Data from crosses of outbred populations are commonly analyzed by least squares line-cross models to detect quantitative trait loci (QTL) that differ between breed. Alternatively, a least squares half-sib model can be used to detect QTL that segregate within lines. A more powerful, yet computationally expensive, alternative consists of simultaneously modeling QTL segregation between and within breed through a linear mixed fit. We used a linear mixed model approach to map QTL for ultimate meat pH in a cross between two outbred swine breeds. Comparing alternative models, allowed to test if QTL alleles were segregating exclusively between or within breed. An initial least square line-cross analysis revealed a putative QTL for one of the pH traits in chromosome 3 (SSC3). The mixed model analysis replicated those results, but also detected two new QTL in SSC15 and SSC1. Comparison between the fixed, random and mixed effects QTL models indicated that the novel QTL are likely to be segregating with similar frequencies within each of the original breeds. In summary, the increased computational cost of fitting linear mixed models in linkage analysis of crosses of outbred populations is justified by their potential to discover new QTL as well as the possibility to test for alternative inheritance models. Such information is extremely valuable when designing validation experiment in commercial lines.