• Energy Research

The increasing demand for lignocellulosic biomass for the production of biofuels provides value to vegetative plant tissue and leads to a paradigm shift for optimizing plant architecture in bioenergy crops. Plant height (PHT) is among the most important biomass yield components and is the focus of this review, with emphasis on the energy grasses maize (Zea mays) and sorghum (Sorghum bicolor). We discuss the scientific advances in the identification of PHT quantitative trait loci (QTLs) and the understanding of pathways and genes controlling PHT, especially gibberellins and brassinosteroids. We consider pleiotropic effects of QTLs or genes affecting PHT on other agronomically important traits and, finally, we discuss strategies for applying this knowledge to the improvement of dual-purpose or dedicated bioenergy crops.

Biofuels obtained from biomass have the potential to replace a substantial fraction of petroleum-based hydrocarbons that contribute to carbon emissions and are limited in supply. With the ultimate goal to maximize biomass yield for biofuel production, this review aims to evaluate prospects of different hybrid breeding schemes to optimally exploit heterosis for biomass yield in perennial ryegrass (Lolium perenne L.) and switchgrass (Panicum virgatum), two perennial model grass species for bioenergy production. Starting with a careful evaluation of current population and synthetic breeding methods, we address crucial topics to implement hybrid breeding, such as the availability and development of heterotic groups, as well as biological mechanisms for hybridization control such as self-incompatibility (SI) and male sterility (MS). Finally, we present potential hybrid breeding schemes based on SI and MS for the two bioenergy grass species, and discuss how molecular tools and synteny can be used to transfer relevant information for genes controlling these biological mechanisms across grass species.

Cell wall components, such as lignin, cellulose, and hemicelluloses, play an important role in the conversion efficiency of corn stover into ethanol. Understanding the molecular basis of cell wall formation is fundamental for marker assisted selection to develop lines more suitable for ethanol production. In this study, we evaluated a set of 40 European forage maize lines for cellulose, lignin, total hemicellulose, glucuronoarabinoxylan (GAX), and monosaccharides, such as arabinose (ara), xylose (xyl), and glucuronic acid (GlcA). The most significant correlations were observed between hemicelluloses and GAX (0.9), and hemicelluloses and cellulose (-0.81). Cell wall digestibility (CWD, estimated by digestible neutral detergent fiber, DNDF) was negatively correlated with Xyl (-0.34). The association analysis between the evaluated traits and polymorphisms within ten "lignin" genes revealed significant associations between polymorphisms within CCoAOMT1, CCoAOMT2, 4CL2 and C4H, and cellulose/xyl, cellulose, cellulose, and GclA, respectively. None of the QTPs identified in this study corresponded to previously reported CWD QTPs.

A better understanding of the genetic control of root development might allow one to develop lines with root systems with the potential to adapt to soils with limited nutrient availability. For this purpose, an association study (AS) panel consisting of 74 diverse set of inbred maize lines were screened for seedling root traits and adult plant root traits under two contrasting nitrogen (N) levels (low and high N). Allele re-sequencing of RTCL, RTH3, RUM1, and RUL1 genes related to root development was carried out for AS panel lines. Association analysis was carried out between individual polymorphisms, and both seedling and adult plant traits, while controlling for spurious associations due to population structure and kinship relations. Based on the SNPs identified in RTCL, RTH3, RUM1, and RUL1, lines within the AS panel were grouped into 16, 9, 22, and 7 haplotypes, respectively. Association analysis revealed several polymorphisms within root genes putatively associated with the variability in seedling root and adult plant traits development under contrasting N levels. The highest number of significantly associated SNPs with seedling root traits were found in RTCL (19 SNPs) followed by RUM1 (4 SNPs) and in case of RTH3 and RUL1, two and three SNPs, respectively, were significantly associated with root traits. RTCL and RTH3 were also found to be associated with grain yield. Thus considerable allelic diversity is present within the candidate genes studied and can be utilized to develop functional markers that allow identification of maize lines with improved root architecture and yield under N stress conditions.

Expected future cellulosic ethanol production increases the demand for biomass in the US Corn Belt. With low nutritious value, low nitrogen content, and compact biomass, maize cobs can provide a significant amount of cellulosic materials. The value of maize cobs depends on cob architecture, chemical composition, and their relation to grain yield as primary trait. Eight traits including cob volume, fractional diameters, length, weight, tissue density, and grain yield have been analyzed in this quantitative trait locus (QTL) mapping experiment to evaluate their inheritance and inter-relations. One hundred eighty-four recombinant inbred lines of the intermated B73 × Mo17 (IBM) Syn 4 population were evaluated from an experiment carried out at three locations and analyzed using genotypic information of 1,339 public SNP markers. QTL detection was performed using (1) comparison-wise thresholds with reselection of cofactors (α = 0.001) and (2) empirical logarithm of odds score thresholds (P = 0.05). Several QTL with small genetic effects (R2 = 2.9–13.4 %) were found, suggesting a complex quantitative inheritance of all traits. Increased cob tissue density was found to add value to the residual without a commensurate negative impact on grain yield and therefore enables for simultaneous selection for cob biomass and grain yield.

We analyzed five near-isogenic brown midrib hybrids in maize via pyrolysis/gas chromatography–mass spectrometry (Py/GC-MS) in order to determine how differing lignin composition and structure impacts individual bio-oil compounds. Twenty-six compounds were analyzed for differences among the five hybrids and between cob and stover materials. We found statistically significant differences for 9 compounds, when comparing the 5 hybrids, and 17 significant differences when comparing maize cobs with stover. Our data indicate that it may be possible to predict phenolic compounds within bio-oil based on cell wall lignin composition. The genetic variation observed in this study suggests that bio-oil quality can be improved by plant breeding.

Abstract Background Reduced lignin content leads to higher cell wall digestibility and, therefore, better forage quality and increased conversion of lignocellulosic biomass into ethanol. However, reduced lignin content might lead to weaker stalks, lodging, and reduced biomass yield. Genes encoding enzymes involved in cell wall lignification have been shown to influence both cell wall digestibility and yield traits. Results In this study, associations between monolignol biosynthetic genes and plant height (PHT), days to silking (DTS), dry matter content (DMC), and dry matter yield (DMY) were identified by using a panel of 39 European elite maize lines. In total, 10 associations were detected between polymorphisms or tight linkage disequilibrium (LD) groups within the COMT, CCoAOMT2, 4CL1, 4CL2, F5H, and PAL genomic fragments, respectively, and the above mentioned traits. The phenotypic variation explained by these polymorphisms or tight LD groups ranged from 6% to 25.8% in our line collection. Only 4CL1 and F5H were found to have polymorphisms associated with both yield and forage quality related characters. However, no pleiotropic polymorphisms affecting both digestibility of neutral detergent fiber (DNDF), and PHT or DMY were discovered, even under less stringent statistical conditions. Conclusion Due to absence of pleiotropic polymorphisms affecting both forage yield and quality traits, identification of optimal monolignol biosynthetic gene haplotype(s) combining beneficial quantitative trait polymorphism (QTP) alleles for both quality and yield traits appears possible within monolignol biosynthetic genes. This is beneficial to maximize forage and bioethanol yield per unit land area.

AbstractBackgroundAssessing the impact of the environment on plant performance requires growing plants under controlled environmental conditions. Plant phenotypes are a product of genotype × environment (G × E), and the Enviratron at Iowa State University is a facility for testing under controlled conditions the effects of the environment on plant growth and development. Crop plants (including maize) can be grown to maturity in the Enviratron, and the performance of plants under different environmental conditions can be monitored 24 h per day, 7 days per week throughout the growth cycle.ResultsThe Enviratron is an array of custom-designed plant growth chambers that simulate different environmental conditions coupled with precise sensor-based phenotypic measurements carried out by a robotic rover. The rover has workflow instructions to periodically visit plants growing in the different chambers where it measures various growth and physiological parameters. The rover consists of an unmanned ground vehicle, an industrial robotic arm and an array of sensors including RGB, visible and near infrared (VNIR) hyperspectral, thermal, and time-of-flight (ToF) cameras, laser profilometer and pulse-amplitude modulated (PAM) fluorometer. The sensors are autonomously positioned for detecting leaves in the plant canopy, collecting various physiological measurements based on computer vision algorithms and planning motion via “eye-in-hand” movement control of the robotic arm. In particular, the automated leaf probing function that allows the precise placement of sensor probes on leaf surfaces presents a unique advantage of the Enviratron system over other types of plant phenotyping systems.ConclusionsThe Enviratron offers a new level of control over plant growth parameters and optimizes positioning and timing of sensor-based phenotypic measurements. Plant phenotypes in the Enviratron are measured in situ—in that the rover takes sensors to the plants rather than moving plants to the sensors.