Leptosphaeria maculans-Brassica napus Battle: A Comparison of Incompatible vs. Compatible Interactions Using Dual RNASeq

Leptosphaeria maculans causes blackleg disease, which is one of the most destructive diseases of canola (Brassica napus L.). Due to the erosion of the current resistance in B. napus, it is pivotal to introduce new resistant genotypes to the growers. This study evaluated the potential of Rlm7 gene as resistance to its corresponding avirulence AvrLm7 gene is abundant. The Rlm7 line was inoculated with L. maculans isolate with AvrLm7; UMAvr7; and the CRISPR/Cas9 knockout AvrLm7 mutant, umavr7, of the same isolate to cause incompatible and compatible interactions, respectively. Dual RNA-seq showed differential gene expressions in both interactions. High expressions of virulence-related pathogen genes-CAZymes, merops, and effector proteins after 7-dpi in compatible interactions but not in incompatible interaction—confirmed that the pathogen was actively virulent only in compatible interactions. Salicyclic and jasmonic acid biosynthesis and signaling-related genes, defense-related PR1 gene (GSBRNA2T00150001001), and GSBRNA2T00068522001 in the NLR gene family were upregulated starting as early as 1- and 3-dpi in the incompatible interaction and the high upregulation of those genes after 7-dpi in compatible interactions confirmed the early recognition of the pathogen by the host and control it by early activation of host defense mechanisms in the incompatible interaction.     

Land use regression model for ultrafine particles in Amsterdam

There are currently no epidemiological studies on health effects of long-term exposure to ultrafine particles (UFP), largely because data on spatial exposure contrasts for UFP is lacking. The objective of this study was to develop a land use regression (LUR) model for UFP in the city of Amsterdam. Total particle number concentrations (PNC), PM10, PM2.5, and its soot content were measured directly outside 50 homes spread over the city of Amsterdam. Each home was measured during one week. Continuous measurements at a central urban background site were used to adjust the average concentration for temporal variation. Predictor variables (traffic, address density, land use) were obtained using geographic information systems. A model including the product of traffic intensity and the inverse distance to the nearest road squared, address density, and location near the port explained 67% of the variability in measured PNC. LUR models for PM2.5, soot, and coarse particles (PM10, PM2.5) explained 57%, 76%, and 37% of the variability in measured concentrations. Predictions from the PNC model correlated highly with predictions from LUR models for PM2.5, soot, and coarse particles. A LUR model for PNC has been developed, with similar validity as previous models for more commonly measured pollutants.     

Organic solvent pretreatment to enhance enzymic saccharification of straw

Enzymic saccharification of wheat straw in the absence of any pretreatment was only about 20 %. Acid hydrolysis did not improve the overall cellulose enzymic breakdown, nor did pretreatment by flash autohydrolysis under pressure or sodium chlorite delignification. When wheat straw was treated with N-methyl-morpholine-N-oxide (MMNO) at J20°C for 20–30 min, this treatment and subsequent enzymic hydrolysis produced carbohydrate conversion of 73%. Similar results could be obtained by treating straw with 0·1 M sodium hydroxide. When MMNO treatment was combined with any other pretreatment, the saccharification yield was greatly enhanced. Nearly quantitative conversion was obtained by swelling straw in 0·1 M sodium hydroxide followed by MMNO treatment. The results show that lignin content of plant material does not represent the limiting factor to enzymic saccharification.     

Evolution of the localisation and composition of phenolics in grape skin between veraison and maturity in relation to water availability and some climatic conditions

BACKGROUND: Several studies have investigated the composition of phenolics in grape skin during grape maturation under various conditions of light exposure, water stress, nitrogen supply and mineral nutrition, but their localisation during berry development is not well known. In this study the composition and localisation of proanthocyanidins were monitored for three years on four plots known to induce a distinctive behaviour of the vine (Cabernet Franc). The composition of phenolics was determined by spectrophotometry; also, in one year, proanthocyanidins were determined by high‐performance liquid chromatography. Further information was obtained histochemically by means of toluidine blue O staining and image analysis. RESULTS: The results indicated that clear differences in phenolic quantification existed between the biochemical and histochemical approaches; the proportion of cells without phenolics was not linked with the quantity determined by the analytical methods used. The histochemical method showed the evolution of the localisation and typology of cells with and without phenolics during ripening. The number of cells without any phenolic compounds appeared to be very dependent on the mesoclimatic conditions and only slightly dependent on the site water status. CONCLUSION: Clear differences in phenolic quantification existed between the biochemical and histochemical approaches; the proportion of cells with phenolics was not linked with the quantity determined by biochemistry. The histochemical method showed an evolution of the localisation and typology of cells with and without phenolics in which mesoclimatic conditions were the most influential factor. Finally, the study showed some advantages of the histochemical approach: it gives information about the anatomy of the tissue as well as the nature and distribution of some of the large macromolecules and allows reconstruction of the three‐dimensional plant structure. Copyright © 2011 Society of Chemical Industry     

Guiding collaborative revision of science explanations

International Journal of Computer-Supported Collaborative Learning - This paper illustrates how the combination of teacher and computer guidance can strengthen collaborative revision and identifies...     

Farm-scale bio-power-to-methane: Comparative analyses of economic and environmental feasibility

Power-to-gas technologies are considered to be part of the future energy system, but their viability and applicability need to be assessed. Therefore, models for the viability of farm-scale bio-power-to-methane supply chains to produce green gas were analysed in terms of levelised cost of energy, energy efficiency and saving of greenhouse gas emission. In bio-power-to-methane, hydrogen from electrolysis driven by surplus renewable electricity and carbon dioxide from biogas are converted to methane by microbes in an ex situ trickle-bed reactor. Such bio-methanation could replace the current upgrading of biogas to green gas with membrane technology. Four scenarios were compared: a reference scenario without bio-methanation (A), bio-methanation (B), bio-methanation combined with membrane upgrading (C) and the latter with use of renewable energy only (all-green; D). The reference scenario (A) has the lowest costs for green gas production, but the bio-methanation scenarios (B-D) have higher energy efficiencies and environmental benefits. The higher costs of the bio-methanation scenarios are largely due to electrolysis, whereas the environmental benefits are due to the use of renewable electricity. Only the all-green scenario (D) meets the 2026 EU goal of 80% reduction of greenhouse gas emissions, but it would require a CO₂ price of 200 € t⁻¹ to achieve the levelised cost of energy of 65 €ct Nm⁻³ of the reference scenario. Inclusion of the intermittency of renewable energy in the scenarios substantially increases the costs. Further greening of the bio-methanation supply chain and how intermittency is best taken into account need further investigation.     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.     

Airfoil optimisation for vertical‐axis wind turbines with variable pitch

To advance the design of a multimegawatt vertical‐axis wind turbine (VAWT), application‐specific airfoils need to be developed. In this research, airfoils are tailored for a VAWT with variable pitch. A genetic algorithm is used to optimise the airfoil shape considering a balance between the aerodynamic and structural performance of airfoils. At rotor scale, the aerodynamic objective aims to create the required optimal loading while minimising losses. The structural objective focusses on maximising the bending stiffness. Three airfoils from the Pareto front are selected and analysed using the actuator cylinder model and a prescribed‐wake vortex code. The optimal pitch schedule is determined, and the loadings and power performance are studied for different tip‐speed ratios and solidities. The comparison of the optimised airfoils with similar airfoils from the first generation shows a significant improvement in performance, and this proves the necessity to properly select the airfoil shape.     

Application of principal component analysis to the prediction of lucerne forage protein content and in vitro dry matter digestibility by NIR spectroscopy

Application of principal component regression (PCR) was proposed for the development of a prediction equation of forage composition by near infra-red spectroscopy. PCR involves two steps: (a) the creation of new synthetic variables by principal component analysis (PCA) of spectral data, and (b) multiple linear regression with these new variables. Results obtained by this procedure have been compared with those generated by the conventional application of multiple linear regression (MLR) on spectral data. The comparison used the determination of protein content and in vitro dry matter digestibility (IVDMD) in 345 samples of lucerne forages. For protein determination, results of both procedures were quite similar (correlation coefficients: 0.978 and 0.980; standard errors of calibration: 0.86 and 0.84% DM; standard errors of prediction: 0.81 and 0.80% DM respectively for MLR and PCR prediction equations). The same was observed for IVDMD determination (correlation coefficients: 0.942 and 0.951; standard errors of calibration: 1.89 and 1.71% DM; standard errors of prediction: 2.22 and 2.22% DM, respectively). A large number of PCA variables were necessary for an accurate prediction of both constituents. The influence of the number of regression terms introduced in the PCR equation has been studied. The criterion for stopping the introduction of new terms in PCR did not seem as critical as in MLR.     

Differentiation of apple juice samples on the basis of heat treatment and variety using chemometric analysis of MIR and NIR data

The potential of mid-infrared (MIR) and near-infrared (NIR) spectroscopy for their ability to differentiate between apple juice samples on the basis of apple variety and applied heat-treatment was evaluated. The heat-treatment involved exposure of juice samples (15 ml) for 30 s in a 900 W microwave oven and the apple varieties used to produce the juice samples were Bramley, Elstar, Golden Delicious and Jonagold. The chemometric procedures applied to the MIR and NIR data were partial least squares regression (PLS1 for differentiation on the basis of heat-treatment, PLS2 for varietal differentiation) and linear discriminant analysis (LDA) applied to principal component (PC) scores. PLS1 and PLS2 gave the highest level of correct classification of the apple juice samples according to heat-treatment (77.2% for both MIR and NIR data) and variety (78.3–100% for MIR data; 82.4–100% for NIR data), respectively.