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Background  Biofuels derived from lignocellulosic plant material are an important component of current renewable energy strategies. Improvement efforts in biofuel feedstock crops have been primarily focused on increasing biomass yield with less consideration for tissue quality or composition. Four primary components found in the plant cell wall contribute to the overall quality of plant tissue and conversion characteristics, cellulose and hemicellulose polysaccharides are the primary targets for fuel conversion, while lignin and ash provide structure and defense. We explore the genetic architecture of tissue characteristics using a quantitative trait loci (QTL) mapping approach in  Panicum hallii , a model lignocellulosic grass system. Diversity in the mapping population was generated by crossing xeric and mesic varietals, comparative to northern upland and southern lowland ecotypes in switchgrass. We use near-infrared spectroscopy with a primary analytical method to create a  P. hallii  specific calibration model to quickly quantify cell wall components.    Results  Ash, lignin, glucan, and xylan comprise 68% of total dry biomass in  P. hallii : comparable to other feedstocks. We identified 14 QTL and one epistatic interaction across these four cell wall traits and found almost half of the QTL to localize to a single linkage group.    Conclusions   Panicum hallii  serves as the genomic model for its close relative and emerging biofuel crop, switchgrass ( P. virgatum ). We used high throughput phenotyping to map genomic regions that impact natural variation in leaf tissue composition. Understanding the genetic architecture of tissue traits in a tractable model grass system will lead to a better understanding of cell wall structure as well as provide genomic resources for bioenergy crop breeding programs.    Electronic supplementary material  The online version of this article (10.1186/s13068-018-1033-z) contains supplementary material, which is available to authorized users.

Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii