The objective of this study was to investigate the drought stress and plant density possibility on water productivity and grain yield of maize (Zea mays L.) (Planting Baghdad 3 synthetic varieties), Field experiment was conducted at Abu Ghraib Research Station (Baghdad) during spring and Autumn seasons of 2016 using a randomized complete block design arranged in split plot with three replications. Three irrigation treatment included: irrigation after depletion 50% of available water (T1), irrigation after depletion 75% of available water (T2) and irrigation after depletion 90% of available water (T3) in the main plots and three plant density which were: 1 seeds hill-1 (D1) giving a uniform plant density of 66666 plants ha-1 , 2 seeds hill1

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect beco

Preparation of Carboxy Methylated mPEG-Block-(4-Dodecyl Anilide) Copolymers and Their Visco Metric and Surface Tension Properties in THF

Simultaneous determination of Furosemide, Carbamazepine, Diazepam, and Carvedilol in bulk and pharmaceutical formulation using the partial least squares regression (PLS-1 and PLS-2) is described in this study. The two methods were successfully applied to estimate the four drugs in their quaternary mixture using UV spectral data of 84synthetic mixtures in the range of 200-350nm with the intervals Δλ=0.5nm. The linear concentration range were 1-20 μg.mL-1 for all, with correlation coefficient (R2) and root mean squares error for the calibration (RMSE) for FURO, CARB, DIAZ, and CARV were 0.9996, 0.9998, 0.9997, 0.9997, and 0.1128, 0.1292, 0.1868,0.1562 respectively for PLS-1, and for PLS-2 were 0.9995, 0.9999, 0.9997, 0.9998, and 0.1127, 0.

This study was conducted in the poultry fields of the College of Agricultural Engineering Sciences / University of Baghdad from 10/15/2021 to 11/25/2021.To know the effect of adding different levels of Ganoderma lucidum to broiler diets on productive performance. 200 unsexed (Ross 308) chicks of one day age with a starting weight of (40) g were used. The chicks were randomly distributed into four treatments and 50 birds. One treatment included five replicates (10 birds/replicate), and the experimental treatments was as follows: T1, T2, T3, T4, and the percentages of adding reishi mushroom were 0, 0.5, 1, and 1.5 g/kg of feed, respectively, and the birds were fed on three starter diets, growth and final diets, The results of this stu

A factorial experiment was conducted at the College of Education for Pure Sciences Ibn al Haitham/University of Baghdad for the 2023 growing season to study the effect of the biofertilizer represented by the mycorrhizae vaccine and the NPK Nano fertilizer on some indicators of vegetative and root growth, yield, and volatile oil production of the basil plant, Ocimum basilicum L., the experiment included two factors. The rst factor was mycorrhizae inoculum at 2 levels: 0 (no addition) and an addition of 25 g plant–1, as the seeds were inoculated upon planting. The second factor was spraying the plant’s shoots with NPK Nano fertilizer at four levels (0, 0.5, 1, 1.5) g l–1. The results showed a signicant eect of the treatment of inocula

Research was conducted to study the effect of proline and aspirin with 10 and 20 ppm on seed germination and seedling growth of Lycopersicon esculentum and the effect of surface growth of Fusarium oxysporum. The results showed that the proline and aspirin effected significantly to decreased percentage of seed germination, acceleration of germination, promoter indicator, elongation speed of radical and plumule and also the infection percentage of seed decay and surface growth of Fusarium oxysporum was reduced significantly.

Research was conducted to study the effect of proline and aspirin with 10 and 20 ppm on seed germination and seedling growth of Lycopersicon esculentumand the effect of surface growthof Fusarium oxysporum.The results showed that the proline and aspirin effected significantly to decreased percentage of seed germination, acceleration of germination, promoter indicator, elongation speed of radical and plumule and also the infection percentage of seed decay and surface growth of Fusarium oxysporumwas reduced significantly.

The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values ​​of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend buil