Sweet pepper (Capsicum annuum L.) is an economically important vegetable crop. Wilt disease caused by Fusarium oxysporum f. sp. capsici is a specific pathogen that affects the pepper. Four isolates of F. oxysporum f. sp. capsici Fo3, Fo6, Fo7 and Fo8 were obtained from diseased pepper plants that were collected from different pepper fields in Baghdad. Fo6 isolate that has high pathogenicity to pepper seeds, Trichoderma harzianum (Th) was tested in vitro against F. oxysporum f. sp. capsici showed a high inhibition rate for the isolate Fo6, the concentration of chelated iron Fe-EDDHA 0.5% reduced the radial growth of Fo6 whi

This paper aims to validate a proposed finite element model to be adopted in predicting displacement and soil stresses of a piled-raft foundation. The proposed model adopts the solid element to simulate the raft, piles, and soil mass. An explicit integration scheme has been used to simulate nonlinear static aspects of the piled-raft foundation and to avoid the computational difficulties associated with the implicit finite element analysis.

The validation process is based on comparing the results of the proposed finite element model with those of a scaled-down experimental work achieved by other researchers. Centrifuge apparatus has been used in the experimental work to generate the required stresses to simulate t

The present investigation deals with experimental study of three-phase direct-contact heat exchanger, for water-Freon R11 system, where water is the continuous phase (liquid) and Freon R11 (liquid-gas) is the dispersed phase. The test section consisted of a cylindrical Perspex column with inner diameter 8cm and 1.2m long, in which, water was to be confined. Liquid Freon R11 drops were injected into the hot water filled column, through a special design of distributors at the bottom of the column. The liquid Freon R11 drops rose on their way up and evaporated into two-phase bubbles at atmospheric pressure. The study was devoted to express the effect of process variables such as c

This study was conducted in a lath house, Dept of Hort. and Landscape, College of Agricultural Engineering Sciences, Univ. During the 2021 growing season, Baghdad will investigate the influence of organic and Biological fertilizers on three Citrus rootstocks' growth and leaf mineral content. The first factor is the addition of liquid organic fertilizers Vit-Org (O) at three levels without addition (O0), soil addition at 10 ml.L-1 (O10) and soil addition at 20 ml.L-1 (O20). The second factor is the addition of nitrogen-fixing bacteria without addition (N1), add 30 ml.Transplant-1 of Azotobacter chroococcum (N2) and add 30 ml.Transplant-1 of Azospirillum brasilemse (N3). The third factor is three citrus rootstocks: sour orange (R1), R

In the current study, three types of algae namely Tetradesmus nygaardi (MZ801740), Scenedesmus quadricauda (MZ801741) and Coelastrella sp (MZ801742) were extracted by 95% ethanol and hexane against two types of gram positive and two types of gram negative bacteria by wells diffusion methods. Eleven concentrations from the extract of algae (2, 5, 10, 15, 20, 25, 30, 35, 40, 45 and 50 mg/ml) were utilized. It was noticed that ethanolic extraction was more effective than hexane in Scenedesmus quadricauda than the two other mentioned algal species against all pathogenic bacteria, Acintobacter baumanii (ATCC: 19606), Klebsiella pneumonia (ATCC: 13883) Enterococcus faecalis (ATCC: 29212) and Staphylococc

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.