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Determine, Predict and Map Soil pH Level by Fiber Optic Sensor
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Abstract<p>Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal. The Kriging method gave a prediction accuracy of 65% while the SVM algorithm gave an accuracy of 80%. The root mean square error (RMSE) was 0.36, 0.16 and the mean absolute error (MAE) was 0.37, 0.13, respectively, for the two methods. These two methods allow the prediction of soil pH and thus the assessment of soils, allowing for easier and more efficient management decisions and sustaining productivity.</p>
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Publication Date
Sat Jan 19 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECT OF TWO HARROWING SYSTEMS ON DECOMPOSITION OF ORGANIC MATTER, SOME SOIL PROPERTIES, GROWTH AND PRODUCTIVITY OF MAIZE
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A field experiment was conducted at Abu-Ghrib during 2013- 2014 season to study the effect of harrowing systems on the decomposition and fermentation on organic matter(OM) when added and mixed with the soil under special technology, as well as its effect on the growth parameters and productivity of (Zea mays L. 5018). The experiment was laid out using factorial randomized complete block design (RCBD) in split-split design with three replications in SCL bare soil with a percent of moisture ranged from 16 – 18 %. The main plots were designated to the two systems of harrowing (Rotary Harrowand Disc Harrow ). The sub main plots were specified for two organic matters ( Sheep manure ,cow manure ) . Data were statistically analyzed, and

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation the Effect of Addition of Plasma Treated Polypropylene Fiber and Silanized Silicon Dioxide Nanoparticles Composite on Some Properties of Heat-Polymerized Polymethylmethacrylate
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Background: Polymethylmethacrylate (PMMA) is the most ‎commonly used m‏aterial in denture construction. This material is ‎far from ideal in fulfilling the‎ mechanical requirements, like low impact and transverse strength and poor thermal conductivity are present in this material. The purpose of this study was to study the effect of addition a composite which include 1%wt silanized silicone dioxide nano fillers (SiO2) and 1wt% oxygen plasma treated polypropylene fiber (PP) on some properties of heat cured acrylic resin denture base material (PMMA). Materials and methods: One hund‏red (100) prepared specimens were divided into five groups according to the tests, each group consisted of 20 specimens and t

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Measuring Uranium in the Soil of Some Area in Missan Governorate/ Iraq
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Concentrations of uranium were measured in this study for twenty soil samples from four areas with different depths (soil surface-20-40-60-80)cm .The study regions include Missan Governorate (Al-Iskan area,Al-Shibbana area ,Hai-Al Moualimin Al Jadied area ,Sector 30 area). The Uranium concentrations in soil samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U-283) with thermal neutrons from (241Am-Be) neutron source that has flux neutron thermal of (5 ×103 n cm-2 s-1). The concentrations values were calculated by a comparison with standard samples. Through out the result, it was found that averages of uranium concentrations in soil samples were as the following : Al - Iskan

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Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
Predicting Wetting Patterns in Soil from a Single Subsurface Drip Irrigation System
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Soil wetted pattern from a subsurface drip plays great importance in the design of subsurface drip irrigation (SDI) system for delivering the required water directly to the roots of the plant. An equation to estimate the dimensions of the wetted area in soil are taking into account water uptake by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, three soil textures namely loamy sand, sandy loam, and loam soil were used with three different types of crops tomato, pepper, and cucumber, respectively, and different values of drip discharge, drip depth, and initial soil moisture content were proposed. The soil wetting patterns were obtained at every thirty minutes for a total time of irrigation equ

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Biological Activity of Levan Produced from Rhizospheric Soil Bacterium Brachybacterium phenoliresistens KX139300
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Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishmanial acti

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Biological Activity of Levan Produced from Rhizospheric Soil Bacterium Brachybacterium phenoliresistens KX139300
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Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishman

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Publication Date
Fri Jan 01 2021
Journal Name
Agrosystems, Geosciences &amp; Environment
Cover crop influence on soil water dynamics for a corn–soybean rotation
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Abstract<p>Crop production is reduced by insufficient and/or excess soil water, which can significantly decrease plant growth and development. Therefore, conservation management practices such as cover crops (CCs) are used to optimize soil water dynamics, since CCs can conserve soil water. The objective of this study was to determine the effects of CCs on soil water dynamics on a corn (<italic>Zea mays</italic> L.)–soybean [<italic>Glycine max</italic> (L.) Merr.] rotation at three soil depths over 3 yr. The study was conducted at the Chariton County Cover Crop Soil Health Research and Demonstration Farm (CCSH) in Missouri. Initial CC establishment occurred in 2012. Volumetric soil water </p> ... Show More
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Publication Date
Mon Nov 24 2025
Journal Name
Scientific Reports
Bearing capacity improvement of medium clay soil using sodium silicate sand columns
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Antagonistic of trichoderma species against some plant pathogenic soil fungi on carnation
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Adhrt all fungal biological control ability Tdhadah less than 2 repel Alaftran Almamradan showed leaky mushroom Biological control is thermally laboratories and different concentrations of 5, 10 and 20% inhibition in the growth of fungus colonies amounted to 3.8 cm and 3.1 and 2.4 respectively in comparison with control 9 cm

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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