Leaf water content is one of the most common physiological parameters limiting efficiency of photosynthesis and biomass productivity in plants including Miscanthus. Therefore, it is of great significance to determine or predict the water content quickly and nondestructively. In this study, we explored the relationship between leaf water content and diffuse reflectance spectra in Miscanthus. Three multivariate calibrations including partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function (RBF) neural network (NN) were developed for the models of leaf water content determination. The non-linear models including RBF_LSSVR and RBF_NN showed higher accuracy than the PLS and Lin_LSSVR models. Moreover, 75 sensitive wavelengths were identified to be closely associated with the leaf water content in Miscanthus. The RBF_LSSVR and RBF_NN models for predicting leaf water content, based on 75 characteristic wavelengths, obtained the high determination coefficients of 0.9838 and 0.9899, respectively. The results indicated the non-linear models were more accurate than the linear models using both wavelength intervals. These results demonstrated that visible and near-infrared (VIS/NIR) spectroscopy combined with RBF_LSSVR or RBF_NN is a useful, nondestructive tool for determinations of the leaf water content in Miscanthus, and thus very helpful for development of drought-resistant varieties in Miscanthus.

Miscanthus is a perennial wild grass that is of global importance for paper production, roofing, horticultural plantings, and an emerging highly productive temperate biomass crop. We report a chromosome-scale assembly of the paleotetraploid M. sinensis genome, providing a resource for Miscanthus that links its chromosomes to the related diploid Sorghum and complex polyploid sugarcanes. The asymmetric distribution of transposons across the two homoeologous subgenomes proves Miscanthus paleo-allotetraploidy and identifies several balanced reciprocal homoeologous exchanges. Analysis of M. sinensis and M. sacchariflorus populations demonstrates extensive interspecific admixture and hybridization, and documents the origin of the highly productive triploid bioenergy crop M. × giganteus. Transcriptional profiling of leaves, stem, and rhizomes over growing seasons provides insight into rhizome development and nutrient recycling, processes critical for sustainable biomass accumulation in a perennial temperate grass. The Miscanthus genome expands the power of comparative genomics to understand traits of importance to Andropogoneae grasses.

Background: Grain protein content (GPC) is an important quality determinant for barley used as malt, feed as well as food. It is controlled by a complex genetic system. GPC differs greatly among barley genotypes and is also variable across different environments. It is imperative to understand the genetic control of barley GPC and identify the genotypes with less variation under the different environments. Results: In this study, 59 cultivated and 99 Tibetan wild barley genotypes were used for a genome-wide association study (GWAS) and a multi-platform candidate gene-based association analysis, in order to identify the molecular markers associated with GPC. Tibetan wild barley had higher GPC than cultivated barley. The significant correlation between GPC and diastatic power (DP), and malt extract confirmed the importance of GPC in determining malt quality. Diversity arrays technology (DArT) markers associated with barley GPC were detected by GWAS. In addition, GWAS revealed two HvNAM genes as the candidate genes controlling GPC. No association was detected between HvNAM1 polymorphism and GPC, while a single nucleotide polymorphism (SNP) (798, P < 0.01), located within the second intron of HvNAM2, was associated with GPC. There was a significant correlation between haplotypes of HvNAM1, HvNAM2 and GPC in barley. Conclusions: The GWAS and candidate gene based-association study may be effectively used to determine the genetic variation of GPC in barley. The DArT markers and the polymorphism of HvNAM genes identified in this study are useful in developing high quality barley cultivars in the future. HvNAM genes could play a role in controlling barley GPC.