Magnetically recoverable photocatalysts based on metal oxide nanostructures (Fe and Zn)

The synthesis of y-Fe203&ZnO hybrid nanocomposites has been carried out by a solvothermal process at low temperature evaluating the influence of different experimental parameters and conditions. Several techniques such as X-Ray diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (HR-TEM), Vibrating Sample Magnetometry (VSM), Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), Dynamic Light Dispersion (DLS), Thermogravimetric Analysis (TGA) and UV-Vis Spectroscopy have been used to characterize the size, shape, structure, chemical composition, purity, crystalline phase and spectroscopic, magnetic, and finally the photocatalytic properties of nanocomposites prepared. Based on the results obtained, under irradiation ofUV-Vis light, the nanocomposites of y-Fe203-ZnO synthesised both at 6 hand 12 hat 120°C demonstrate a high photocatalytic activity (PCA) compared to pure y-Fe203 and ZnO samples for the degradation of methylene blue (MB), used as a cationic dye model. The percentage of degradation obtained for both cases was much higher than that obtained for the pure compounds of y-Fe203 and ZnO (85% and 81% vs 51% and 46%, respectively). Also, the study of stability, magnetic recovery and recyclability in MB dye degradation was carried out. For this purpose, photocatalytic tests were performed by reusing these hybrid nanocomposites during successive cycles. It has been verified that the PCA of these nanocomposites is maintained after several cicles of experiments with new MB solutions demonstrating their high photocatalytic stability. In conclusion, y-Fe203-ZnO hybrid nanostructures are a suitable candidate for its use in environmental applications, and to solve problems of removal of organic contaminants in the wastewater treatments as a magnetically recoverable photocatalyst

Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35–43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations

Genome‐Wide Association Study for Nine Plant Architecture Traits in Sorghum

Sorghum [ (L) Moench], an important grain and forage crop, is receiving significant attention as a lignocellulosic feedstock because of its water-use efficiency and high biomass yield potential. Because of the advancement of genotyping and sequencing technologies, genome-wide association study (GWAS) has become a routinely used method to investigate the genetic mechanisms underlying natural phenotypic variation. In this study, we performed a GWAS for nine grain and biomass-related plant architecture traits to determine their overall genetic architecture and the specific association of allelic variants in gibberellin (GA) biosynthesis and signaling genes with these phenotypes. A total of 101 single-nucleotide polymorphism (SNP) representative regions were associated with at least one of the nine traits, and two of the significant markers correspond to GA candidate genes, () and (), affecting plant height and seed number, respectively. The resolution of a previously reported quantitative trait loci (QTL) for leaf angle on chromosome 7 was increased to a 1.67 Mb region containing seven candidate genes with good prospects for further investigation. This study provides new knowledge of the association of GA genes with plant architecture traits and the genomic regions controlling variation in leaf angle, stem circumference, internode number, tiller number, seed number, panicle exsertion, and panicle length. The GA gene affecting seed number variation () and the genomic region on chromosome 7 associated with variation in leaf angle are also important outcomes of this study and represent the foundation of future validation studies needed to apply this knowledge in breeding programs