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Anatomical and physiological traits of broad bean (Vicia faba L.) seedling affected by salicylic acid and salt stress
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A laboratory experiment was carried out at the College of Agriculture University of Baghdad in 2017. The aim was to improve the anatomical and physiological traits of broad bean seedling under salt stress by soaking it in salicylic acid. The concentrations of salicylic acid were 0, 10, and 20 mg L-1 and the electrical conductivity levels were 0, 3, and 6 dS m-1. The complete randomized design was used with four replications. The increasing of salicylic acid concentration up to 10 mg L-1 led to increasing the stem cortex thickness, stem vascular bundles thickness, and root cortex thickness significantly by (34.9,36.7,and 55 μm) respectively, while the treatment of 20 mg L-1 led to decreasing these traits by (28.2, 27.8, and 48.1 μm), compared to control treatment (33.8, 35.9, and 53.8 μm), respectively, and the interaction of studied factors led to increasing those traits up to 10 mg L-1 and then decreased up to 20 mg L-1 of salicylic acid under each level of electrical conductivity. Therefore, it is recommended to soak the broad been seeds with 10 mg L-1 salicylic acid to improve the anatomical traits of seedlings and increase their tolerance to salt stress up to 6 dS m-1.

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Publication Date
Sun Jun 30 2024
Journal Name
Sabrao Journal Of Breeding And Genetics
PHYTOHORMONES, BIO- AND MINERAL FERTILIZERS EFFECTS ON THE GROWTH AND SECONDARY COMPOUNDS OF CHAMOMILE (MATRICARIA CHAMOMILLA L.)
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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Stress Analysis of Guide Rails of Elevators
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The mechanical design of elevator elements is always performed by international standards. The engineer selects the appropriate elements of elevator according to catalogues without knowing scientific details. Therefore, a theoretical analysis is achieved at two operating conditions for guide rails (1) safety gear operation, and (2) running condition with the loads unevenly distributed on the elevator car. The guide rail is considered a continuous beam with variable supports. Then the British code is listed showing the equations used in it.

The theoretical equations showed that guide rails are never subjected to stress in simultaneous combined buckling and bending in the plane, where the bending moment is exerted. It is always a c

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Publication Date
Mon May 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Screening and optimization of a novel gallic acid and tannase production under semi quantitative and quantitative methods
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Abstract<p>Tannin acyl hydrolase as the common name of tannase is an inducible extracellular enzyme that causes the hydrolysis of galloyl ester and depside bonds in tannins, yielding gallic acid and glucose. The main objective of this study is to find a novel gallic acid and tannase produced by <italic>Acinetobacter Baumannii</italic>. A number of optimization steps were followed in order to improve the highest production of gallic acid and tannase. In present study, <italic>A. baumannii</italic> were isolated from ICU burn. <italic>A. baumannii</italic> was examined by microscopic examination, morphological and biochemical assay including oxidase and catalase. The </p> ... Show More
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Publication Date
Tue Jan 01 2013
Journal Name
Al- Mustansiriyah J. Sci.
Synthesis and Characterization of Some Mixed Ligand Complexes of Quinaldic Acid and α-Picoline with Some Metal Salts Basima
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Some metal ions (Mn+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of quinaldic acid (QuinH) and α-picoline (α-Pic) have been synthesized and characterized on the basis of their , FTIR, (U.V-Vis) spectroscopy, conductivity measurements, magnetic susceptibility and atomic absorption. From the results obtained the following general formula has suggested for the prepared complexes [M(Quin)2( α-Pic)2].XH2O where M+2 = (Mn, Co, Ni, Cu, Zn, Cd and Hg), X = 2, X = zero for (Co+2 and Hg+2) complexes, (Quin-) = quinaldate ion, (α-Pic) = α-picoline. The results showed that the deprotonated ligand (QuinH) by using (KOH) coordinated to metal ions as bidentate ligand through the oxygen atom of the carboxylate group (-COO-) and the nitrogen ato

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Publication Date
Thu Oct 01 2009
Journal Name
National Journal Of Chemistry
Synthesis and study of the mixed ligand (phenylalanine and alanine acid)with some transition Ions
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Thispaperpresentsthesynthesisandstudyofsomenewmixed-liagnd complexescontainingtowaminoacids[Alanine(Ala)andphenylalanine(phe)]withsome metals .Theresultsproductswerefoundtobesolidcrystallinecomplexeswhichhave been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity and solubiltyThe proposed structure of the complexes using program , chem office 3D(2000) .The general formula have been given for the prepared complexes :[M(A-H)(phe-H)]M(II): Hg , Mn ,Co , Ni , Cu ) , Zn , Cd(II) .Ala = Alanine acid = C3H7NO2Phe = phenylalanine = C9H11NO2

Publication Date
Fri Jan 16 2009
Journal Name
National Journal Of Chemistry
Synthesis and study of the mixed ligand (phenylalanine and alanine acid) with some transition Ions
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This paper presents the synthesis and study of some new mixed-liagnd complexes containing tow amino acids[Alanine(Ala) and phenylalanine (phe)] with some metals . The results products were found to be solid crystalline complexes which have been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity and solubilty The proposed structure of the complexes using program , chem office 3D(2000) . The general formula have been given for the prepared complexes : [M(A-H)(phe-H)] M(II): Hg , Mn ,Co , Ni , Cu ) , Zn , Cd(II) . Ala = Alanine acid = C3H7NO2 Phe = phenylalanine = C9H11NO2

Publication Date
Mon Jan 01 2007
Journal Name
Al Mustansiriya Journal Of Pharmaceutical Sciences
Synthesis and study of the mixed ligand (phenylalanine and anthranilic acid) with some transition Ions
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This paper presents the synthesis and study of some new mixed-ligand complexes containing anthranilic acid and amino acid phenylalanine (phe) with some metals . The resulting products were found to be solid crystalline complexes which have been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity . The proposed structure of the complexes using program , chem office 3D(2000) . The general formula have been given for the prepared complexes : [M(A-H)(phe-H)] M(II): Hg(II) , Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) . A = Anthranilic acid = C7H7NO2 Phe = phenylalanine = C9H11NO2

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Publication Date
Thu Jan 01 2009
Journal Name
National Journal Of Chemistry
Synthesis and study of the mixed ligand (phenylalanine and alanine acid) with some transition Ions .
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Publication Date
Mon Jan 01 2024
Journal Name
Current Chemistry Letters
Synthesis and characterisation of novel metal-organic frameworks (MOFs) based on zirconium and bicinchoninic acid
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Metal-organic frameworks (MOFs) are a relatively new class of materials of unique porous structures and exceptional properties. Currently, more than 110,000 types of MOFs have been reported among the countless possibilities. In this study, we have synthesised a novel MOF using zirconium chloride as the metal source and 4,4'-dicarboxy-2,2'-biquinoline (bicinchoninic acid disodium salt) as the linker, which reacted in N,N-Dimethylformamide (DMF) solvent. Three preparation methods were employed to prepare five types of the MOF, and they were compared to optimize the synthesis conditions. The resulting MOFs, named Zr-BADS, were characterised using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), microscopy, and

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Publication Date
Mon Apr 27 2026
Journal Name
Applied Fruit Science
Predicting Bitter Orange (Citrus aurantium L.) Maturity by Machine Learning Based on Picking Force in Smart Picker
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Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

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