Exploring the Mycovirus Sclerotinia sclerotiorum Hypovirulence-Associated DNA Virus 1 as a Biocontrol Agent of White Mold Caused by Sclerotinia sclerotiorum.

Sclerotinia sclerotiorum is a necrotrophic fungal pathogen causing white mold on many important economic crops. Recently, some mycoviruses such as S. sclerotiorum hypovirulence-associated DNA virus 1 (SsHADV-1) converted S. sclerotiorum into a beneficial symbiont that helps plants manage pathogens and other stresses. To explore the potential use of SsHADV-1 as a biocontrol agent in the United States and to test the efficacy of SsHADV-1-infected United States isolates in managing white mold and other crop diseases, SsHADV-1 was transferred from the Chinese strain DT-8 to United States isolates of S. sclerotiorum. SsHADV-1 is readily transmitted horizontally among United States isolates of S. sclerotiorum and consistently conferred hypovirulence to its host strains. Biopriming of dry bean seeds with hypovirulent S. sclerotiorum strains enhanced resistance to white mold, gray mold, and Rhizoctonia root rot. To investigate the underlying mechanisms, endophytic growth of hypovirulent S. sclerotiorum in dry beans was confirmed using PCR, and the expression of 12 plant defense-related genes were monitored before and after infection. The results indicated that the endophytic growth of SsHADV-1-infected strains in plants stimulated the expression of plant immunity pathway genes that assisted a rapid response from the plant to fungal infection. Finally, application of the seed biopriming technology with SsHADV-1-infected hypervirulent strain has promise for the biological control of several diseases of wheat, pea, and sunflower.

Suitable Methods of Inoculation and Quantification of Fusarium Root Rot in Lentil.

Lentil (Lens culinaris L. subsp. culinaris) is an important grain legume grown worldwide. As its popularity grows among consumers and more acres are produced, new root rot complexes have become more prevalent. This work sought to develop methods for studying root rot caused by Fusarium avenaceum in lentil using controlled environments. The objectives were to (i) find an effective and seed-safe sterilization technique, (ii) optimize the inoculation technique and lentil growing environment, and (iii) develop visual and automated disease scoring systems. Results showed the use of detergent and a low concentration (0.1%) of NaClO (the active ingredient in bleach) maintained germinability and effectively eliminated bacterial and fungal contamination on seeds. Other treatments, such as ethanol, reduced seed germination or failed to kill pathogenic fungi such as Fusarium spp. Placing inoculum at a moderate rate of 1 × 106 spores both directly on the seed and on top of the media covering the seed improved severity scores and reduced escapes compared with placement on top of the media only. Visual severity scoring systems and diagrammatic scales were developed for scoring the cotyledon region and roots. A computer vision algorithm was designed to improve the efficiency of scoring the cotyledon region and roots for disease severity using a simple RGB camera and lightbox. Visual and computer scores were best correlated when images were visually scored on a monitor, and multiple images were averaged. The scores generated from the computer vision algorithm had better correlations with visual scores for cotyledon rot (r = 0.92 and ß1 = 0.96) than root rot (r = 0.62 and ß1 = 0.67).

Phenotypic and Genetic Characterization of the Lentil Single Plant-Derived Core Collection for Resistance to Root Rot Caused by Fusarium avenaceum.

Lentil (Lens culinaris) is a pulse crop grown for its amino acid profile, moderate drought tolerance, and ability to fix nitrogen. As the global demand for lentils expands and new production regions emerge so too have the complement of diseases that reduce yield, including the root rot complex. Although the predominant causal pathogen varies based on growing region, Fusarium avenaceum is often found to be an important contributor to disease. This study screened part of the lentil single plant-derived core collection for resistance to F. avenaceum in a greenhouse. Plants were phenotyped for disease severity using three scoring scales and the differences in biomass traits due to pathogen presence were measured. Lentil accessions varied in disease severity and differences in biomass traits were found to be correlated with each visual severity estimate (r = -0.37 to -0.63, P < 0.001), however, heritability estimates were low to moderate among traits (H2 = 0.12 to 0.43). Results of a genome-wide association study (GWAS) using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing revealed 11 quantitative trait loci (QTL) across four chromosomes. Two pairs of QTL colocated for two traits and were found near putative orthologs that have been previously associated with plant disease resistance. The identification of lentil accessions that did not exhibit a difference in biomass traits may serve as parental material in breeding or in the development of biparental mapping populations to further validate and dissect the genetic control of resistance to root rot caused by F. avenaceum.

Identification of Root Rot Resistance QTLs in Pea Using Fusarium solani f. sp. pisi-Responsive Differentially Expressed Genes.

Pisum sativum (pea) yields in the United States have declined significantly over the last decades, predominantly due to susceptibility to root rot diseases. One of the main causal agents of root rot is the fungus Fusarium solani f. sp. pisi (Fsp), leading to yield losses ranging from 15 to 60%. Determining and subsequently incorporating the genetic basis for resistance in new cultivars offers one of the best solutions to control this pathogen; however, no green-seeded pea cultivars with complete resistance to Fsp have been identified. To date, only partial levels of resistance to Fsp has been identified among pea genotypes. SNPs mined from Fsp-responsive differentially expressed genes (DEGs) identified in a preceding study were utilized to identify QTLs associated with Fsp resistance using composite interval mapping in two recombinant inbred line (RIL) populations segregating for partial root rot resistance. A total of 769 DEGs with single nucleotide polymorphisms (SNPs) were identified, and the putative SNPs were evaluated for being polymorphic across four partially resistant and four susceptible P. sativum genotypes. The SNPs with validated polymorphisms were used to screen two RIL populations using two phenotypic criteria: root disease severity and plant height. One QTL, WB.Fsp-Ps 5.1 that mapped to chromosome 5 explained 14.8% of the variance with a confidence interval of 10.4 cM. The other four QTLs located on chromosomes 2, 3, and 5, explained 5.3-8.1% of the variance. The use of SNPs derived from Fsp-responsive DEGs for QTL mapping proved to be an efficient way to identify molecular markers associated with Fsp resistance in pea. These QTLs are potential candidates for marker-assisted selection and gene pyramiding to obtain high levels of partial resistance in pea cultivars to combat root rot caused by Fsp.

Consequences of underexplored variation in biodiversity indices used for land-use prioritization.

For biodiversity protection to play a persuasive role in land-use planning, conservationists must be able to offer objective systems for ranking which natural areas to protect or convert. Representing biodiversity in spatially explicit indices is challenging because it entails numerous judgments regarding what variables to measure, how to measure them, and how to combine them. Surprisingly few studies have explored this variation. Here, we explore how this variation affects which areas are selected for agricultural conversion by a land-use prioritization model designed to reduce the biodiversity losses associated with agricultural expansion in Zambia. We first explore the similarity between model recommendations generated by three recently published composite indices and a commonly used rarity-weighted species richness metric. We then explore four underlying sources of ecological and methodological variation within these and other approaches, including different terrestrial vertebrate taxonomic groups, different species-richness metrics, different mathematical methods for combining layers, and different spatial resolutions of inputs. The results generated using different biodiversity approaches show very low spatial agreement regarding which areas to convert to agriculture. There is little overlap in areas identified for conversion using previously published indices (mean Jaccard similarity, Jw , between 0.3 and 3.7%), different taxonomic groups (5.0% < mean Jw  < 13.5%), or different measures of species richness (15.6% < mean Jw  < 33.7%). Even with shared conservation goals, different methods for combining layers and different input spatial resolutions still produce meaningful, though smaller, differences among areas selected for conversion (40.9% < mean Jw  < 67.5%). The choice of taxonomic group had the largest effect on conservation priorities, followed by the choice of species richness metric, the choice of combination method, and finally the choice of spatial resolution. These disagreements highlight the challenge of objectively representing biodiversity in land-use planning tools, and present a credibility challenge for conservation scientists seeking to inform policy making. Our results suggest an urgent need for a more consistent and transparent framework for designing the biodiversity indices used in land-use planning, which we propose here.

Hypoperfusion Intensity Ratio Correlates with CTA Collateral Status in Large-Vessel Occlusion Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Collateral blood supply is a key determinant of outcome in large-vessel occlusion acute ischemic stroke. Single- and multiphase CTA collateral scoring systems have been described but are subjective and require training. We aimed to test whether the CTP-derived hypoperfusion intensity ratio is associated with CTA collateral status and whether a threshold hypoperfusion intensity ratio exists that predicts poor CTA collaterals. MATERIALS AND METHODS: Imaging and clinical data of consecutive patients with large-vessel occlusion acute ischemic stroke were retrospectively reviewed. Single-phase CTA and multiphase CTA scoring were performed by 2 blinded neuroradiologists using the Tan, Maas, and Calgary/Menon methods. CTP was processed using RApid processing of PerfusIon and Diffusion software (RAPID). Hypoperfusion intensity ratio = ratio of brain volume with time-to-maximum >10 seconds over time-to-maximum >6-second volume. Correlation between the hypoperfusion intensity ratio and CTA collateral scores was calculated using the Pearson correlation. The optimal threshold of the hypoperfusion intensity ratio for predicting poor collaterals was determined using receiver operating characteristic curve analysis. RESULTS: Fifty-two patients with large-vessel occlusion acute ischemic stroke were included. Multiphase CTA collateral scoring showed better interrater agreement (κ = 0.813) than single-phase CTA (Tan, κ = 0.587; Maas, κ = 0.273). The hypoperfusion intensity ratio correlated with CTA collateral scores (multiphase CTA: r = -0.55; 95% CI, -0.67 to -0.40; P ≤ .001). The optimal threshold for predicting poor multiphase CTA collateral status was a hypoperfusion intensity ratio of >0.45 (sensitivity = 78%; specificity = 76%; area under the curve = 0.86). Patients with high hypoperfusion intensity ratio/poor collateral status had lower ASPECTS/larger infarcts, higher NIHSS scores, and larger hypoperfused volumes. CONCLUSIONS: The hypoperfusion intensity ratio is associated with CTA collateral status in patients with large-vessel occlusion acute ischemic stroke. The hypoperfusion intensity ratio is an automated and quantitative alternative to CTA collateral scoring methods for both clinical and future stroke trial settings.

KASP Markers Reveal Established and Novel Sources of Resistance to Pea Seedborne Mosaic Virus in Pea Genetic Resources.

Pea seed-borne mosaic virus (PSbMV) is both seedborne and aphid-transmitted and can cause economic losses for pea (Pisum sativum L.) production by reducing yield through decreased seed weight and number. The P1 pathotype is especially virulent, affecting this important vegetable crop across the United States and internationally in regions of West Asia, North Africa, Europe, and Australia. Previously, two kompetitive allele-specific PCR (KASP) genotyping markers (eIF4E resistant 1 and 2) were developed and validated on P. sativum accessions identifying two PSbMV pathotype P1 resistance alleles in the eukaryotic translation initiation factor gene, eIF4E. The current study utilized these novel markers to rapidly evaluate 318 genetic resource accessions maintained as part of the United States Department of Agriculture National Plant Germplasm System's Pea Single Plant Collection (PSPC). The evaluations also included 58 commercial and other plant introduction (PI) lines that were assessed for the two eIF4E resistance alleles. All genotyping results were validated in greenhouse assays by confirmation of observable disease symptoms after inoculations and by enzyme-linked immunosorbent assays. The eIF4E resistant 1 and 2 alleles were found in 18 accessions from the PSPC, five commercial lines, and 14 other PI accessions. A single PSPC accession showed resistance to PSbMV pathotype P1 that is believed to be a novel source of resistance based on sequencing analysis of eIF4E. Sources of resistance were identified in the PSPC and in commercial cultivars that can be introgressed into breeding lines using traditional techniques to reduce the time and cost required to generate germplasm with superior disease-resistant traits.

High Resolution, Annual Maps of Field Boundaries for Smallholder-Dominated Croplands at National Scales.

Mapping the characteristics of Africa's smallholder-dominated croplands, including the sizes and numbers of fields, can provide critical insights into food security and a range of other socioeconomic and environmental concerns. However, accurately mapping these systems is difficult because there is 1) a spatial and temporal mismatch between satellite sensors and smallholder fields, and 2) a lack of high-quality labels needed to train and assess machine learning classifiers. We developed an approach designed to address these two problems, and used it to map Ghana's croplands. To overcome the spatio-temporal mismatch, we converted daily, high resolution imagery into two cloud-free composites (the primary growing season and subsequent dry season) covering the 2018 agricultural year, providing a seasonal contrast that helps to improve classification accuracy. To address the problem of label availability, we created a platform that rigorously assesses and minimizes label error, and used it to iteratively train a Random Forests classifier with active learning, which identifies the most informative training sample based on prediction uncertainty. Minimizing label errors improved model F1 scores by up to 25%. Active learning increased F1 scores by an average of 9.1% between first and last training iterations, and 2.3% more than models trained with randomly selected labels. We used the resulting 3.7 m map of cropland probabilities within a segmentation algorithm to delineate crop field boundaries. Using an independent map reference sample (n = 1,207), we found that the cropland probability and field boundary maps had respective overall accuracies of 88 and 86.7%, user's accuracies for the cropland class of 61.2 and 78.9%, and producer's accuracies of 67.3 and 58.2%. An unbiased area estimate calculated from the map reference sample indicates that cropland covers 17.1% (15.4-18.9%) of Ghana. Using the most accurate validation labels to correct for biases in the segmented field boundaries map, we estimated that the average size and total number of field in Ghana are 1.73 ha and 1,662,281, respectively. Our results demonstrate an adaptable and transferable approach for developing annual, country-scale maps of crop field boundaries, with several features that effectively mitigate the errors inherent in remote sensing of smallholder-dominated agriculture.

The effects of sub-bandgap transitions and the defect density of states on the photocurrent response of a single ZnO-coated silica nanospring.

The electrical and optoelectronic properties of nanometer-sized ZnO structures are highly influenced by its native point defects. Understanding and controlling these defects are essential for the development of high-performance ZnO-based devices. Here, an electrical device consisting of a polycrystalline ZnO-coated silica nanospring was fabricated and used to characterize the electrical and photoconductive properties of the ZnO layer using near-UV (405 nm) and sub-bandgap (532 and 633 nm) excitation sources. We observe a photocurrent response with all three wavelengths and notably with 532 nm green illumination, which is the energy associated with deep oxygen vacancies. The polycrystalline ZnO-coated silica nanospring exhibits a high responsivity of 1740 A W-1 with the 405 nm excitation source. Physical models are presented to describe the photocurrent rise and decay behavior of each excitation source where we suggest that the rise and decay characteristics are highly dependent on the energy of the excitation source and the trapping of electrons and holes in intermediate defect levels in the bandgap. The energy levels of the trap depths were determined from the photoconductive decay data and are matched to the reported energy levels of singly and doubly ionized oxygen vacancies. A phenomenological model to describe the dependence of the saturation photocurrent on excitation intensity is presented in order to understand the characteristics of the observed breaks in the slopes of the saturation photocurrent versus excitation intensity profile.

MRI-visible perivascular spaces as an imaging biomarker in Fabry disease.

INTRODUCTION: Fabry disease (FD) is an X-linked lysosomal storage disorder resulting in vascular glycosphingolipid accumulation and increased stroke risk. MRI findings associated with FD include white matter hyperintensities (WMH) and cerebral microbleeds (CMBs), suggesting the presence of cerebral small vessel disease. MRI-visible perivascular spaces (PVS) are another promising marker of small vessel disease associated with impaired interstitial fluid drainage. We investigated the association of PVS severity and anatomical distribution with FD. PATIENTS AND METHODS: We compared patients with genetically proven FD to healthy controls. PVS, WMH, lacunes and CMBs were rated on standardised sequences using validated criteria and scales, blinded to diagnosis. A trained observer (using a validated rating scale), quantified the total severity of PVS. We used logistic regression to investigate the association of severe PVS with FD. RESULTS: We included 33 FD patients (median age 44, 44.1% male) and 20 healthy controls (median age 33.5, 50% male). Adjusting for age and sex, FD was associated with more severe basal ganglia PVS (odds ratio (OR) 5.80, 95% CI 1.03-32.7) and higher total PVS score (OR 4.03, 95% CI 1.36-11.89). Compared with controls, participants with FD had: higher WMH volume (median 495.03 mm3 vs 0, p = 0.0008), more CMBs (21.21% vs none, p = 0.04), and a higher prevalence of lacunes (21.21% vs. 5%, p = 0.23). CONCLUSIONS: PVS scores are more severe in FD than control subjects. Our findings have potential relevance for FD diagnosis and suggest that impaired interstitial fluid drainage might be a mechanism of white matter injury in FD.

Analysis and Identification of QTL for Resistance to Sclerotinia sclerotiorum in Pea (Pisum sativum L.).

White mold caused by Sclerotinia sclerotiorum is an important constraint to field pea (Pisum sativum L.) production worldwide. To transfer white mold resistance into an adapted background, and study the genetics of the disease, two recombinant inbred line (RIL) populations (PRIL17 and PRIL19) were developed by crossing two partially resistant plant introductions with two susceptible pea cultivars. PRIL17 (Lifter × PI240515), and PRIL19 (PI169603 × Medora) were evaluated for resistance to white mold by measuring lesion expansion inhibition (LEI) and nodal transmission inhibition (NTI) at 3, 7, and 14 days post inoculation (dpi) under controlled environmental conditions. Lesion expansion inhibition percentage (LEIP), survival rate (SR), and area under disease progress curves (AUDPC) were also calculated accordingly. Because of a positive correlation between LEI and NTI with height, short and long internode individuals of each population were analyzed separately to avoid any confounding effect of height to pathogen response. A total of 22 short genotypes demonstrated partial resistance based on at least two Porter's resistance criteria. Only two pea genotypes with partial resistance to white mold (PRIL19-18 and PRIL19-124) had both semi-leafless (afila) and short internode traits. Both the RIL populations were genotyped using genotyping by sequencing (GBS). For PRIL17 and PRIL19, genetic maps were constructed from a total of 1,967 and 1,196 single nucleotide polymorphism (SNP) and spanned over 1,494 cM and 1,415 cM representing seven and nine linkage groups, respectively. A consensus map constructed using data from both populations, had 1,486 unique SNPs over 2,461 cM belonging to seven linkage groups. Inclusive composite interval mapping (ICIM) identified thirteen quantitative trait loci (QTL) associated with white mold resistance traits in both populations. Three of them were co-located with height genes (a morphological trait that reduces infection risk and acts as disease avoidance) and the other ten QTL were associated with two forms of physiological resistance (seven for LEI and three for NTI) with LOD and r2 ranging from 3.0 to 28.5 and 5.1 to 64.3, respectively. The development of resistance lines, genetic dissection and identification of markers associated will help accelerate breeding efforts for white mold resistance using molecular breeding approaches.

Identification of Fusarium solani f. sp. pisi (Fsp) Responsive Genes in Pisum sativum.

Pisum sativum (pea) is rapidly emerging as an inexpensive and significant contributor to the plant-derived protein market. Due to its nitrogen-fixation capability, short life cycle, and low water usage, pea is a useful cover-and-break crop that requires minimal external inputs. It is critical for sustainable agriculture and indispensable for future food security. Root rot in pea, caused by the fungal pathogen Fusarium solani f. sp. pisi (Fsp), can result in a 15-60% reduction in yield. It is urgent to understand the molecular basis of Fsp interaction in pea to develop root rot tolerant cultivars. A complementary genetics and gene expression approach was undertaken in this study to identify Fsp-responsive genes in four tolerant and four susceptible pea genotypes. Time course RNAseq was performed on both sets of genotypes after the Fsp challenge. Analysis of the transcriptome data resulted in the identification of 42,905 differentially expressed contigs (DECs). Interestingly, the vast majority of DECs were overexpressed in the susceptible genotypes at all sampling time points, rather than in the tolerant genotypes. Gene expression and GO enrichment analyses revealed genes coding for receptor-mediated endocytosis, sugar transporters, salicylic acid synthesis, and signaling, and cell death were overexpressed in the susceptible genotypes. In the tolerant genotypes, genes involved in exocytosis, and secretion by cell, the anthocyanin synthesis pathway, as well as the DRR230 gene, a pathogenesis-related (PR) gene, were overexpressed. The complementary genetic and RNAseq approach has yielded a set of potential genes that could be targeted for improved tolerance against root rot in P. sativum. Fsp challenge produced a futile transcriptomic response in the susceptible genotypes. This type of response is hypothesized to be related to the speed at which the pathogen infestation advances in the susceptible genotypes and the preexisting level of disease-preparedness in the tolerant genotypes.

Development and Validation of KASP Markers for the Identification of Pea seedborne mosaic virus Pathotype P1 Resistance in Pisum sativum.

As pesticides have become heavily relied on for management of insect pests vectoring economically important pathogens of vegetable crops, development of pathogen-resistant germplasm remains a promising alternative to reduce or eliminate costly and timely chemical inputs. Molecular markers can be used to rapidly identify resistant genotypes to aid breeders in advancing germplasm. This study developed two kompetitive allele-specific PCR (KASP) genotyping markers for rapid screening of Pisum sativum genotypes for resistance to Pea seedborne mosaic virus pathotype P1 (PSbMV-P1), the most economically devastating strain worldwide. The KASP markers differentiate two eIF4E PSbMV-P1-resistant allelic variants from susceptible eIF4E variants. A single nucleotide polymorphism (Resistant 1) and a 3-basepair deletion (Resistant 2) present in either of the two resistant alleles were used for marker design. Forty-four P. sativum lines previously characterized for resistance to PSbMV were inoculated with PSbMV-P1 in a greenhouse, observed for visual symptoms, assayed for virus susceptibility by enzyme-linked immunosorbent assay (ELISA), and genotyped by KASP marker analysis. The KASP markers were 100% accurate in characterizing PSbMV-P1-susceptible and PSbMV-P1-resistant genotypes when correlated with the ELISA results. The Resistant 1 marker also correlated with resistance to PSbMV pathotypes P2 and P4 completely, making this marker a new advanced tool for P. sativum breeding programs.

Dissecting the Genetic Architecture of Aphanomyces Root Rot Resistance in Lentil by QTL Mapping and Genome-Wide Association Study.

Lentil (Lens culinaris Medikus) is an important source of protein for people in developing countries. Aphanomyces root rot (ARR) has emerged as one of the most devastating diseases affecting lentil production. In this study, we applied two complementary quantitative trait loci (QTL) analysis approaches to unravel the genetic architecture underlying this complex trait. A recombinant inbred line (RIL) population and an association mapping population were genotyped using genotyping by sequencing (GBS) to discover novel single nucleotide polymorphisms (SNPs). QTL mapping identified 19 QTL associated with ARR resistance, while association mapping detected 38 QTL and highlighted accumulation of favorable haplotypes in most of the resistant accessions. Seven QTL clusters were discovered on six chromosomes, and 15 putative genes were identified within the QTL clusters. To validate QTL mapping and genome-wide association study (GWAS) results, expression analysis of five selected genes was conducted on partially resistant and susceptible accessions. Three of the genes were differentially expressed at early stages of infection, two of which may be associated with ARR resistance. Our findings provide valuable insight into the genetic control of ARR, and genetic and genomic resources developed here can be used to accelerate development of lentil cultivars with high levels of partial resistance to ARR.

Protein, weight, and oil prediction by single-seed near-infrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum).

BACKGROUND: Pea (Pisum sativum) is a prevalent cool-season crop that produces seeds valued for their high protein content. Modern cultivars have incorporated several traits that improved harvested yield. However, progress toward improving seed quality has received less emphasis, in part due to the lack of tools for easily and rapidly measuring seed traits. In this study we evaluated the accuracy of single-seed near-infrared spectroscopy (NIRS) for measuring pea-seed weight, protein, and oil content. A total of 96 diverse pea accessions were analyzed using both single-seed NIRS and wet chemistry methods. To demonstrate field relevance, the single-seed NIRS protein prediction model was used to determine the impact of seed treatments and foliar fungicides on the protein content of harvested dry peas in a field trial. RESULTS: External validation of partial least squares (PLS) regression models showed high prediction accuracy for protein and weight (R2 = 0.94 for both) and less accuracy for oil (R2 = 0.74). Single-seed weight was weakly correlated with protein and oil content in contrast with previous reports. In the field study, the single-seed NIRS predicted protein values were within 10 mg g-1 of an independent analytical reference measurement and were sufficiently precise to detect small treatment effects. CONCLUSION: The high accuracy of protein and weight estimation show that single-seed NIRS could be used in the dual selection of high-protein, high-weight peas early in the breeding cycle, allowing for faster genetic advancement toward improved pea nutritional quality. © 2020 Society of Chemical Industry.

ZnO Microfiltration Membranes for Desalination by a Vacuum Flow-Through Evaporation Method.

ZnO was deposited on macroporous α-alumina membranes via atomic layer deposition (ALD) to improve water flux by increasing their hydrophilicity and reducing mass transfer resistance through membrane pore channels. The deposition of ZnO was systemically performed for 4-128 cycles of ALD at 170 °C. Analysis of membrane surface by contact angles (CA) measurements revealed that the hydrophilicity of the ZnO ALD membrane was enhanced with increasing the number of ALD cycles. It was observed that a vacuum-assisted 'flow-through' evaporation method had significantly higher efficacy in comparison to conventional desalination methods. By using the vacuum-assisted 'flow-through' technique, the water flux of the ZnO ALD membrane (~170 L m-2 h-1) was obtained, which is higher than uncoated pristine membranes (92 L m-2 h-1). It was also found that ZnO ALD membranes substantially improved water flux while keeping excellent salt rejection rate (>99.9%). Ultrasonic membrane cleaning had considerable effect on reducing the membrane fouling.

Luminescent properties of a 3,5-diphenylpyrazole bridged Pt(ii) dimer.

We report the synthesis, electrochemistry, photophysical properties and electroluminescence of a highly luminescent pyrazolate-bridged platinum(ii) complex. The complex has the general formula of [((N^C^N)Pt)2(µ-pz)][PF6] where N^C^N = 1,3-di(2-pyridyl)benzene and µ-pz = 3,5-diphenylpyrazolate. The X-ray structure shows that the bridging pyrazolate ligand causes a close Pt-Pt interaction of 3.05(7) Å. The emission profile of the complex was determined in solution, glassy 2-methyltetrahydrofurane at 77 K, and the solid state at both room temperature and 77 K. Each emission profile displayed a strong red metal-metal-to-ligand charge transfer while the solution and glassy 2-methyltetrahydrofurane emission profiles also displayed a ligand-centred transition. The absolute quantum yields of the complex in solution and the solid state at room temperate are 86% and 39%, respectively. Light-emitting electrochemical cells (LEECs) of [((N^C^N)Pt)2(µ-pz)][PF6] were fabricated which displayed appreciable electroluminescence, among the brightest and most efficient LEECs from dinuclear compounds to date.

Confirmation of Fusarium root rot resistance QTL Fsp-Ps 2.1 of pea under controlled conditions.

BACKGROUND: Dry pea production has increased substantially in North America over the last few decades. With this expansion, significant yield losses have been attributed to an escalation in Fusarium root rots in pea fields. Among the most significant rot rotting pathogenic fungal species, Fusarium solani fsp. pisi (Fsp) is one of the main causal agents of root rot of pea. High levels of partial resistance to Fsp has been identified in plant genetic resources. Genetic resistance offers one of the best solutions to control this root rotting fungus. A recombinant inbred population segregating for high levels of partial resistance, previously single nucleotide polymorphism (SNP) genotyped using genotyping-by-sequencing, was phenotyped for disease reaction in replicated and repeated greenhouse trials. Composite interval mapping was deployed to identify resistance-associated quantitative trait loci (QTL). RESULTS: Three QTL were identified using three disease reaction criteria: root disease severity, ratios of diseased vs. healthy shoot heights and dry plant weights under controlled conditions using pure cultures of Fusarium solani fsp. pisi. One QTL Fsp-Ps 2.1 explains 44.4-53.4% of the variance with a narrow confidence interval of 1.2 cM. The second and third QTL Fsp-Ps3.2 and Fsp-Ps3.3 are closely linked and explain only 3.6-4.6% of the variance. All of the alleles are contributed by the resistant parent PI 180693. CONCLUSION: With the confirmation of Fsp-Ps 2.1 now in two RIL populations, SNPs associated with this region make a good target for marker-assisted selection in pea breeding programs to obtain high levels of partial resistance to Fusarium root rot caused by Fusarium solani fsp. pisi.

Electrical characterization of ZnO-coated nanospring ensemble by impedance spectroscopy: probing the effect of thermal annealing.

The effects of thermal annealing on the electrical properties of randomly oriented ZnO-coated nanospring ensembles were extensively investigated through AC impedance spectroscopy. Annealing the nanospring mats for an hour at 873 K in air showed significant change in ZnO morphology, reduced electrical conductivity due to the presence of grain boundaries, decreased apparent donor concentration, and faster decay of sub-band gap photocurrent. The role of the nanospring-nanospring junctions in the conduction of carriers in the ensemble was also examined, as well as evaluation of their responsiveness to thermal and optical stimulations. This work identifies the effects of heat treatment in the presence of air on the electrical properties of the nanospring ensembles, which are related to the mesoscopic morphology and interconnect within the ensemble and the properties of the ZnO coating.

The Effect of UV Illumination on the Room Temperature Detection of Vaporized Ammonium Nitrate by a ZnO Coated Nanospring-Based Sensor.

The effect of UV illumination on the room temperature electrical detection of ammonium nitrate vapor was examined. The sensor consists of a self-assembled ensemble of silica nanosprings coated with zinc oxide. UV illumination mitigates the baseline drift of the resistance relative to operation under dark conditions. It also lowers the baseline resistance of the sensor by 25% compared to dark conditions. At high ammonium nitrate concentrations (120 ppm), the recovery time after exposure is virtually identical with or without UV illumination. At low ammonium nitrate concentrations (20 ppm), UV illumination assists with refreshing of the sensor by stimulating analyte desorption, thereby enabling the sensor to return to its baseline resistance. Under dark conditions and low ammonium nitrate concentrations, residual analyte builds up with each exposure, which inhibits the sensor from returning to its original baseline resistance and subsequently impedes sensing due to permanent occupation of absorption sites.