Variation of Grain Yield, Grain Protein Content and Nitrogen Use Efficiency Components under Different Nitrogen Rates in Mediterranean Durum Wheat Genotypes

Nitrogen (N) is a crucial nutrient for plant growth and development. To optimize agricultural environments, N fertilizers represent a critical tool to regulate crop productivity. The improvement of nitrogen use efficiency (NUE) represents a promising tool that may enable cereal production to meet future food demand. Wheat reported contrasting behaviors in N utilization showing specific abilities depending on genotype. This study selected two landraces and two improved genotypes from Northern Africa to investigate grain yield (GY), grain protein content (GPC) and NUE. Plants were grown under three levels of N supply: 0, 75, 150 kg N ha−1 and for two consecutive years. Results reported a better NUE (0.40 kg.kg N−1) obtained under 150 kg N ha−1, while N utilization efficiency (NUtE) showed a 13% increase using 75 kg N ha−1 compared with 150 kg N ha−1. Under low nitrogen rate (0 N), crop N supply (CNS) and N uptake efficiency (NUpE) were shown as determinant factors for improved genotypes GY (R2 = 0.72), while NUtE represented the most determinant component for GPC in landraces (R2 = 0.92). Multivariate regression models explained the dependence in GPC on NUE, NUpE, and NUtE. In conclusion, our results recognize GPC and NUtE as suitable selection traits to identify durum wheat with higher NUE

Model-based expert system for design and simulation of APS coatings

International audienceThis article aims at presenting an expert system to assist the design and the simulation of 2-D shapes of alumina-titania (i.e., Al2O3-13 wt.% TiO2) Atmospherically Plasma Sprayed (APS) coatings. Indeed, the expert system derives from a spray deposition mathematic model resulting from experiments. The varied processing parameters were the geometric and the kinematics parameters, mainly, such as: the relative speed gun-substrate, the spray distance, the spray angle, the relative positioning powder injector-spray gun trajectory, the number of passes and the powder feed rate. The variations of the geometry and some of the structural parameters were analyzed relatively to the aforementioned varied parameters. Thus, a large set of spray pattern parameters was designed. This set considers mostly the spray pattern geometry. All the relationships between the processing parameters and the spray pattern parameters were hence grouped in a spray deposition model. The second step of this work consisted in optimizing the robotic (i.e., spray gun) trajectory using a robotic code, which permits a realistic simulation of the spray gun speed and its inertia. Using this simulation software, a trajectory file was built. In the third step of the work, an expert system was developed by combining the spray deposition model with the trajectory. The tasks of the expert system are: (1) to assist the user in designing the coatings by selecting the processing parameters and (2) to simulate the coating shapes by integrating the gun trajectory

Suspension Plasma-Sprayed Alumina Coating Structures: Operating Parameters Versus Coating Architecture

International audienceSuspension plasma spraying (SPS) is able to process sub-micrometric-sized feedstock particles and permits the deposition of layers thinner (from 5 to 50 lm) than those resulting from conventional atmospheric plasma spraying (APS). SPS consists in mechanically injecting within the plasma flow a liquid suspension of particles of average diameter varying between 0.02 and 1 lm, average values. Upon penetration within the DC plasma jet, two phenomena occur sequentially: droplet fragmentation and evaporation. Particles are then processed by the plasma flow prior their impact, spreading and solidification upon the surface to be covered. Depending upon the selection of operating parameters, among which plasma power parameters (operating mode, enthalpy, spray distance, etc.), suspension properties (particle size distribution, powder mass percentage, viscosity, etc.), and substrate characteristics (topology, temperature, etc.), different coating architectures can be manufactured, from dense to porous layers. Nevertheless, the coupling between the parameters controlling the coating microstructure and properties are not yet fully identified. The aim of this study is to further understand the influence of parameters controlling the manufacturing mechanisms of SPS alumina coatings, particularly the spray beads influence