Call for partners: Big data and modelling for pro-active risk-basedmonitoring of safety of animal feeds

Project

Call for partners: Big data and modelling for pro-active risk-basedmonitoring of safety of animal feeds (PRO-RISKFEED)

Wageningen Food Safety Research combines expertise and experience within this PPP project to help companies in the early set up of the pro-active and risk based monitoring of food safety hazards in animals feeds.

Industrial partners

Industrial partners from the entire feed productions chain are very welcome to join. We would be pleased to further discuss your challenges in this field and how this consortium could help you solving them.

Cutting-edge informatics knowledge, software tools and big data

PRO-RISKFEED combines cutting-edge informatics knowledge, software and big data to develop a novel prediction tool for a pro-active and quick set up of risk based monitoring plans for food safety hazards in animal feeds. Such a tool will aid early identification of the most important contaminants and feed materials (with origin countries) to monitor, and advise on the set-up of the monitoring programs for the safety of animal feeds.

Pro-active approach

Relative to existing systems in place at the companies, the approach
will be more pro-active and able to give earlier information. It will also cover food safety of new feed materials (from waste/side streams).

Early Identification of food safety hazards

By global developments, such as climate change, and by national developments related to the use of side streams in animal feed production, food safety hazard may emerge in animal feeds. To safeguard the production of safe animal feeds, feed industry has several systems in place, such as HACCP and common monitoring programs (in which monitoring results are combined and shared).

The output of the PRO-RISKFEED project will help to be more pro-active  and even more risk based, in order to early identify food safety hazards that are likely to be present or emerge in certain feed materials. This pro-active and early risk based approach for the monitoring of these food safety hazards will significantly contribute to food- and feed safety and will save costs.

Use our experiences and expertise

Within this Public-Private-Partnership, we tackle this challenge by  enabling the feed industry to speed up their developments of the early set-up of a pro-active risk based monitoring for food safety hazards in animal feed, not only including regular feed materials but also covering (new) side and waste streams used for feed production. We will use our experiences and expertise in methods for risk based monitoring, big data and machine learning. We will apply cutting edge informatics knowledge and software tools to support the optimal set up of monitoring programs.

Use our experiences and expertise

Within this Public-Private-Partnership, we tackle this challenge by enabling the feed industry to speed up their developments of the early set-up of a pro-active risk based monitoring for food safety hazards in animal feed, not only including regular feed materials but also covering (new) side and waste streams used for feed production. We will use our experiences and expertise in methods for risk based monitoring, big data and machine learning. We will apply cutting edge informatics knowledge and software
tools to support the optimal set up of monitoring programs.

Call for partners: PRO-RISKFEED

Monitoring in a very early stage

PRO-RISKFEED will enable feed producers to monitor a set of contaminants and pathogens that are predicted by the tool to be developed, as having a high probability to be present in a certain feed materials from certain regions. This will be done in a very early stage, so monitoring can take place and timely intervention measures implemented if needed. Such timely interventions will save costs.

What are we going to do?

  • Collect monitoring data from industrial partners (provided in fully anonymous way), other monitoring data, and open source data from aside the safety domain
  • Process the data into one consistent database
  • Develop machine learning algorithms to setup a the PRO-RISKFEED model
  • Test the developed model in several companies
  • Develop user interface for companies to use the PRO-RISKFEED model

What are we going to deliver?

  • PRO-RISKFEED model for pro-active risk based monitoring of safety in animal feeds
  • Guidance for companies to use PRO-RISKFEED
  • Scientific publication and popular article on the developed model

What is the advantage for companies to cooperate?

  • Access to the PRO-RISKFEED model at the end of the project.
  • Use of the model will save costs for sampling and analyses, and will reduce losses through less purchase of contaminated batches of feed materials
  • The more companies cooperate, the more data we will have, and the better (more accurate) will be the model.