Low in Food has set its specific work flow
AREFLHis a partner oftheproject LOWINFOOD, defined as a "Multi-actor design of low-waste food value chains through the demonstration of innovative solutions to reduce food loss and waste". The consortium has now set the specific workflow to be followed during the whole duration of the project.
The aims of the project is to reduce food loss and waste in food production, processing, distribution and consumption in 4 value chains particularly concerned by this issue, due to their perishable products as well as the large amount of waste generated in each of them.
The consortium has come together to deploy and implement innovative solutions to the food waste problem by demonstrating their effectiveness and marker potential. A portfolio of 14 innovations has been selected among promising solutions that have already been developed and tested by some partners and includes technological tools and devices as well as organizational and managerial solutions.
Fruits & vegetable, bakery products and fish value chains are selected as settings to apply the innovation as these perishable foods are particularly concerned by the issue of food waste. For each value chain, the upstream stages are considered in the demonstration of the innovations, from production to retailing. Another set of innovations to the consumer level, to avoid the waste of all foods in out-of-home and home consumption.
LOWINFOOD has set the specific workflow to be followed during the whole duration of the project. Close cooperation among partners is needed to successfully attain the expected results. This is the general sequences of activities that will be carried out:
- Co-definition of methodology with stakeholders;
- Implementation of Innovations;
- Effects: quantity of food waste environmental impact, socio-economic impact;
- The exploitation of results and innovation in more value chains;
- Baseline in FW (food waste) assessment in value chains;
- FW (food waste) assessment under innovation;
- Guidelines for market replication and policy indications.
For more information about the project, please visit the following media :
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No.101000439