AI assisted prediction and optimisation of environmental impacts, nutritional and food quality in food product development

Main Presenter:    Thomas Nemecek 

Co-Authors:   Daniel Auner     Romeo Racz      Jasper Van Altena                                    

The food industry plays a key role to contribute to the mitigation of the environmental impacts by using food ingredients with low environmental burdens, by reducing the environmental impacts of processing, packaging, storage, and transports, and by offering a product basket of high quality to the consumers with low environmental impact and high nutritional value, which is at the same time safe, tasty, and attractive. However, food developers nowadays face a multidimensional, highly complex optimisation problem with many parameters to consider. The EU project OptiSignFood (“Data Science and AI assisted holistic software to digitally design optimised high quality and safe food products with minor environmental impact”) aims at developing a tool for the food industry to integrate environmental, nutritional, health, sensorial, and safety parameters into the development process of new food products.
Environmental impacts of food ingredients are calculated using LCA methodology and drawn from different LCI databases. The data are harmonized, adapted and standardized for integration into the meta-database. Nutritional parameters are taken from the EuroFIR database. Nutritional indices are calculated to provide an aggregated metric of nutritional quality and/or potential health impacts, namely the nutrient-rich food index, the Nutri-Score, and the Health Nutritional Index. Based on laboratory tests, colour and pH prediction models are established. To link the nutritional, life cycle inventory and the laboratory parameter databases, a semi-automatic standardization approach was applied, combining manual and automatic linking of food entries, based on the names and the LanguaL classification.
Users can prepare recipes by choosing food ingredients and ranges for their amounts. The tool then predicts environmental impacts, nutrient values, nutritional indices, food quality and safety parameters. The user can then further optimize recipes by adjusting selected parameters.
OptiSignFood leads to faster product development with less products being rejected and food waste being avoided. Manufacturers can react faster to societal and market trends, e.g. replacing animal-sourced ingredients by plant-based alternatives. The systematic consideration of environmental impacts and food quality, while ensuring food safety will lead to more nutritious food with lower environmental impacts and improved resource efficiency.

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