The alfalfa plant, after harvesting, was washed, dried, and grinded to get fine powder used in water treatment. We used the alfalfa plant with ethanol to make the alcoholic extract characterized by using (GCMass, FTIR, and UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticles. We characterized Zinc nanoparticles using (FTIR, UV, SEM, EDX Zeta potential, XRD, AFM). Zinc nanoparticle with Alfalfa extract and alfalfa powder were used in the treatment of water polluted with inorganic elements such as Cr, Mn, Fe, Cu, Cd, Ag by (Batch processing). The batch process with using alfalfa powder gets treated with Pb (51.45%), which is the highest percentage of treatment. Mn (13.18%), which is the lowe

The alfalfa plant, after harvesting, was washed, dried, and grinded to get fine powder used in water treatment. We used the alfalfa plant with ethanol to make the alcoholic extract characterized by using (GC-Mass, FTIR, and UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticles. We characterized Zinc nanoparticles using (FTIR, UV, SEM, EDX Zeta potential, XRD, AFM). Zinc nanoparticle with Alfalfa extract and alfalfa powder were used in the treatment of water polluted with inorganic elements such as Cr, Mn, Fe, Cu, Cd, Ag by (Batch processing). The batch process with using alfalfa powder gets treated with Pb (51.45%), which is the highest percentage of treatment. Mn (13.18%), which is the

The current study aimed to evaluate the effect of the heavy metals copper, cadmium and cobalt when added individually, in combination and in combination on the growth and reproduction of the aquatic fungus Saprolegnia hypogyna.

Monitoring lotic ecosystems is vital for addressing sustainability issues. The Al-Shamiyah River is the primary source of water for various daily activities in the Al-Shamiyah district. This study assessed the pollution levels of the river by measuring the concentration and distribution of heavy metals—specifically chromium, cadmium, manganese, copper, zinc, and lead—in both the river's water and sediments. The concentrations of heavy metals in the water ranged from 0.05 to 1.44µg/ L for copper (Cu), 1.57 to 7.25µg/ L for manganese (Mn), 0 to 1.7µg/ L for cadmium (Cd), 0.02 to 1.33µg/ L for lead (Pb), 0.08 to 2.74µg/ L for zinc (Zn), and 0.44 to 1.84µg/ L for chromium (Cr). In the particulate phase, the concentrations ranged from

A simple and rapid high performance liquid chromatographic with fluorescence detection method for the determination of the aflatoxin B1, B2, G1 and G2 in peanuts, rice and chilli was developed. The sample was extracted using acetonitrile:water (90:10, v/v%) and then purified by using ISOLUTE multimode solid phase extraction. After the pre-column derivatisation, the analytes were separated within 3.7 min using Chromolith performance RP-18e (100–4.6 mm) monolithic column. To assess the possible effects of endogenous components in the food items, matrix-matched calibration was used for the quantification and validation. The recoveries of aflatoxins that were spiked into food samples were 86.38–104.5% and RSDs were <4.4%. The method was

    The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method) involved using three different solvents which are  absolute ethanol, 50% aqueous ethanol and water  for both extraction methods using room temperature and direct heat respectively. Crude extracts of two tea samples that obtained from two methods were fractionated by using two solvents with different polarity (chloroform and

This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.