1. Major carbohydrate component Major protein component
Decision support tool for producers of advanced ready-to-eat foods to ensure safe, tasty and nutritious products
Taran Skjerdal1, Girum Tadesse Tessema1, Tone Mathisen Fagereng1, and Cecilie From2
1Norwegian Veterinary Institute, Oslo, Norway; 2Matbørsen, Stokke, Norway
Background
Food business operators must make strategic and daily tradeoffs where food safety and quality are only some of the criteria.
Results and discussions
Decision support was desired by industry within topics related to multidisciplinary dilemmas like:
The need of a high productivity per square meter, leading to a need of precooked materials to save space and time.
The customer demand of different salads versus the probability of mistakes by differentiated production.
The laboratory experiments indicated that the salad compositions, process and storage scenarios, could be used to estimate the pathogen level categories (growth, no growth and decline) by using the pH, the lactic acid bacteria content in the dressing, the storage temperature and the content of meat as input parameters (Figure 2). The data visualized how the salad composition could be adapted to improve the safety, how replacement of an ingredient could be done without compromising quality or safety, and which deviations that lead to a change of food safety category and thereby a need for corrective action (Table 1).
Purposes
To map where decision support is needed in industry
To develop the food quality and safety parts of a prototype of a multidisciplinary decision support tool.
Methods
Three companies located in Norway, Italia and Ireland were visited by researchers for several days to identify the real industry challenges, how they dealt with the complexity in production, learn where deviations occurred, as well as how and when decisions were made in production of deli salads.
Experiments were carried out in the lab with simulated industry products using potato salads with more than 40 variations of ingredient composition and storage scenarios, (Figure 1), inoculated with Listeria monocytogenes and Staphylococcus aureus.
Major carbohydrate component
Potato
Spices
Salt, Pepper, Sugar
Vegetables
Fresh chives, Pickled cucumber
Processing
(i) removing one or more of ingredients
(ii) reducing the amount of ingredients
(iii) substituting with other ingredients
(iv) adding new ingredients
Dressing
Mayonnaise, Sour cream, Crème fraîche, Quark, Yoghurt, Buttermilk, Cottage cheese, Pesto, Oil, Vinegar
Major protein component
Chicken meat
Storage
Abuse time-temperature conditions
Ingredients
Table 1. Examples of scenarios compromising quality or safety with possible corrective actions.
Scenarios
Safety/quality/ effect
Possible corrective actions
Case 1-supply chain
Precooked instead of fresh ingredient
Rely on the supplier in terms of quality and safety
- More focus on supply chain management
- Adaptation of in-house HACCP
Case 2-process/
composition
Dressing with low fat dairy products or less amount of dressing
- pH heterogeneity
- more rapid growth of Lm due to less content of preserving LAB*
- Mould formation on the potato at abuse
temperature
- Add more dressing
- Add LAB or include parts of the sauce with dairy products containing preserving LAB
- Shorten the shelf life
- Pack in MAP
Case 3-storage conditions
Storage at abuse temperature
- Increased growth potential of Lm in some cases
- Less growth potential of Lm in case of presence of reserving LAB*
- Mould formation
- Add dressing with preserving
LAB
- Shorten shelf life
- None
- See above
Figure 1. Process map for productions of 40 varieties of potato salad in the lab.
Salad
types
Fate of pathogens at
different storage
conditions
Salad 1
Partial inactivation ND
Salad 2
100% inactivation
Salad 3
Salad 4
Growth
Salad 5
Salad 6
Salad 7
Salad 8
Salad 9
Survival
Salad 10
Salad 11
Salad 12
Salad 13
Salad 14
Salad 15
Salad 16
Salad 17
Salad 18
Salad 19
Salad 20
Salad 21
Salad 22
Salad 23
Salad 24
Salad 25
Salad 26
Salad 27
Salad 28
Salad 29
Salad 30
Salad 31
Salad 32
Salad 33
Salad 34
Salad 35
Salad 36
Salad 37
Salad 38
Salad 39
Salad 40
Salad 41
Salad 42
*found in this study, may not be valid for other products and LABs.
Significance
The main significance of the work is identification of scenarios that may lead to changed growth patterns pathogens and some quality deviations, how they can be categorised and presented in an easy and rapid way for people with limited training in microbiology who have to make decisions.
Green
100% inactivation
Yellow
Survival or
Partial inactivation
Red
Growth
Acknowledgments
STARTEC ( is funded by the European Commission FP7-KBBE safety and quality of ready-to-eat foods under grant agreement no
Figure 2. User friendly visualization of salad formulations and pathogen levels during storages categorized in red (significant growth), yellow (no growth r slight reduction) and green (100 % inactivation) for the decision support tool.