In a previous article, we discussed the benefits that AI can bring to the industrialization of Life Cycle Assessment (LCA) in the food sector. In this new article, we discuss its inherent limitations and how it is possible to go beyond LCA while remaining scientifically sound.
The criticisms of LCA applied to food generally fall into two categories: a “productive” category and a “service” category.
The “ productivist “ axis consists of the observation that LCA considers agriculture in its function of “food production”, to the exclusion of any other function (such as rurality, maintenance of territories, etc.). This is reflected in the LCA indicators of “environmental performance”, which are always reduced to the “quantity of product produced”: the impact “per kilo of product produced” is thus eliminated, which naturally favours productivist systems.
The “ service “ axis criticizes the fact that LCA focuses only on the negative impacts of agriculture, excluding any consideration of the positive impacts (the “ecosystem services” provided by agriculture). Inherited from the industrial sector, LCA sees agriculture from the outset as a polluting activity whose efficiency must be optimised. It therefore struggles to take account of environmental issues in their entirety, as well as more harmonious agricultural practices.
These criticisms explain why LCA, as a method of analytical accounting at the level of the finished product, naturally favors very intensive agricultural production systems and is not a method that promotes organic farming or extensive production practices.
To assess the impacts of food chains in a more relevant way, it is necessary to go beyond LCA: to maintain the scientific approach of modeling and accounting for impacts, while understanding the complex and specific nature of food systems, their territorial dimension and the environmental services associated with them. A promising direction of unification is that developed by Olivier Thérond and Michel Duru of INRAE, who propose to combine LCA (impact-oriented) with the accounting of ecosystem services (service-oriented).
The authors show that these two approaches (impact and ecosystem services) are complementary and can be modeled in a coherent and quantitative way to ensure a “fair” comparison between conventional, organic and agroecological crop production systems. By taking these “ecosystem services” into account, we can see that the ranking is reversed with respect to “impacts”: sustainable practices are then favoured over conventional practices, which are still more efficient from an LCA perspective.
This work shows that it is possible, relevant and, above all, desirable to go beyond LCA to assess the impact of food products. The definition of a global model that allows linking the reduction of impacts and the development of ecosystem services is particularly important in the current political and regulatory context, where the Eco-Score methodology has to be finalised during 2023.
This global model will also be the key to tomorrow’s economic model, as it will be necessary to agree on how to reward farmers for implementing sustainable practices and environmental services, and to accompany transitions. Finally, it will allow consumers to have a fairer, more informed and more “positive” vision of their food by integrating all aspects of agricultural production.