The experiment was carried out to study the effect of variety and gibberellic acid in concentration (0 and 50)mg.lat-1 and BL in five concentration (0, 0.50 ,1 ,2 and 3)mg.ltr-1 and their interaction in some chemical Characteristics and total chlorophyll for Dill plant . the experiment designed according Randomized Complete Block Design (RCBD) and three replicates per treatment, compared to the average using less significant difference at the level of probability (0.05) , the results showed the following:- The effect of brassinolide with it,s concentrations led to obtain a significant increase in all the studied characteristics, so the superiority of the concentration of 2 mg.L-1 of brassinolide in each of Ca, Mg,Fe, and total chlorophyll T

To investigate the effect of spraying some plant extraction and anti-oxidants on growth and yield of two cultivars of sunflower, a field experiment was conducted during fall season of 2009 and spring season of 2010 at the Experimental Farm, Department of Field Crop Science, College of Agriculture/ University of Baghdad. RCBD with three replications as factorial at two factors was used. First factor was cultivars Akmar and Shmoss, second was spraying with extraction of karkade at 25%, liquorices at 50%, vitamin C at concentration 1.5 mg.l-1 and nutrient which content 15 elements at concentration 15 % in addition to control treatment which sprayed with distilled water only. The result showed no significant differences between the two cultivar

A plant mixture containing indigenous Australian plants was examined for synergistic antimicrobial activity using selected test microorganisms. This study aims to investigate antibacterial activities, antioxidant potential and the content of phenolic compounds in aqueous, ethanolic and peptide extracts of plant mixture.

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe

This paper investigates the performance evaluation of two state feedback controllers, Pole Placement (PP) and Linear Quadratic Regulator (LQR). The two controllers are designed for a Mass-Spring-Damper (MSD) system found in numerous applications to stabilize the MSD system performance and minimize the position tracking error of the system output. The state space model of the MSD system is first developed. Then, two meta-heuristic optimizations, Simulated Annealing (SA) optimization and Ant Colony (AC) optimization are utilized to optimize feedback gains matrix K of the PP and the weighting matrices Q and R of the LQR to make the MSD system reach stabilization and reduce the oscillation of the response. The Matlab softwar