Food chain model for sustainable food chains and food waste prevention

When developing a model to assess the environmental impact of different production methods, one focus was on analysing chocolate that uses cocoa pulp as a sugar substitute. The model comprises five toolboxes, ranging from scenario analyses to food losses and environmental impacts. A comparison with conventional chocolate formed a central part of the study.

The main product of this project comprises five modules (toolboxes), which together form the Sustainable Food Chain Model (FCM) and enable the modelling of the environmental effects of entire value chains. This allows scenarios of value chains (VCs) to be modelled with their effects on the environment.

The first toolbox "Scenarios" contains a mass and energy flow analysis from agricultural production through all stages of the value chain to the household or restaurant where the food is consumed. Each stage of the VAC is characterised by processes (e.g. harvesting, storage). Food losses (e.g. 5% edible harvest losses) and environmentally relevant processes (e.g. 2kg diesel consumption per kg harvest yield) are assigned to the processes. This toolbox is called "scenarios" because several scenarios can be modelled for each VAC. This allows the effect of changes in parameters (e.g. electricity mix used) on the environment to be estimated. The model allows the stages of the VAC to be freely labelled and arranged so that different cases can be mapped (e.g. one or more processing stages). The path of the food can branch out, e.g. if part of the food from processing is delivered to the retail trade and the rest to catering establishments. Fig. 1 shows an example of the mass flow analysis of chocolate with three processing stages and branching into retail and catering.

The second toolbox "Causes" contains a list of causes to which food losses can be assigned. In this model, food losses are not statically classified as avoidable or unavoidable, but the causes of food losses are flexibly divided into avoidable and unavoidable depending on the issue at hand. This makes modelling compatible with different definitions.

In the third toolbox, "Environmental impacts", environmentally relevant processes are linked with data sets from life cycle assessment databases and weighted with factors. This allows data from different databases as well as primary and literature data to be combined and harmonised.

In two further toolboxes, suitable sets of environmental assessment methods can be created to answer specific questions and a list of sources can be provided. In this way, all entered data can be linked to sources and commented on individually.

At the current stage of development, the FCM can model entire VACs. Scenarios can be created and compared by changing parameters. The comparisons can focus on any aspect of the VACs, e.g. on the quantities of food losses per stage of the VAC, per process or per cause and broken down into avoidable and unavoidable. The environmental effects of processes, end products, food losses or entire scenarios can also be compared, e.g. the reference scenario "Cheese production with feeding of whey" with the alternative scenario "Cheese production with valorisation of whey to whey protein isolate and lactose powder".

Successful measures can be derived from the results in order to reduce environmental impacts in the following three fields of action:

1. Producing food more ecologically (e.g. processing with renewable energy instead of fossil fuels)
2. Increase the efficiency of VACs by avoiding food waste (e.g. halving food waste in households)
3. More sustainable products and menus selected by consumers.

The integration of further functionalities into the FCM in follow-up projects should enable the modelling of shopping baskets and linked VACs, the operation of the tool via target group-specific user interfaces and the constructive collaboration of different stakeholders thanks to user environments with specific user rights.

Many thanks to Ursina Krähenmann and Anian Schreiber for their advisory support of the project and to Erich Zbinden, Davide Stallone and Nadina Müller for their great commitment to the project.

This text was translated with DeepL