation that works because the pathway exists before pressure arrives, and knowledge that once lived in a few experienced heads becoming something the organization owns. Asking that structure to take on more than it can carry is not just ambition; it is the initiation of a series of hidden risks that won’t show up in any projection, P&L, or return, because it is a weight carried by the people, on the system’s behalf, until something eventually gives.

The operations that scale without losing control treat that infrastructure work as part of growth itself, by developing governance alongside expansion, rather than reacting to growth after the fact. Concentrated strain that no one is addressing does not stay contained. It surfaces as a recall, a headline, sometimes as harm reaching the person who trusted the label, and traces back, almost always, to a control that was normalized. These are not new failures. Read across any timeline of recalls, the causes are overwhelmingly ones already understood and already preventable: known hazards, met by known controls, allowed to recur. That is the plainest evidence that the systems are not learning from the record they already hold.

This is what the technology is for, and where its potential most often goes unrealized. The monitoring platforms, the scheduling systems, the real-time alerts, the data collection, the dashboards — the advances are real, and detection and data management have come a remarkable distance. But better instruments read through the same frame return more of the same, in finer detail. The data does its best work when the organization is willing to shift how it reads what it already sees, and has the authority, clarity, and will to act on it. That is the level of transparency this work asks for — a kind of self-sight most systems do not yet have, and it has to start with the business looking honestly at itself. Not to cut cost for its own sake, but to free the resources to fix what is actually breaking, and then to grow on a foundation that can hold the next thing rather than bolting another pillar onto one already straining under the load it already carries.

The real question is whether the system can keep growing without asking people to absorb what structure should be carrying — because people are the first place growth strain becomes visible, and they are the last place it should be allowed to stay. Read for what else they hold, a company’s own records show more than events. They show what the organization is asking its people, its controls, and its business model to carry, and for how long it has been asking. Inside the company, that reading shapes how decisions get made under ordinary pressure. Outside it, external parties such as regulators, auditors, and customers evaluate a system based on the evidence it generates, regardless of whether the organization is paying attention. When internal governance is coherent, it creates external legibility that fosters trust well before a crisis tests the brand. The true risk is not expansion itself, but scaling upon a foundation that is already overextended — a condition the system’s own records have likely been signaling all along.

Editors Note: the author Azure Edwards is presenting “You’ve Been Collecting Food Safety Data for Years. Why Isn’t It Making You Better?” at the Food Safety Consortium Conference, October 21-23. Washington DC

More info at Food Safety Consortium Agenda  

Testing methods, analysis

Beyond the Certificate of Analysis: What Supplier Verification Really Asks of You

By Bala Murugan
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Testing methods, analysis

Walk into most receiving operations and supplier verification looks like a filing system. A lot arrives, a certificate of analysis arrives with it, the COA says the ingredient is within spec, and the document goes into the folder. Box checked. It feels like verification right up until a recall, an FDA inspection, or a customer complaint asks the harder question the folder was never built to answer: not “do we have the paperwork?” but “was the product actually safe?”

Those are not the same question. The space between them is where a surprising number of preventable failures live, and closing it is one of the highest-return moves a quality team can make.

What the rule actually asks for

It helps to start with what FSMA requires, because the regulation is more demanding and more sensible than “keep the COAs on file.”

The Preventive Controls for Human Food rule (21 CFR Part 117) turned supplier oversight from a procurement nicety into a defined food safety control. Under Subpart G, when a hazard in an ingredient is controlled before you receive it what the rule calls a “supply-chain-applied control” your facility has to run a risk-based supply-chain program that gives real assurance the hazard was significantly minimized or prevented.1

Holding paperwork does not satisfy that. The rule expects you to use approved suppliers, decide on and carry out verification activities suited to the hazard, and document what you did. The part many programs miss is that the regulation deliberately scales the verification to the risk. For a hazard with serious health consequences say, a pathogen like Salmonella in a ready-to-eat ingredient an onsite audit of the supplier is the default expectation, before you first approve them and annually after, unless you’ve written down a defensible reason to do something else.3 For lower-risk hazards, sampling and testing, a review of the supplier’s records, or another fitting activity may be enough.

Read that closely and the rule is already making this article’s argument for you: verification is a spectrum, and a certificate is one tool on it right for some hazards, badly undersized for others.

Why a certificate isn’t proof

A COA is, at bottom, an assertion. It says someone tested a sample of a lot, by some method, and got a result. That can be genuinely useful. Treated as proof of safety, though, it has three weak points worth being honest about.

It describes a sample, not your lot. For contaminants that don’t distribute evenly mycotoxins, heavy metals, pathogens in dry goods are the usual suspects the result is only as good as the sampling behind it. Aflatoxin is the textbook case: a few contaminated kernels can carry thousands of times the toxin of the material around them, so a clean number pulled from a careless grab sample tells you about the scoop, not the shipment. If you don’t know how the supplier sampled, you don’t really know what their number means.

It’s only as good as the lab and the method. A result with no validated method behind it, from a laboratory whose competence for that analyte and matrix you can’t establish, is hard to lean on when it matters. That’s the practical case for accredited testing: ISO/IEC 17025 accreditation means a lab has shown technical competence for specific tests, works to validated methods, and proves itself through proficiency testing. A COA from an unknown lab and a report from an accredited one aren’t the same instrument, even when the numbers happen to agree.

And documents can simply be wrong through honest error, a stale specification, or, in the well-documented world of economically motivated adulteration, deliberate falsification. Anyone who has watched the adulteration stories around spices, oils, and honey knows that a supplier’s paperwork and a supplier’s product are not always the same thing.

None of this makes COAs worthless. It means they belong inside a program that occasionally tests whether they’re telling the truth not standing in for one.

Building verification that fits the hazard

The programs that hold up treat verification as a portfolio matched to risk, not a single document repeated for everything. A few principles do most of the work.

Match the effort to the hazard. Put your most rigorous tools onsite audits, independent confirmatory testing against the hazards that could hurt someone, and lighter activities against lower-risk ingredients. That isn’t just sensible; it’s how Subpart G expects you to make approval and verification decisions in the first place.

Spot-check your suppliers’ COAs with your own testing. The goal isn’t to retest every lot of everything nobody requires that, and nobody could afford it. It’s to confirm, on a risk-based cadence, that the supplier’s documentation matches reality, using a lab whose competence for that analyte and matrix you can actually demonstrate. The day your independent result and the supplier’s COA disagree is the day the whole program earns its keep.

Treat sampling as seriously as the assay. For unevenly distributed contaminants, the sampling plan is the control. Specify how representative samples get drawn and ground, because no instrument, however sophisticated, rescues a bad sample.

Revisit suppliers on a schedule and whenever something changes. New ingredient, new origin, new supplier the hazard picture moves, and the paperwork lags. The supply-chain program, and for imported ingredients its sibling the Foreign Supplier Verification Program under 21 CFR Part 1, expects you to weigh supplier performance and reassess when new information about a hazard or a supplier turns up.

Write down the reasoning, not just the result. When you choose a verification activity other than the default for a serious hazard, the rule expects a documented justification.3 The artifact that protects you isn’t only the test report; it’s the recorded logic tying the hazard to the supplier to the activity you picked.

The shift worth making

The real change here is one of posture. A program built to collect documents answers “do we have the paperwork?” A program built to verify answers the question that actually keeps people safe: if this ingredient were out of spec right now, would we catch it before our customer did?

The distance between those two questions gets measured in recalls. FSMA’s supply-chain program sets a floor approved suppliers, risk-based verification, documentation. The manufacturers who turn that floor into genuine protection are the ones who treat a certificate of analysis as the start of verification, not the end of it, and who back their supplier programs with sampling and analytical competence equal to the hazards they’re trying to control.

Paperwork can promise safety. Only verification demonstrates it.