Fault Reactivation Analysis Using Microearthquake Clustering Based on Signal-to-Noise Weighted Waveform Similarity

The cluster formation of about 2000 induced microearthquakes (mostly M L < 2) is studied using a waveform similarity technique based on cross-correlation and a subsequent equivalence class approach. All events were detected within two separated but neighbouring seismic volumes close to the geothermal powerplants near Landau and Insheim in the Upper Rhine Graben, SW Germany between 2006 and 2013. Besides different sensors, sampling rates and individual data gaps, mainly low signal-to-noise ratios (SNR) of the recordings at most station sites provide a complication for the determination of a precise waveform similarity analysis of the microseismic events in this area. To include a large number of events for such an analysis, a newly developed weighting approach was implemented in the waveform similarity analysis which directly considers the individual SNRs across the whole seismic network. The application to both seismic volumes leads to event clusters with high waveform similarities within short (seconds to hours) and long (months to years) time periods covering two magnitude ranges. The estimated relative hypocenter locations are spatially concentrated for each single cluster and mirror the orientations of mapped faults as well as interpreted rupture planes determined from fault plane solutions. Depending on the waveform cross-correlation coefficient threshold, clusters can be resolved in space to as little as one dominant wavelength. The interpretation of these observations implies recurring fault reactivations by fluid injection with very similar faulting mechanisms during different time periods between 2006 and 2013

Mapping quantitative trait loci (QTLs) associated with dough quality in a soft × hard bread wheat progeny

Bread wheat (Triticum aestivum L.) quality is a key trait for baking industry exigencies and broad consumer preferences. The main goal of this study was to undertake quantitative trait loci (QTL) analyses for bread wheat quality in a set of 79 recombinant inbred lines (RILs) derived from a soft × hard bread wheat cross. Field trials were conducted over two years, utilizing a randomized complete block design. Dough quality was evaluated by sedimentation test, mixograph and alveograph analysis. Protein content was measured by near-infrared reflectance analysis and grain hardness was determined by the single kernel characterization system (SKCS). A genetic map based on 263 SSR markers and glutenin loci was constructed. Composite interval mapping (CIM) analysis detected a total of 20 QTLs distributed among ten chromosomes which were associated with variations in quality traits. Results confirmed the previous investigations on the known relationship between storage-protein alleles and dough quality, and detected new and stable QTLs related to dough quality parameters on chromosomes 2A, 7A, 5B and 1D. These new QTLs could be further investigated. Also, in this study, some RILs showed very high dough extensibility values which involve future validation studies for QTLs associated with to this trait

A case study of Kanban implementation within the Pharmaceutical Supply Chain

The paper explores the implementation of the kanban system, which is a Lean technique, within the Pharmaceutical Supply Chain (PSC). The case study provides insight to the benefits and challenges arising from the application of this technique, within a group of cooperative pharmacists, in Greece. The research questions developed from the review of the literature were tested using evidence from field-based, action research within a pharmaceutical organisation. The reported case study contributes to the longer term debate on assessing the Lean maturity level within the healthcare sector. There are two primary findings: i) that the adoption of kanban system provides a strategic benefit and improves the quality of services. ii) it also provides a basis for a strategy of operational change; it gives the opportunity to the organisation to move away from the current push delivery and logistics systems toward improved logistics strategy models

Quantitative trait loci conferring grain mineral nutrient concentrations in durum wheat 3 wild emmer wheat RIL population

Mineral nutrient malnutrition, and particularly deficiency in zinc and iron, afflicts over 3 billion people worldwide. Wild emmer wheat, Triticum turgidum ssp. dicoccoides, genepool harbors a rich allelic repertoire for mineral nutrients in the grain. The genetic and physiological basis of grain protein, micronutrients (zinc, iron, copper and manganese) and macronutrients (calcium, magnesium, potassium, phosphorus and sulfur) concentration was studied in tetraploid wheat population of 152 recombinant inbred lines (RILs), derived from a cross between durum wheat (cv. Langdon) and wild emmer (accession G18-16). Wide genetic variation was found among the RILs for all grain minerals, with considerable transgressive effect. A total of 82 QTLs were mapped for 10 minerals with LOD score range of 3.2–16.7. Most QTLs were in favor of the wild allele (50 QTLs). Fourteen pairs of QTLs for the same trait were mapped to seemingly homoeologous positions, reflecting synteny between the A and B genomes. Significant positive correlation was found between grain protein concentration (GPC), Zn, Fe and Cu, which was supported by significant overlap between the respective QTLs, suggesting common physiological and/or genetic factors controlling the concentrations of these mineral nutrients. Few genomic regions (chromosomes 2A, 5A, 6B and 7A) were found to harbor clusters of QTLs for GPC and other nutrients. These identified QTLs may facilitate the use of wild alleles for improving grain nutritional quality of elite wheat cultivars, especially in terms of protein, Zn and Fe

Neuropeptidomics of the Supraoptic Rat Nucleus

The mammalian supraoptic nucleus (SON) is a neuroendocrine center in the brain regulating a variety of physiological functions. Within the SON, peptidergic magnocellular neurons that project to the neurohypophysis (posterior pituitary) are involved in controlling osmotic balance, lactation, and parturition, partly through secretion of signaling peptides such as oxytocin and vasopressin into the blood. An improved understanding of SON activity and function requires identification and characteriza-tion of the peptides used by the SON. Here, small-volume sample preparation approaches are optimized for neuropeptidomic studies of isolated SON samples ranging from entire nuclei down to single magnocellular neurons. Unlike most previous mammalian peptidome studies, tissues are not im-mediately heated or microwaved. SON samples are obtained from ex vivo brain slice preparations via tissue punch and the samples processed through sequential steps of peptide extraction. Analyses of the samples via liquid chromatography mass spectrometry and tandem mass spectrometry result in the identification of 85 peptides, including 20 unique peptides from known prohormones. As the sample size is further reduced, the depth of peptide coverage decreases; however, even from individually isolated magnocellular neuroendocrine cells, vasopressin and several other peptides are detected

Genetic Insight into Yield-Associated Traits of Wheat Grown in Multiple Rain-Fed Environments

Background: Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL) directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14. Methodology/Principal Findings: Ten yield-associated traits, including yield per plant (YP), number of spikes per plan

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

© The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/ genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.Peer reviewedFinal Published versio

Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Increasing grain yield potential in wheat has been a major target of most breeding programs. Genetic advance has been frequently hindered by negative correlations among yield components that have been often observed in segregant populations and germplasm collections. A tetraploid wheat collection was evaluated in seven environments and genotyped with a 90K SNP assay to identify major and stable quantitative trait loci (QTL) for grain yield per spike (GYS), kernel number per spike (KNS) and thousand-kernel weight (TKW), and to analyse the genetic relationships between the yield components at QTL level. The genome-wide association analysis detected eight, eleven and ten QTL for KNS, TKW and GYS, respectively, significant in at least three environments or two environments and the mean across environments. Most of the QTL for TKW and KNS were found located in different marker intervals, indicating that they are genetically controlled independently by each other. Out of eight KNS QTL, three were associated to significant increases of GYS, while the increased grain number of five additional QTL was completely or partially compensated by decreases in grain weight, thus producing no or reduced effects on GYS. Similarly, four consistent and five suggestive TKW QTL resulted in visible increase of GYS, while seven additional QTL were associated to reduced effects in grain number and no effects on GYS. Our results showed that QTL analysis for detecting TKW or KNS alleles useful for improving grain yield potential should consider the pleiotropic effects of the QTL or the association to other QTLs