Water has many food-related uses. Many of these uses will impact compliance under the Food Safety Modernization Act (FSMA). Pre-harvest uses of water and FSMA compliance have recently been re-opened by FDA to address the concerns brought forward by many parties in the agricultural community across the country.
At this time, specific new rules have not been promulgated under FSMA regarding cooling or wash water. However, the general guidelines of FSMA apply, implying that one needs to know:
- What is the process?
- Why is it the process?
- How do you know that you did the process?
It is important to recognize that cooling and washing are part of the process and that there is generally no kill step to mitigate failures in control when dealing with produce. Frozen products that are blanched are the major exception.
To address these three questions, it is easier to start with why it is the process. Cooling rapidly removes field heat and slows the metabolism of the product, conserving sugar and thereby preserving shelf life. Washing removes foreign matter and reduces microbial load to some degree. It’s essential to do no harm during both the cooling and washing of these products. For doing no harm, the most important food safety objective associated with both of these processes is mitigation of cross-contamination by managing the water chemistry. This management is complicated by the reuse of water in these processes to reduce energy costs. In any event, allowing trace sporadic contamination to spread is not acceptable. Increasing the microbial lethality of wash processes to a 4 log kill remains the holy grail of produce washing. Unfortunately, a 4 log kill remains out of reach without rendering products unacceptable, but there may be improvements on the horizon.
Challenges
At this point, a diligent processor who wishes to comply with FSMA encounters three important challenges relative to mitigation of cross-contamination. First, there is no gold standard process for washing or chilling that has regulatory standing and that by definition controls cross-contamination. There is no safe harbor. Unfortunately, it is also unreasonable to expect FDA to provide a safe harbor as it would absolve the industry from utilizing the best practical process. Second, there is no standard assay or objective measure for cross-contamination. Without a procedure, no numeric standard can be established. A qualitative standard, such as “no detectable cross-contamination,” is a meaningless bandage unless a procedure sets a standard for how hard one must look. Existing analytical tools such as most probable number (MPN) techniques permit detection of minute levels of cross-contamination. And third, there are limited options for testing whether cross-contamination is mitigated. Taking even a benign organism into a food processing facility is unacceptable. Intentionally inoculating a food or a processing line should not be done. Additionally, no acceptable surrogate has been identified. SafeTraces continues to develop a non-living surrogate but much work remains before it has a commercial product for demonstrating cross-contamination control.
Controlling Cross-Contamination
According to Journal of Food Protection’s “Guidelines to Validate Control of Cross-Contamination During Washing of Fresh-Cut Leafy Vegetables,” featured in the February 2017 issue, authors suggest three options for demonstrating cross-contamination control:
- Using a surrogate to demonstrate cross-contamination control;
- Using antimicrobial sensors to demonstrate that a critical antimicrobial level is maintained during worst case conditions; or
- Validate placement of sensors to assure that a critical antimicrobial level is always maintained.
Option 1 is direct but subject to all the problems just considered. Options 2 and 3 assume a critical level is known. A critical level can only be established with a standardized assay for cross-contamination and an objective target for control. Neither the assay nor the objective target exist as discussed above. Option 2 also requires an understanding of the worst-case conditions. It is frequently asserted that the worst-case conditions are at high organic load. Research done in the SmartWash Solutions pilot plant using spent water from a commercial operation shows that used water provided better cross-contamination control than fresh water as shown in Figure 1. This figure shows a model system in a Product in Tote washer with steady state free chlorine control provided by a SmartWash Solutions ASAP, cross-contamination from inoculated spinach to uninoculated spinach is largely mitigated even at low chlorine concentrations in spent process water for three commodities in a system where fresh city water failed to control the migration of E. coli inoculum. The spent water included residual SmartWash Solutions SW. Measures sharing a letter within chlorine levels are not significantly different. The identification of the worst-case conditions is more complex than most people realize.
There is an evolving literature surrounding cross-contamination control, however it is nowhere near as developed as heat penetration studies for thermal processing. Most of the experiments are bench scale without steady state control of the antimicrobial level. It is tempting to generalize based on these limited studies to all systems. Very few studies have been done at commercial scale, so recommendations are largely extrapolations to large scale systems. Good studies will insure steady state control of the product flow, the contaminant flow, and the water chemistry including antimicrobial level and pH. The use of any wash adjuvants should also be noted as they can improve wash chemistry performance. There are indications that the sequestering power of some adjuvants, such as SmartWash, mitigate the problems of high organic loading.
Returning to our diligent processor, he or she must make some decisions about how to proceed with incomplete and imperfect information. For the balance of this discussion, let’s assume that he or she has digested the available literature, has generated some of his or her own data, and has pushed his or her suppliers for information. Based on this information, the diligent processor can make a best effort to define his or her process, thus answering the first question. This process will allow cooling and foreign material removal and avoid cross-contamination to the best of their ability. The quality of this process will depend on the quality of the information inputs. The diligent processor can expect to have his or her reasoning questioned during an FDA inspection. To date, FDA has not made an inspection of this type. Until such an inspection occurs, the industry does not know what FDA will find acceptable. However, months and years of safe operation with good control should weigh into this discussion, taking us to the third question, how do you know that you did your process? Contrary to many wishes, it is unreasonable to expect the FDA to accept a 10 ppm control point for free chlorine as sufficient to define an acceptable process given that FDA has not provided a safe harbor, as already discussed.
To prepare for this third question, it is recommended that the diligent processor use an automated control system that automatically logs the key operational parameters of the defined process. Antimicrobial level and pH are the two most fundamental parameters. Temperature should also be considered if it is part of the defined process that the processor developed. However, generating and logging this data is insufficient. The data must be vetted and used.
The data vetting process involves loaded terms such as precision, accuracy, verification, validation, calibration, standards, reference, and many more. Vetting is the process for insuring that the generated and logged data are useful and meaningful. The diligent processor needs to be able to articulate why he or she trusts the logs of operational parameters. “Garbage in yields garbage out” is an oft-cited aphorism that clearly applies in this situation. If the processor is using the suggested controller, the supplier of this controller should be able to demonstrate the utility of the generated data. Utility of the data is considered because all measurements inherently include error and therefore are to some extent wrong. A measurement can be expected to be no more accurate than its reference. A reference should have a traceable pedigree that instills confidence.
The inherent error is normally discussed in terms of variance and statistical probabilities. These tools can be used to establish the probability or confidence that all of the product received the defined process. At present, there is no regulatory guidance as to how this should be accomplished. A best practices approach will need to address at least four types of variance including instrumental variance, process variance due to inhomogeneity in the processing system, process variance associated with product, product feed rate, etc., and reference variance. This is a big task.
Our diligent processor has one more task to conform to FSMA. It is virtually certain that there will be some level of process non-conformity. Plans are needed to address these non-conformities. There needs to be a plan to use the data. This plan is the process to make data into information. It is very powerful to have automation handle routine matters of non-conformity. For example, if the antimicrobial level falls too low, the product feed can be halted. The logged data can provide the information to drive continuous improvement. Its value extends well beyond just insuring that the product produced at the time of collection was properly processed.
Making the assumption that everyone wants to be FSMA compliant in their water usage, it is important to understand the objectives of the water use, understand why the process is done in a particular way, and verify conformity. The water user should be able to articulate the answers to these questions before something unfortunate happens.
Dr. Wilhelmsen is a senior research consultant for SmartWash Solutions, LLC. Reach him at [email protected].
ACCESS THE FULL VERSION OF THIS ARTICLE
To view this article and gain unlimited access to premium content on the FQ&S website, register for your FREE account. Build your profile and create a personalized experience today! Sign up is easy!
GET STARTED
Already have an account? LOGIN