Novolyze, a company working in food safety solutions and quality digitization technology, is announcing it has upgraded its Environmental Monitoring Program (EMP) solution to include advanced predictive analytics and machine learning. This latest upgrade will enable Novolyze's technology to automatically generate trend charts and digital "heat" maps using digital data. This, in turn, will lead to better outbreak forecasting and prediction of pathogens such as Listeria or Salmonella, which have surged in recent months.
An EMP is a crucial tool for food manufacturers to maintain food safety and quality, especially for ready-to-eat (RTE) foods. RTE foods are those that do not require any further cooking or processing before consumption, and as such, they are at higher risk of contamination by foodborne pathogens.
Novolyze's EMP solution has always been a critical tool for ensuring food safety and compliance. By testing the environment, including surfaces and equipment, the EMP helps manufacturers identify potential contamination risks and take appropriate corrective action to remove the risk. With the new upgrade, Novolyze's EMP solution is even more robust, providing manufacturers with real-time predictive analytics that enable them to stay one step ahead of potential foodborne illness outbreaks.
"We are committed to providing the latest technology and solutions to help the food industry reduce risk and maintain the highest levels of food safety," said Novolyze CEO Karim-Franck Khinouche. "With this latest upgrade, our EMP solution is more powerful than ever, and we are excited to continue helping our customers keep their food safe."
The use of predictive insight in an EMP can help food manufacturers identify potential areas of contamination before they become a problem. By collecting and analyzing data on environmental conditions such as temperature, humidity, and sanitation practices, manufacturers can develop models to predict where and when potential contamination events may occur. This allows them to take proactive measures to prevent contamination, rather than waiting for a problem to arise and then reacting to it.
For example, if a manufacturer uses predictive models to identify a specific area in the facility that is at a higher risk of contamination, they can take steps to increase sanitation measures in that area or adjust the production process to reduce the risk of contamination. By doing so, they can prevent potential food safety issues and ensure that the RTE foods they produce are safe for consumption. Novolyze’s EMP can support these efforts.
Additionally, the use of predictive insight in an EMP can also help improve product quality. By monitoring and analyzing data on environmental conditions, manufacturers can identify and address issues that may affect the quality of the product, such as changes in temperature or humidity. This can help ensure that the products are of consistent quality and meet the expectations of consumers.
“Novolyze's EMP solution is particularly relevant in the current climate, with foodborne illness outbreaks becoming far too common,” added Khinouche. “By utilizing the latest technology, including predictive analytics and machine learning, Novolyze's EMP solution is helping to cut down on food safety and quality control issues, enabling manufacturers to maintain the highest levels of food safety and ensuring that consumers can trust the foods they eat.”
For more information, visit novolyze.com.
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