Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two lines. The power of such QTL detection and mapping strategies and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL detected in such populations only represent a small part of the genetic architecture of the trait. Besides, the effects of only two alleles are characterized, which is of limited interest to the breeder. On the other hand, common pedigree breeding material remains unexploited for QTL mapping. From a pre-breeding perspective, the utilization of the good quality phenotypic data generated by breeders can be improved through the search and manipulation of QTL. The development of statistical techniques suitable for QTL mapping in general conventional breeding populations is thus challenging. In this study, we extend QTL mapping methodology to a generalized framework, based on a two-step IBD variance component approach, applicable to any type of breeding population coming from inbred parents. The proposed developments attempt to make full use of any inferable relatedness information between the parents. The power and accuracy of this method were assessed on simulated data mimicking conventional breeding programs in cereals, in an effort to reproduce actual conditions of marker and gene allelic frequencies across the parental lines. A wide range of breeding scenarios and of genetic architectures was explored. We demonstrated that taking into account the estimable relatedness between the parents significantly improved the power and accuracy of the QTL parameter estimations.