This study was conducted at the poultry research station to the office of Agricultural Research / Ministry of Agriculture / during the period 4/1/2016 to 5/5/2016 and 336 one-day-old Ross308 chicks were used, and fed on diets provided with dried dill (Anethum gravelens) at levels 0.4, 0.6 and 0.8% for treatments D2, D3 and D4, respectively, and they were compared with the control treatment D1. Each treatment included three replicates in each replicate contain 28 birds, in order to study the effect of adding different levels of dried dill plant on the productive performance and some characteristics of the carcass for broilers. The results showed a significant increase (p<0.05) in the average body weight at 5 weeks of age for the treatments (D2 and D3) compared to the control treatment D1. The study showed a significant increase (p<0.05) in the rate of weight gain for birds of the treatment in which different percentages of dried dill powder were used compared to the control treatment for the periods (3-5), (0-5) weeks and also feed consumption ratio increased significantly (p<0.05) for treatments D1, D2 and D3 for periods (3-5) and (0-5) compared to treatment D4. These results were reflected on feed conversion ratio, which showed am obvious improvement in the treatments in which dried dill powder was used for all percentages, but the improvement was obvious in the D4 treatment that did not Significantly differ for each of the treatments D2 and D3 compared to the control treatment (D1) during the breeding period .The results had indicated a significant increase (P<0.05) in the percentage of the Brest cut of the birds of treatments D1, D2 and D4 compared to treatment D3, also the study showed a significant increase in liver's weight percentage for birds of D2 treatment compared to other treatments. We conclude from this study the possibility of adding dried dill plant powder to the diet at levels of 0.4 and 0.6% to obtain a positive improvement in the productive performance of meat broilers.
The experiment was carried out at the Field Crops Research Station, College of Agricultural Engineering Sciences - University of Baghdad in Jadiriyah, with the aim of evaluating the performance of partial diallel hybrids and inbred lines of maize and estimating general combining ability(GCA), specific combining ability (SCA) and some genetic parameters. The experiment was carried out in two seasons, spring and fall 2020. Eight inbred lines of maize were used in the study (BI9/834, BSW18, LW/5 L8/844, ZA17W194, Z117W, ZI17W9, ZI7W4), numbered (1,2,3,4,5,6,7,8), It was sowed in the spring season and entered into a cross-program according to a partial diallel crossing system to obtain tw
Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,
... Show MoreApple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin
ABSTRACT Background: Viral hepatitis places a heavy burden on the health care. Large number of patient with bleeding disorders has chronic hepatitis C infection, while few are chronic carriers of hepatitis B virus. Aims of study: evaluate the prevalence of HBV, HCV infection among patient with Von Willebrand disease and to find factors that associated with the chance of getting the infection.
The current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-
... Show MoreThe Ligand 6,6--(1,2-benzenediazo) bis (3-aminobenzoicacid) derived from o-phenylenediamine and 3-aminobenzoicacid was synthesized. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the ligand with the following metal ions (CoII, NiII, CuII and ZnII ) in aqueous ethanol with a 1:1 M:L ratio and at optimum pH. Characterization of these compounds has been done on the basis of elemental analysis, electronic data, FT-IR and UV-Vis, as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). H
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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