rop simulation models play a pivotal role in evaluating irrigation management strategies to improve water use in agriculture. The aim of this study is to verify the validity of the Aquacrop model of maize under the surface and sprinkler irrigation systems, and a cultivation system, borders and furrows, and for two varieties of Maze (Fajr and Drakma) At two different sites in Iraq, Babylon and Al-Qadisiyah governorates. An experiment was conducted to evaluate the performance of the Aquacrop model in simulating canopy cover (CC), biomass (B), dry yield, harvest index (HI), and water productivity (WP). The results of RMSE, R2, MAE, d, NSE, CC, Pe indicated good results and high compatibility between measured and simulated values. The highest achieved results were identical to the method of sprinkler irrigation due to the decrease in the amount of water consumed and the furrows cultivation method as the aerial roots were covered and the cultivar was Drakma. The highest values for the statistical data were R2 (90 and 96%), RMSE (0.60, 0.73), MAE (0.5, 0.67), d (0.97, 0.97), NSE (0.87, 0.90), for Babylon and Al-Qadisiyah sites, respectively. As for the CC values, they were very compatible with the values of R2 and ranged between (92 - 99) %. The prediction error was Pe and minor errors were found. Thus, the Aquacrop model can be used reliably to evaluate the effectiveness of proposed irrigation management strategies for maize.
Carnitine is a regulatory amino acid, necessary for the metabolism of long-chain fatty acids in the ß - oxidation, and it is important in the organization of the work of the blood brain barrier, and is very important in the treatment of infertility and sexual apathy. This study was conducted at the Poultry Farm of the Department of Animal Resource, College of Agriculture, University of Baghdad during the period from 15/2/2011 to 1/8/2011. The aim of this study was to investigate the effect of dietary supplementation with different levels of L - carnitin e on semen characteristics of guinea fowl male. A total of 24 guinea fowl male, 30 weeks of old were used in this study. Birds were randomly distributed into 4 groups (C0, C100, C200, C300)
... Show MoreSorghum cultivation is often accompanied by low field emergence rates and weak seedlings, which may be due to genetic or environmental stress. A factorial experiment was conducted in the spring and fall seasons of 2022 using a randomized complete block design with split-plot arrangement and four replications. Planting dates (spring season: Feb. 15th, Mar. 1st, 15th, and Apr. 1st, 15th; fall season: Jun. 15th, Jul. 1st, 15th, and Aug. 1st, 15th) were allocated to the main plots. Seeds stimulation treatments (35% banana peel extract + 100 mg L-1 citric acid and distilled water soaking treatment only) were allocated to the subplots. The interaction treatment (banana peel extract + citric acid) with the planting date of April 15 showed the high
... Show MoreIn this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
In this paper, the computational method (CM) based on the standard polynomials has been implemented to solve some nonlinear differential equations arising in engineering and applied sciences. Moreover, novel computational methods have been developed in this study by orthogonal base functions, namely Hermite, Legendre, and Bernstein polynomials. The nonlinear problem is successfully converted into a nonlinear algebraic system of equations, which are then solved by Mathematica®12. The developed computational methods (D-CMs) have been applied to solve three applications involving well-known nonlinear problems: the Darcy-Brinkman-Forchheimer equation, the Blasius equation, and the Falkner-Skan equation, and a comparison between the met
... Show MoreIn this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
Abstract
Electrical magnate was designed and constructed, the optimum Magnetic flux and the effect of time on the physical properties of the alkaline (magnetic water) produced from the bottled drinking water [the total dissolved solids (TDS) or the electrical conductivity, and pH] were studied, to simulate ZamZam water in Mekka Saudi Arabia. Also, the efficiency of magnetic field from this designed electrical magnate in decreasing the TDS of sea water (of 1500 ppm NaCl Content), to convert it to water suitable for irrigation (TDS<1000 ppm) was investigated in this work.The results show that the magnetic flux from our designed electrical magnate in the range of (0.013- 0.08) Tesla and 30 minut
... Show MoreAim: The reduction in the amount of marginal bone is the most important demand for the long term success of dental implants. This prospective clinical study was aimed to investigate the marginal bone loss of early loaded SLActive implants with different dimensions and surgical approaches. Materials and methods Fifteen patients aged from 18 to 60 years were divided into 2 groups (flapped and flapless approach) that underwent delayed implant placement protocol with SLActive implants. The marginal bone level was estimated by cone-beam computed tomography during three different periods: preoperatively, 8 weeks after surgery and 24 weeks after loading of the prosthesis. Results: The mean value of marginal bone level was not significantly chan
... Show MoreWe have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed (LSD) to estimate the parameters an
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We have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed (LSD)
... Show MoreTo find out a simple and efficient equation to estimate maize ear grain weight on farm (in situ), twenty three maize crosses along with two synthetics were grown in the field. On the experimental farm of the Dept. of Field Crop Sci., College of Agric., Univ. of Baghdad, seeds of twenty five maize genotypes were grown in the fall season of 2013 with three replicates. At dough stage of the kernels, five naked ears of each experimental units were measured for length and maximum diameter. This will sum up 125 ears of the trial. The volumes of ears were calculated as cylinder (length× r2× 3.1416). Grain weight of all ears were determined after harvesting and drying to 15% grain moisture. A constant was calculated by dividing ear grain weight b
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