Disease phenotyping is an important process for both production field scouting and disease rating in soybean [Glycine max (L.) Merr.] breeding programs because yield is affected by many pathogens including charcoal rot, Macrophomina phaseolina. Charcoal rot has limited chemical control options and affects over 500 species worldwide making crop rotation a difficult management strategy as well. Due to these management challenges, breeding for disease resistance is a valuable strategy, however traditional disease phenotyping relies on human visual ratings which are prone to human error and have scalability issues when moving to large production schemes or modern breeding programs. Furthermore, there is currently little understanding of the genetic control of charcoal rot resistance in soybean. This study utilized hyperspectral imaging to determine its potential for early detection of charcoal rot and to uncover hyperspectral disease signatures for future use in phenotyping tools. QTL mapping was used to further the knowledge on the genetic control of charcoal rot in soybean. Hyperspectral imaging combined with spectral angle mapper analysis uncovered the importance of the non-visible NIR regions in the detection of not yet visible early symptom development on the interior of soybean stems. QTL mapping of a recombinant inbred line family identified two small effect QTL in relation to charcoal rot resistance each explaining 9.9% of the variation. Future work can build on these findings to uncover additional sources of resistance for improved breeding and to identify disease signatures of other diseases in order to develop multispectral cameras for identification of charcoal rot and other soybean diseases for field phenotyping.