More attention is being paid to the importance of preharvest food safety solutions due to the USDA’s Salmonella reduction initiative to reduce the number of Salmonella illnesses associated with poultry. Part of the initiative includes increased quantitative microbial monitoring of incoming flocks to processing plants, focusing on serotypes of concern.1
Increased flock monitoring for quantitative bacteria and a preharvest food safety model based on continuous improvement (CI) can be practical, data-driven approaches to measuring and improving Salmonella loads preharvest.
“Poultry producers should think about all aspects of their farms and processing plants as opportunities for continuous improvement,” said Bill Potter, Ph.D., Elanco Food Safety Technical Advisor.
Salmonella Quantitative Measurements
Pathogen reduction is most successful when multiple steps are implemented along the continuum from farm to plant. Improved technologies in Salmonella quantification and detection preharvest have made measuring the impact of preharvest interventions easier.
Preharvest CI Model
Data drives decisions. Every CI process is based on data collected periodically or continually to describe and understand the process. Principles of the traditional “Plan-Do-Check-Act,” cycle can be used in preharvest food safety. A practical approach to this cycle can be broken down into the following five steps:
Preharvest Food Safety CI Model
Step 1: Quantify Salmonella loads
Quantitative measures of Salmonella can give an accurate picture of incoming loads to plants. These convert to log counts for best interpretation and allow managers to not only confirm the presence of Salmonella but also understand how much is present. Sample collection can be scheduled for random flocks or be ongoing.
Lab technologies have improved significantly in recent years, making it easier to get quantitative measures of Salmonella. Some of these measurement techniques include quantitative PCR (polymerase chain reaction), most probable number (MPN) methods and automated mini-MPN methods.
Also, it is essential to determine which preharvest measurement is most important to each complex. For example, measurements can be taken at the farm (boot covers, environmental swabs, cloaca swabs, etc.) or at the plant (pre-scald rinses, hot rehang or ceca sampling).
Focusing on only a few measurements to start is important; fine-tuning the data collection process can happen over time.
Step 2: Develop Quantitative Baselines
Mangers have multiple options when designating baselines for each plant or complex. Using principles of statistical process control (SPC), these baselines may be developed by taking a specified number of samples per farm and determining the complex mean and standard deviation.
The management team can then identify an acceptable baseline standard for the complex to identify outliers. For instance, a baseline standard may be developed utilizing the upper 80th or 95th percentile or by setting upper limits based on SPC principles using standard deviations. Statisticians or SPC experts can help develop practical baseline standards.
Step 3: Identify Outlier Farms
Once the quantitative baselines are determined, ongoing monitoring consists of taking a set number of samples per farm or week. Complexes may choose to sample all farms or a percentage of farms based on lab capabilities. If not tested weekly, flocks should be tracked to ensure that all flocks are sampled periodically throughout the year.
To best understand flock quantitative loads, it is optimal to take multiple samples in a flock and then average the results for that flock. If a flock is known historically to be high in Salmonella loads, management may choose to take additional samples for those designated flocks.
Outlier farms would then be identified as farms with quantitative results higher than the designated baseline standard for that complex.
Step 4: Develop Outlier Farm Follow-up Checks
Once outlier farms are identified, company field service supervisors, managers, veterinarians or designees can then conduct follow-up “farm check” audits. An audit checklist can be designed based on best management practices to prevent or reduce Salmonella on the farm.
The checklist should include all factors on the farm that could contribute to pathogen loads: biosecurity practices, integrated pest management, litter and water management, bird health, etc.
Step 5: Implement CI Plan
After a thorough farm audit of outlier farms, a formal CI plan can be created to help reduce Salmonella. The plan may include a combination of actions based on the guidance of technical experts inside the company or outside vendor resources.
Common initial C.I. steps can involve:
● Reducing litter moisture
● Stepping up pest elimination
● Modifying house cleanout
● Implementing Salmonella vaccines
● Utilizing probiotics or other supplements
● Implementing litter amendments
● Improving water treatment
The CI plan can be customized to each farm or all outlier farms. This process focuses on CI over time, not a fail-pass approach.
Vendor Partnership in the CI Process
As part of the food safety CI process, poultry companies can leverage vendor partners to help develop new strategies, technologies and ideas to address pathogen concerns. Vendors can offer services such as serotype lab analysis to verify vaccine effectiveness, field evaluations to understand the impacts of feed additives, and vector analysis to measure the effectiveness of insecticide rotations in reducing farm pests.
Elanco’s team of Food Safety advisors, veterinarians, nutritionists and technical consultants strives to have a keen understanding of the customer’s definition of success, whether it is in food safety, bird health or process optimization.
Learn how the Elanco Food Safety team can help you achieve continuous improvement in preharvest pathogen reduction by visiting Salmonella 360 for more information.
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1Eskin S. USDA Regulatory Updates. International Association of Food Protection Conference. Pittsburg. 1 Aug 2022.
