The present study aimed to determine the genetic divergence of seven maize genotypes (Al-Maha, Sumer, Al-Fajr, Baghdad, 5018, 4 × 1 single hybrid, and 4 × 2 single hybrid) under two varied levels of nitrogen fertilization (92 and 276 kg N ha-1). The experiment occurred in 2022 in a randomized complete block design (RCBD) with a split-plot arrangement and three replications at the College of Agricultural Engineering Sciences, University of Baghdad, Iraq. The nitrogen fertilization levels served as main plots, with the maize genotypes allocated as the subplots. The results revealed that genetic variance was higher than the environmental variance for most traits, and the coefficient of phenotypic variation was close to the genetic variation coefficient under the two levels of nitrogen fertilization. Heritability (broad sense) at the 92 kg N ha-1 (N1 level) was the highest for traits. i.e., ear height, grains per row, grains per ear, individual plant yield, yield per unit area, days to 50% male flowering, leaf area, ear length, rows per ear, and 100-grain weight, with values of 92.556%, 90.760%, 90.123%, 95.007%, 95.007%, 88.976%, 89.974%, 88.748%, 85.521%, and 89.690%, respectively. For the N level of 276 kg ha-1 (N2 level), the heritability in a broad sense was high for the traits, viz., days to 50% male flowering (91.546%), plant height (96.150%), ear height (91.038%), ear length (92.454%), individual plant yield (98.108%), yield in the unit area (98.108%), and plant dry weight (85.488%). The cluster analysis divided the maize genotypes into four and five cluster groups under the nitrogen fertilization level of 92 and 276 kg N ha-1, respectively. These different groups of maize genotypes could be due to the genetic divergence among the genotypes resulting from their varied genetic makeup and origin.
RA is a complex chronic disease, primarily affects the lining of the synovial joints and can cause progressive disability, premature death, and socioeconomic burdens. The clinical manifestations of symmetrical joint involvement include arthralgia, swelling, redness, and even limiting the range of motion. The pathogenesis is not known therefore the study included Rheumatoid arthritis (RA) is one of systemic inflammatory diseases that characterized by a progressive disabling course. The study included patients suffering from RA and as healthy controls. immunological and genetic factor were evaluated in each subject by using serum level of cytokine and genetic factor. The etiopathology of the disease is not well known for this reason the study
... Show MoreBackground. Gene polymorphisms affect etanercept’s pharmacokinetics, pharmacodynamics, and side effects. This effect is evidenced by the extensive genetic variation in the drug’s targets. Objectives. This study aims to find the association between different genotypes of the promoter region of the TNF-α gene at -308G/A(rs1800629), -857C/T(rs1799724), -863 C/A(rs1800630), -1031 T/C (rs1799964), -806 C/T (rs4248158) and -376 G/A (rs1800750) and the side effects of ETN that occurred to Iraqi RA patients. Method. The trial included patients with rheumatoid arthritis who had been using ETN for at least six months. The participants were from the Baghdad Teaching Hospital Rheumatology Unit. The PCR was sequenced to determine the polymo
... Show MoreThe impact of a proposal for the curriculum dictated by some of the barriers to the development of motor skillsA. M. D. Huda Ibrahim RezoukiM. M. Susan Salim DawoodIs the childhood of the most important and most fertile stage of basic education because of their significant impact in building a base on which the stated origin of sound in the early stages older age because the baby at this stage be very vulnerability to environmental factors different surroundings in which to leave their mark on his life in the stages of life other.The Gymnastics of sports long-term training, which begins between the ages very early relative to the rest of other games to reach the stage of the tournament from the age of 13-17 years almost to the women, this a
... Show MoreIn the past two decades, maritime transport traffic has increased, especially in the case of container flow. The BAP (Berth Allocation Problem) (BAP) is a main problem to optimize the port terminals. The current manuscript explains the DBAP problems in a typical arrangement that varies from the conventional separate design station, where each berth can simultaneously accommodate several ships when their entire length is less or equal to length. Be a pier, serve. This problem was then solved by crossing the Red Colobuses Monkey Optimization (RCM) with the Genetic Algorithm (GA). In conclusion, the comparison and the computational experiments are approached to demonstrate the effectiveness of the proposed method contrasted with other
... Show MoreText based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.
... Show MoreAbstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization
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