Expanding the current coverage of the study to include more constraints and ingredients, many of which have been studied by NIRS , is possible with our approach. To create a more diverse and variable ingredient portfolio, the inclusion of the local availability of ingredients at the production site could be added as a model constraint; however, such information was unavailable at the time of analysis. The feed ratios shown in this study are thus possible only if comparable ingredients are available and if they are produced in a sufficiently large amount to meet the demand. Analogously, our approach may better quantify the footprint and thereby further optimize it through trade-off mixture ratios, with greater diversification of ingredient provenances. Data harmonization from different measurement locations does require robust analytical quality control, such that the difference in measurement location can be unambiguously distinguished from the geographical origin for all the feed ingredients. Greater transparency could be achieved through a minor addition in the data collection to integrate more feed ingredients from different origins for each location (e.g., as for sunflower meal, Table , Fig. ). Furthermore, increasing the geographical resolution of the LCA from country to region would better include regional agricultural practices involved in crop cultivation, which is particularly relevant for large and heterogeneous countries such as Brazil and Ukraine.