Soil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in predicting the Sr and Cr elements using spectroscopy, with coefficients R2 = 0.73 and RMSE = 63.8 for the determination, and R2 = 0.60 and RMSE = 16.4 for Cr, respectively. This research validates the detection of heavy metal contamination using reflectance spectroscopy. Results of the current study proved that some heavy elements have spectral features become either when their concentrations low or high, such as Cr, Sr, Cu and Zn. The current study opens new possibilities for studying these elements using remote sensing in the future.
The purpose of the study is the city of Baghdad, the capital of Iraq, was chosen to study the spectral reflection of the land cover and to determine the changes taking place in the areas of the main features of the city using the temporal resolution of multispectral bands of the satellite Landsat 5 and 8 for MSS and OLI sensors respectively belonging to NASA and for the period 1999-2021, and calculating the increase and decrease in the basic features of Baghdad. The main conclusions of the study were, This study from 1999 to 2021 and in two different seasons: the Spring of the growing season and Summer the dry season. When using the supervised classification method to determine the differences, the results showed remarkable changes. Where h
... Show More12 membered Schiff base macrocyclic ligands, 6,7,14,15-tetra phenyl-1,2,3,4, 4a,8a, 9,10, 11,12, 12a,16a-dodecahydro dibenzo [b,h] [1,4,7,10] tetraazacyclododecine L1, and 14 membered Schiff base macrocyclic ligands, 6,8,15,17-tetramethyl-1,2,3,4, 4a,7,9a, 10,11,12,13,13a,16,18a-tetra decahydro dibenzo[b,i] [1, 4,8,11] cyclotetradecine tetraaza L2, 7,16-bis(2,4- dichloro benz ylidene)-6,8,15,17-tetra methyl-1,2,3,4, 4a,7,9a, 10, 11,12, 13, 13a,16,18a-tetra deca hydro dibenzo [b,i] [1,4,8,11] tetra azacyclo tetra decine L3 and 6,8,15, 17-tetramethyl-1,2,3, 4,4a,9a,10, 11,12,13,13a,18a-dodecahydro dibenzo [b,i] [1,4,8, 11] tetraazacyclo tetradecine (7,16-diylidene) bis(methanylyli dene) bis (N,N-dimethylaniline) L4 were synthesized by condens
... Show MoreThis paper presents the synthesis and study of some new mixed-ligand complexes containing nicotinamide(C6H7N2O) symbolized (NA) and phenylalanine (C9H11NO2)symbolized (pheH)] with some metal ions. The resulting products were found to be solid crystalline complexes which have been characterized by :Melting points, Solubility, Molar conductivity. determination the percentage of the metal in the complexes by flame(AAS), magnetic susceptipibility, Spectroscopic Method [FT-IR and UV-Vis]. The proposed structure of the complexes using program , chem office 3D(2006) . The general formula have been given for the prepared complexes : [M(NA)2(phe)]cl M(II): Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) & Hg(II)). NA = Nicotinamide= C6
... Show MoreThis paper presents the synthesis and study of some new mixed-liagnd complexes containing nicotinamide(C6H7N2O) symbolized (NA) and phenylalanine (C9H11NO2)symbolized (pheH)] with some metal ions. The resulting products were found to be solid crystalline complexes which have been characterized by :Melting points, Solubility, Molar conductivity. determination the percentage of the metal in the complexes by flame(AAS), magnetic susceptipibility, Spectroscopic Method [FT-IR and UV-Vis]. The proposed structure of the complexes using program , chem office 3D(2006) . The general formula have been given for the prepared complexes :[M(NA)2(phe)]cl M(II): Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) & Hg(II) . NA = Nicotinamide= C6H7N2O Phe -
... Show MoreA new ligand [N-(4-nitrobenzoylamino)-thioxomethyl] phenylalanine is synthesized by reaction of 4-nitrobenzoyl isothiocyanate with phenylalanine (1:1). It is characterized by micro elemental analysis (C.H.N.S.), FT-IR, (UV-Vis) and 1H and 13CNMR spectra. Some metals ions complexes of this ligand were prepared and characterized by FT-IR, UV-Visible spectra, conductivity measurements, magnetic susceptibility and atomic absorption. From results obtained, the following formula [M(NBA)2] where M2+ = Mn, Co, Ni, Cu, Zn, Pd, Cd and Hg, the proposed molecular structure for these complexes as tetrahedral geometry, except copper and palladium complexes are have square planer geometry.
A new ligand [N-(4-nitrobenzoylamino)-thioxomethyl] phenylalanine is synthesized by reaction of 4-nitrobenzoyl isothiocyanate with phenylalanine (1:1). It is characterized by micro elemental analysis (C.H.N.S.), FT-IR, (UV-Vis) and 1H and 13CNMR spectra. Some metals ions complexes of this ligand were prepared and characterized by FT-IR, UV-Visible spectra, conductivity measurements, magnetic susceptibility and atomic absorption. From results obtained, the following formula [M(NBA)2] where M2+ = Mn, Co, Ni, Cu, Zn, Pd, Cd and Hg, the proposed molecular structure for these complexes as tetrahedral geometry, except copper and palladium complexes are have square planer geometry.
Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct
The study was aimed to evaluate the marketing efficiency of dry Onion crop in Salah al-Deen, as estimate the impact of some quality and quantity factors in the efficiency of marketing process of crop using Tobit regression model. The average marketing efficiency of the research sample was 71.3686%. The marketing margins differed according to the marketing channel followed in marketing the crop. The qualitative and quantitative variables in the model are productivity, family size, distance from the market, educational level. The estimated model revealed that a variable productivity is the most important and influential in marketing efficiency, followed by the variable of the distance between the farm and the market, then the variable
... Show MoreThe study was aimed to evaluate the marketing efficiency of dry Onion crop in Salah al-Deen, as estimate the impact of some quality and quantity factors in the efficiency of marketing process of crop using Tobit regression model. The average marketing efficiency of the research sample was 71.3686%. The marketing margins differed according to the marketing channel followed in marketing the crop. The qualitative and quantitative variables in the model are productivity, family size, distance from the market, educational level. The estimated model revealed that a variable productivity is the most important and influential in marketing efficiency, followed by the variable of the distance between the farm and the market, then the variable
... Show MoreThis research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being
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