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Updated: Jan 14, 2026

Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management
Published on: July 14, 2023
Dataset of reference values for the quantification of net primary production use (or biotic resource use) of feed
Samuel Le Féon1, Joël Aubin1, Aurélie Wilfart1
1INRAE, Institut Agro, SAS, 65 rue de Saint Brieuc, 35042 Rennes, France.
Abstract:
In order to quantify the pressure of livestock feeding practices on biotic resources with Life Cycle Assessment (LCA), Papatryphon et al. (2004) developed a midpoint impact category called Net Primary Production Use (NPPU). It is expressed in kg of carbon by kg of product and is derived from the carbon-content of the feed ingredient, adjusted by its trophic level following the formula developed by Pauly and Christensen (1995). Another name is found in literature for NPPU as Biotic Resource Use (BRU), Cashion et al. (2016) arguing that both are used for aquaculture, when BRU is also used for fisheries. Since, it has been widely used in LCA, especially to compare different feed solutions for aquaculture. NPPU has been calculated essentially for fish-based and plant-based feed ingredients. Despite the indicator was used in numerous publications for years, there is currently no proper database of reference values easy-to-use and validated by peers that includes a wide range of fish-based and plant-based feed ingredients. This data paper aims to produce this reference dataset of values to be used as standard in future studies. In addition, it also proposes values for other-animal-based feed ingredients, freshwater-fish-based feed ingredients and milk-based ingredients. Therefore, it is recommended to be used in future LCA studies of aquaculture. This data paper also provides the calculation rules and hypotheses made in the calculation, in order to explain the procedure, allowing readers to reproduce results and calculate values for their own ingredients. Finally, different levels (Tiers) of specificity are proposed for the datasets, that use more detailed primary data, associated with more uncertainty in return.
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