The ListWare and ListComplex Projects

Purchase the innocative shelf life calculator by Animalia, a product of two research projects.

Listware

Software for risk assessment of Listeria in ready-to-eat meat products Abattoirs (Innovation project in the Norwegian business sector - BIONÆR) 

Norwegian Research Council, grant no.: 256259/E50

Project period: 01.07.2016 – 30.06.2019

In Collaboration with the Norwegian Veterinary Institute, Orkla Foods Norge AS, Grilstad AS, Matbørsen AS and Fatland AS

ListComplex

Software for risk assessment of Listeria in complex ready-to-eat products (Innovation project in the Norwegian business sector - BIONÆR) 

Norwegian Research Council, grant no.: 309791

Project period: 01.05.2020 –30.04.2023 

In Collaboration with the Norwegian Veterinary Institute, Fatland AS, Grilstad AS, Matbørsen AS, Mills AS, Bama AS and Salatmestern AS

The Challenge of Listeria

The "ListComplex" project has developed a shelf life calculator for companies producing ready-to-eat foods, i.e. products not heat-treated before consumption. This shelf life calculator will contribute in risk assessment and documentation of shelf life for ready-to-eat foods using predictive modelling. The bacterium Listeria monocytogenes poses a risk in foods that are not heat treated by consumer because listeria can grow at refrigerator temperatures and reach disease-causing levels during storage. Healthy people can tolerate eating some listeria and the legislation states that listeria must not exceed 100 cfu per gram product during the shelf life.

Web Tool Development

The software is web-based and can be used on mobile, tablet and computer in Norwegian or English. The software is owned and operated by Animalia (www.animalia.no), which administers user licenses, and is available at the end of the project for food companies in Norway and internationally.

The Veterinary Institute has performed 243 listeria growth studies with 27 ingredients or composite foods, with different packaging methods and storage temperatures. The results are statistically processed using algorithms and predictive models. Models are tested in verification trials. These models are programmed into software. The user interface is very user-friendly for food companies. The user selects a product from a menu, and product characteristics such as ingredients, pH, water activity, carbohydrate content and growth inhibitors such as lactate and acetate are suggested. These suggestions are based on 1677 lab-analyzes. The user can overwrite the default values. The user fills in packaging method and storage temperature, and a growth curve for listeria is calculated. The number of days for listeria growth to reach 100 cfu per gram is defined as the listeria shelf life. The user can print this documentation for use at inspections and product development. The software can also be used for simulation, to find methods to increase shelf life, such as addition of acetate or lactate, changing to another packaging method and changing the pH and carbohydrate content. Longer shelf life is calculated with a few keystrokes, instead of performing challenge studies.

Research Work

Behind these predictive models, there is considerable research work. Competence is obtained from Norwegian and European research environments within listeria and predictive modelling. Different models have been tested, such as linear regression models and gamma models. The regression model is scientifically accepted in a recognized scientific journal (Skjerdal et al., 2022) and the gamma model article is being prepared, in collaboration with foreign researchers (Gangsei et al., in prep.). The project has also been presented at two international conferences, in addition to Norwegian journals and websites.

The shelf life calculator is based on the ListWare project for meat products and the EU project Startec, as well as contributions from European research communities in Italy, Spain, Switzerland and France. In ListComplex, we have mainly investigated mayonnaise-based salads and mixed green salads. Listeria outbreaks in recent years have been caused by mixed products. Risk assessment of composite food products is challenging, and difficult to model because each ingredient represents a separate environment and contact surfaces can change the conditions of the individual components. Mixed products can increase the risk of listeria growth as the microenvironment between two ingredients can provide good growth conditions, even if each individual ingredient has a low growth potential. Little research has been published on listeria growth in composite products, and our findings show interesting results. The main finding is that pH drops during storage period if there are carbohydrates available in the mixture, which inhibit the listeria growth. The pH in meat products are basically stable, but if the meat is mixed with vegetables, the background flora will grow in the vegetables and produce acids that reduce the pH and inhibit the listeria growth. The food industry can use this to extend shelf lives of certain ready-to-eat foods. It is also shown that sour cream added to mayonnaise-based salads increases shelf life due to lactic acid bacteria content.

Industrial Partners

Six industrial partners in this project, have through cooperation and openness, built up their competence in microbiology, predictive modelling, statistical analysis and web design. The ListComplex project has developed a tool that would not been developed without the research support. The web program ListWare will contribute to cheaper and simpler risk assessments for the shelf life of ready-to-eat products. It will provide safer food, reduced costs for food companies, less food waste and more sustainable goods flow.