Soybean [Glycine max (L.) Merr.] seeds contain high levels of mineral nutrients essential for human and animal nutrition. High throughput elemental profiling (ionomics) has identified mutants in model plant species grown in controlled environments. Here, we describe a method for identifying potential soybean ionomics mutants grown in a field setting and apply it to 975 N-nitroso-N-methylurea (NMU) mutagenized lines. After performing a spatial correction, we identified mutants using either visual scoring of standard score (z-score) plots or computational ranking of putative mutants followed by visual confirmation. Although there was a large degree of overlap between the methods, each method identified unique lines. The visual scoring approach identified 22 out of 427 (5%) potential mutants, 70% (16 out of 22) of which were confirmed when seeds from the same parent plant were regrown in the field. We also performed simulations to determine an optimal strategy for screening large populations. All data from the screen is available at the Ionomics Hub File Transfer Page (http://www.ionomicshub.org/home/PiiMS/dataexchange).