Thermal process validation - analysis and optimisation

David Whittaker, Thermal Processing Specialist

In this whiteboard presentation, David covers how we interpret and use the results from a validation study to optimise a thermal process. Thermal process optimisation preserves a product’s nutritional and sensory attributes, which is very important for quality and consumer acceptance.


Watch part one to understand more about thermal process validations.

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David Whittaker

About David Whittaker

David Whittaker is a thermal processing specialist with an all-round knowledge of thermal processing across many sectors of the food industry - particularly in chilled, acidified and heat preserved food and beverage manufacturing. Read more...

Transcript

Hello and thank you for watching this whiteboard presentation. My name is David Whittaker and I work as a process specialist at Camden BRI. Today I'm going to talk about thermal process optimisation. Based on the analysis of a thermal process validation study, this presentation follows on from my previous presentation on thermal process validation and we're going to talk a little bit about how the data and results can be interpreted from the validation study to actually not only understand whether it hits a minimum level from a food safety point of view, but also to understand how to further optimise that thermal process.


Now, what do we mean by thermal process optimisation? Well, we're not only looking at the minimum level to say whether a validation is passed or not, we're also looking to make sure that the process isn't over-processed, so the product isn't over-processed. So, we're looking at it from the other point of view as well, making sure that over-processing is absolutely minimised because over processing is a bad thing. It's bad for the product quality, depending on the product, and it can actually have a detrimental impact on the nutritional attributes of the food in question, as well as wasting energy and valuable time in the factory. So, we want to keep that over-process a minimum. It's really about understanding the optimal time and temperature for use during a thermal process on your specific product.


We're going to get data which looks a bit like this taken from a thermal process validation study. We have three plots on the graph. In red the environment temperature, so that is the temperature of the environment within the processing equipment so in a retort within a kettle or oven, and that is the temperature that the products is seeing through the process. This in blue is the product temperature and this is taken directly from the validation study and of course as part of validation, there should be a number of replicas and we would recommend taking the worst case of your many replicas and using this as your point of reference when looking to optimise that thermal process. Then finally the lethality. So that is the lethal effects accumulating over time of the heat on the product and normally this needs to reach a specific level to show whether the process is safe and acceptable to make it safe.


Now, when we're actually optimising, we're using all this plots and this data but considering three points to help us understand whether we can take some time potentially off a thermal process to optimise it. We need to understand what our absolute minimum of lethality is. So, in this example, we're talking about a sterilisation process.


So sterilisation worldwide is known to have a minimum level of lethality of three minutes - that is known as F zero. So an absolute minimum level in this example would be the point at which the lethality reaches three minutes, so this far into the process: ten minutes, twenty minutes, whatever the total process time is, and that is the absolute minimum level for food safety. But we also need to understand a safety factor. Now, this safety factor depends on the process and the product and it's something based on essentially a risk assessment, it's the amount lethality we want to actually achieve, divided by at what our absolute minimum is. So in this example let's say we want to get a target of six minutes, that's our in-house manufactured target for this product is six minutes, but it's a sterilisation process and we know the absolute minimum is three minutes, so six over three gives you two SF safety factor equals two. So the safety factor can depend on number of things, but really we're looking at how robust that thermal process is, how variable it is, how repeatable it is. So if we've done our validation and we've got a number of different results for lethality of products, different samples of product, we need to be thinking about how consistent those results are. The more consistent the lower number you can have for your safety factor. If they're very inconsistent we might be looking for safety factors of three or four having an in-house F0 target of over ten perhaps. If we're really controlled and we're very confident in our validation and our process then we might have something a bit smaller, maybe we'd have an in-house target of F0 equals four instead of six. But in this example we've gone for the typical quite a typical target of six minutes lethargy.


The other key point when considering a optimisation, is whether to use the heating, the cook and or the cooling phase as parts of the lethality accumulated. So in this example, the environment temperature dictates three different phases or three set different set points in the actual program or the cycle of the cook. In this case, we'd have the heating, the cook phase and the cooling phase and the question is well we're going to have to use something so we'll use the cook phase of course that is typically the most controlled part of the program, maybe we would use the heating phase because that can also be quite controlled, but the cooling phase typically the temperatures are not that controlled and in a lot of cases like we're talking about ovens the product actually comes out of the cooking vessel to cool, and then there's no control on the temperature of the product then. So in that case we absolutely could not use cooling so we're not going to use cooling which, in most cases, we would recommend not to do. Our maximum the fallacy from the process then is about 10 minutes.


So bearing all this in mind, our free point for optimisation and looking at our data, we then need to make a decision can we optimize, well the answer in this example would be yes because at the end of the cook phase we've got 10 minutes of lethality accumulated, so it's over our in-house target of 6 which has been established to give us a safety factor of 2, because it's 2 times our minimum absolute minimum, so yes we in theory we could take a section of this cook phase out. From here to here from here to here or here to here this is essentially with over-processing were unnecessarily cooking the product so we could take that out and optimise our process. Thank you very much for listening.