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DAta-based Dynamic Food PRoductiOn ManAgement (AROMA)

Reference number
Coordinator Linköpings universitet - Institutionen för ekonomisk och industriell utveckling
Funding from Vinnova SEK 3 100 363
Project duration September 2022 - November 2025
Status Completed
Venture Strategic innovation programme for process industrial IT and automation – PiiA
Call PiiA: Data analysis in process industrial value chains, spring 2022

Important results from the project

The project has developed a model for recipe optimization that considers aspects such as taste, waste, by-products, nutrition, and cost. Tests demonstrated that it is possible to vary the amount of meat and plant-based material (including rest streams/by-products) in meatballs while maintaining good quality. The platform is an early but valuable aid for food companies in product and process development, and there is interest from companies and municipalities.

Expected long term effects

The outcome of the project is an optimization platform where it is possible to optimize food recipes based on multiple aspects, such as; taste, nutritional content, waste, by-products, utilization of production equipment, and manufacturing costs. The platform can easily be used for new products if the user contributes data for the recipe and its ingredients. This makes food production more resilient and capable of delivering environmentally friendly food even during special events/circumstances.

Approach and implementation

The project was divided into two parallel tracks: food modeling and the development of an optimization platform. The food modeling was demonstrated for plant-based meatballs, and the model was then imported into the optimization platform. The meatballs were optimized based on several aspects, and a decision support system was developed to choose between the suggested recipes. These steps form the basis for creating Digital Food Identity Cards where data about the food can be included.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 12 December 2025

Reference number 2022-01485