Including nutritional variability among and within feed ingredients in multi-objective optimization leads to mixture ratios that always meet the quality constraints within each Pareto front, for each target feed and environmental indicator (Fig. ). This is essential because using occasional off-line measurements as an indicator of the average ingredient nutritional composition may render the produced feed unsuitable for meeting the animal's nutritional requirements. For example, a mixture ratio optimized from accurate nutritional compositions of feed ingredients was compared with that optimized from off-line measurements (Fig. ). The two optimizations selected similar feed ingredients, but in different ratios and from different countries of origin. The extent to which nutritional requirements are not met when using off-line measurements was dependent on the target feeds and environmental indicators. For instance, broilers need more protein and fat than do pigs (Table ); thus, there is a higher preference for soybean than for barley in broiler feed (Fig. ). Offline determination of ingredient quality generally failed to meet the protein, fat, and starch requirements for pigs or the fat and ash requirements for broilers (Fig. ). The nutritional requirements for pigs were not met for 92% of the simulations, with a median sum of absolute deviations of 8.3 g/kg. For broilers, 74-84% of the simulations did not meet the requirements, with a median sum of absolute deviations of 1.8-3.1 g/kg for land stress and climate change, respectively.