Sarah Hawkins

Quantification of hydroxycinnamic acids and lignin in perennial forage and energy grasses by Fourier-transform infrared spectroscopy and partial least squares regression.

Levels of lignin and hydroxycinnamic acid wall components in three genera of forage grasses (Lolium,Festuca and Dactylis) have been accurately predicted by Fourier-transform infrared spectroscopy using partial least squares models correlated to analytical measurements. Different models were derived that predicted the concentrations of acid detergent lignin, total hydroxycinnamic acids, total ferulate monomers plus dimers, p-coumarate and ferulate dimers in independent spectral test data from methanol extracted samples of perennial forage grass with accuracies of 92.8%, 86.5%, 86.1%, 59.7% and 84.7% respectively, and analysis of model projection scores showed that the models relied generally on spectral features that are known absorptions of these compounds. Acid detergent lignin was predicted in samples of two species of energy grass, (Phalaris arundinacea and Pancium virgatum) with an accuracy of 84.5%.

Accelerating the domestication of a bioenergy crop: identifying and modelling morphological targets for sustainable yield increase in Miscanthus

To accelerate domestication of Miscanthus, an important energy crop, 244 replicated genotypes, including two different species and their hybrids, were analysed for morphological traits and biomass yield over three growing seasons following an establishment phase of 2 years in the largest Miscanthus diversity trial described to date. Stem and leaf traits were selected that contributed both directly and indirectly to total harvested biomass yield, and there was variation in all traits measured. Morphological diversity within the population was correlated with dry matter yield (DMY) both as individual traits and in combination, in order to determine the respective contributions of the traits to biomass accumulation and to identify breeding targets for yield improvement. Predictive morphometric analysis was possible at year 3 within Miscanthus sinensis genotypes but not between M. sinensis, Miscanthus sacchariflorus, and interspecific hybrids. Yield is a complex trait, and no single simple trait explained more than 33% of DMY, which varied from 1 to 5297g among genotypes within this trial. Associating simple traits increased the power of the morphological data to predict yield to 60%. Trait variety, in combination, enabled multiple ideotypes, thereby increasing the potential diversity of the crop for multiple growth locations and end uses. Both triploids and interspecific hybrids produced the highest mature yields, indicating that there is significant heterosis to be exploited within Miscanthus that might be overlooked in early selection screens within years 1–3. The potential for optimizing biomass yield by selecting on the basis of morphology is discussed.

A novel grass hybrid to reduce flood generation in temperate regions

We report on the evaluation of a novel grass hybrid that provides efficient forage production and could help mitigate flooding. Perennial ryegrass (Lolium perenne) is the grass species of choice for most farmers, but lacks resilience against extremes of climate. We hybridised L. perenne onto a closely related and more stress-resistant grass species, meadow fescue Festuca pratensis. We demonstrate that the L. perenne × F. pratensis cultivar can reduce runoff during the events by 51% compared to a leading UK nationally recommended L. perenne cultivar and by 43% compared to F. pratensis over a two year field experiment. We present evidence that the reduced runoff from this Festulolium cultivar was due to intense initial root growth followed by rapid senescence, especially at depth. Hybrid grasses of this type show potential for reducing the likelihood of flooding, whilst providing food production under conditions of changing climate.

Contrasting geographic patterns of genetic variation for molecular markers vs. phenotypic traits in the energy grass Miscanthus sinensis

Species and hybrids of Miscanthus are a promising energy crop, but their outcrossing mating systems and perennial life cycles are serious challenges for breeding programs. One approach to accelerating the domestication of Miscanthus is to harness the tremendous genetic variation that is present within this genus using phenotypic data from extensive field trials, high‐density genotyping and sequencing technologies, and rapidly developing statistical methods of relating phenotype to genotype. The success of this approach, however, hinges on detailed knowledge about the population genetic structure of the germplasm used in the breeding program. We therefore used data for 120 single‐nucleotide polymorphism and 52 simple sequence repeat markers to depict patterns of putatively neutral population structure among 244 Miscanthus genotypes grown in a field trial near Aberystwyth (UK) and delineate a population of 145 M. sinensis genotypes that will be used for association mapping and genomic selection. Comparative multivariate analyses of molecular marker and phenotypic data for 17 traits related to phenology, morphology/biomass, and cell wall composition revealed significant geographic patterns in this population. A longitudinal cline accounted for a substantial proportion of molecular marker variation (R2 = 0.60, P = 3.4 × 10−15). In contrast, genetic variation for phenotypic traits tended to follow latitudinal and altitudinal gradients, with several traits appearing to have been affected by divergent selection (i.e., QST >> FST). These contrasting geographic trends are unusual relative to other plants and provide opportunities for powerful studies of phenotype–genotype associations and the evolutionary history of M. sinensis.

Impact of drought stress on growth and quality of miscanthus for biofuel production

Miscanthus has a high potential as a biomass feedstock for biofuel production. Drought tolerance is an important breeding goal in miscanthus as water deficit is a common abiotic stress and crop irrigation is in most cases uneconomical. Drought may not only severely reduce biomass yields, but also affect biomass quality for biofuel production as cell wall remodeling is a common plant response to abiotic stresses. The quality and plant weight of 50 diverse miscanthus genotypes were evaluated under control and drought conditions (28 days no water) in a glasshouse experiment. Overall, drought treatment decreased plant weight by 45%. Drought tolerance – as defined by maintenance of plant weight – varied extensively among the tested miscanthus genotypes and ranged from 30% to 110%. Biomass composition was drastically altered due to drought stress, with large reductions in cell wall and cellulose content and a substantial increase in hemicellulosic polysaccharides. Stress had only a small effect on lignin content. Cell wall structural rigidity was also affected by drought conditions; substantially higher cellulose conversion rates were observed upon enzymatic saccharification of drought‐treated samples with respect to controls. Both cell wall composition and the extent of cell wall plasticity under drought varied extensively among all genotypes, but only weak correlations were found with the level of drought tolerance, suggesting their independent genetic control. High drought tolerance and biomass quality can thus potentially be advanced simultaneously. The extensive genotypic variation found for most traits in the evaluated miscanthus germplasm provides ample scope for breeding of drought‐tolerant varieties that are able to produce substantial yields of high‐quality biomass under water deficit conditions. The higher degradability of drought‐treated samples makes miscanthus an interesting crop for the production of second‐generation biofuels in marginal soils.

Genetic relationships between spring emergence, canopy phenology and biomass yield increase the accuracy of genomic prediction in Miscanthus

Multivariate analysis unveils complex genetic relationships between spring emergence, canopy phenology and biomass yield in Miscanthus, leading to increased response to selection and substantial improvements in genome-wide prediction.

Predicting future biomass yield in Miscanthus using the carbohydrate metabolic profile as a biomarker

In perennial energy crop breeding programmes, it can take several years before a mature yield is reached when potential new varieties can be scored. Modern plant breeding technologies have focussed on molecular markers, but for many crop species, this technology is unavailable. Therefore, prematurity predictors of harvestable yield would accelerate the release of new varieties. Metabolic biomarkers are routinely used in medicine, but they have been largely overlooked as predictive tools in plant science. We aimed to identify biomarkers of productivity in the bioenergy crop, Miscanthus, that could be used prognostically to predict future yields. This study identified a metabolic profile reflecting productivity in Miscanthus by correlating the summer carbohydrate composition of multiple genotypes with final yield 6 months later. Consistent and strong, significant correlations were observed between carbohydrate metrics and biomass traits at two separate field sites over 2 years. Machine‐learning feature selection was used to optimize carbohydrate metrics for support vector regression models, which were able to predict interyear biomass traits with a correlation (R) of >0.67 between predicted and actual values. To identify a causal basis for the relationships between the glycome profile and biomass, a 13C‐labelling experiment compared carbohydrate partitioning between high‐ and low‐yielding genotypes. A lower yielding and slower growing genotype partitioned a greater percentage of the 13C pulse into starch compared to a faster growing genotype where a greater percentage was located in the structural biomass. These results supported a link between plant performance and carbon flow through two rival pathways (starch vs. sucrose), with higher yielding plants exhibiting greater partitioning into structural biomass, via sucrose metabolism, rather than starch. Our results demonstrate that the plant metabolome can be used prognostically to anticipate future yields and this is a method that could be used to accelerate selection in perennial energy crop breeding programmes.