Two new high-throughput techniques, computer tomography X-ray densitometry (CT scan) and pyrolysis molecular beam mass spectrometry (pyMBMS), coupled with quantitative trait loci (QTL) analysis, were tested as a means to overcome the time and cost associated with conventional characterization of biomass feedstock components. Applications of these two techniques were evaluated using hybrid poplar for the CT scan and loblolly pine for the pyMBMS. Segregating progeny from hybrid poplar varied in specific gravity, with individual mean estimates ranging from 0.21-0.41. Progeny from loblolly pine varied in lignin, ex cellulose, and mannan contents, with individual mean estimates of lignin content ranging from 28.7-33.1%, a cellulose content from 28.8-43.5% and mannan content from 4.2-10.1%. QTL analysis of the loblolly pine data suggested that eleven QTLs were associated with individual feedstock characteristics and that two QTLs for several feedstock components were linked to the same position on the loblolly pine genetic map. Each QTL individually accounted for 7-13% of the total phenotypic variation in associated loblolly pine feedstock components.