Variation in cell wall composition and bioenergy potential of rice straw

Abstract

In most grain crops the leaf and straw is often under-utilized. This biomass is largely plant cell wall, whose heterogeneous composition and recalcitrance limits end uses such as forage or bioenergy. I review the desirable traits for several bioenergy pathways from this biomass and identify traits in biomass that need to be optimized for enzymatic or thermochemical conversion of the biomass to energy. Sufficient variation exists across species and varieties for improving these traits through breeding. I assess variation in cellulose, lignin, hemicellulose, ash, total glucose, total xylose, mixed linkage glucan, saccarification yield and efficiency, hydroxyproline content and bulk density across two environments in the leaf and stem tissue of five rice varieties. Environment and tissue type are highly influential on the composition and yield phenotypes, and some traits perform better than others at predicting bioenergy yield in the field environment. Optimizing specific bioenergy-related phenotypes in isolation is not sufficient as overall crop health relies on many components. The plant cell wall serves an important function in crop health as a critical barrier against pests and diseases. I investigate the role of a family of putative broad spectrum defense response genes in rice, OsOXOs, that degrade oxalic acid: a pathogenicity factor. When expression of these genes is modified, I find a large impact on disease resistance to Sclerotinia sclerotiorum but little impact in the presence of Rhizoctonia solani. OsOXOs must play an important role in defense against S. sclerotiorum which relies on oxalic acid as a pathogenicity factor, because OsOXOs can degrade oxalic acid. R. solani utilizes a broader range of enzymes and compounds, limiting the effectiveness of OsOXOs against R. solani. With the bioenergy phenotyping methods optimized above, I assess saccharification yield of a rice mapping population, along with other agronomic traits including total biomass, flowering time, grain yield, and plant height. Transgressive segregation is apparent for all traits and quantitative trait loci (QTL) mapping approaches are presented. With the methods and populations evaluated here, we are closer to identifying the conditions and genes that can maximize biomass tailored for many purposes.