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Basal stem rot caused by
Ganoderma boninense
is the major threat to oil palm cultivation in Southeast Asia, which accounts for 80% of palm oil production worldwide, and this disease is increasing in Africa. The use of resistant planting material as part of an integrated pest management of this disease is one sustainable solution. However, breeding for
Ganoderma
resistance requires long-term and costly research, which could greatly benefit from marker-assisted selection (MAS). In this study, we evaluated the effectiveness of an in silico genetic mapping approach that took advantage of extensive data recorded in an ongoing breeding program. A pedigree-based QTL mapping approach applied to more than 10 years’ worth of data collected during pre-nursery tests revealed the quantitative nature of
Ganoderma
resistance and identified underlying loci segregating in genetic diversity that is directly relevant for the breeding program supporting the study. To assess the consistency of QTL effects between pre-nursery and field environments, information was collected on the disease status of the genitors planted in genealogical gardens and modeled with pre-nursery-based QTL genotypes. In the field, individuals were less likely to be infected with
Ganoderma
when they carried more favorable alleles at the pre-nursery QTL. Our results pave the way for a MAS of
Ganoderma
resistant and high yielding planting material, and the provided proof-of-concept of this efficient and cost-effective approach could motivate similar studies based on diverse breeding programs.