The animal protein industry is under increasing pressure to become more sustainable. Whether we like or not, parts of the industry are currently viewed by many as significant contributors to climate change and habitat loss. The publication of high-level, average figures for the industry’s contribution to anthropogenic greenhouse gas (GHG) emissions has tarred all players with the same brush. To the average consumer, animal production is responsible for 14.5% of GHG emissions.
The reality of the situation is somewhat different, however. The production of animal protein is highly nuanced in terms of species, feed, production system and the environment, while the ability to improve the environmental footprint varies considerably from farm to farm.
Furthermore, in many cases the GHG footprint comparisons made between animal proteins and other foods are based on a functional unit of 1 kg of produce, irrespective of the composition of the food, its digestibility, and its nutritional value. While monitoring and reducing GHG emissions in animal production is important if we are to meet our collective commitments to the Paris Agreement, there are many other environmental variables that are of considerable significance. These include nitrogen and phosphorus pollution, soil quality, the use of water resources, land use, and impacts on biodiversity.
As calls for good environmental stewardship increase, it is in the interests of any progressive animal protein producer to ensure that their operations are assessed accordingly. This means measuring the full range of environmental footprints of animal production at farm level, using actual and specific farm data in a credible, auditable way.
Unlocking the value of sustainability can be achieved by measuring the footprint of the animal protein production at farm level using full Life Cycle Assessment (LCA), identifying areas for improvement, and making the necessary interventions. The use of advanced LCA tools, modelling and benchmarking are a powerful business diagnostic: too high a footprint is mostly associated with inefficiencies in the farming system, factors that often remain hidden or unrecognized unless this diagnostic is undertaken. Identifying these inefficiencies allows smart interventions to be modelled prior to implementation, increasing certainty that the interventions will be effective in reducing the footprint while at the same time capturing financial value for the farmer.
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21 March 2022
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