The current study dealt with the effect of water extract of pomegranate peel plant on Oscillatoria amoena growth that isolated from Diwaniya river, The effect of the pomegranate extract was measured by calculating the total number of cells and the absorbance values of the alga. Three concentrations were used 3.5, 7 and 14 mg/ml from extract of pomegranate fruit peel in addition to the control group. The results showed that exposing the alga to concentrate 14 mg/ml led to lower growth sharply, while the rest of the concentrations 3.5 and 7 mg/ml also decreased the growth gradually. The absorbance values showed a decline similar to the number of cells during the period of the exposure.
The apricot plant was washed, dried, and powdered after harvesting to produce a fine powder that was used in water treatment. created an alcoholic extract from the apricot plant using ethanol, which was then analysed using GC-MS, Fourier transform infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using an alcoholic extract. FTIR, UV-Vis, SEM, EDX, and TEM are used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with apricot extract and powder were employed to clean polluted water. Firstly, 2 g of zinc nanoparticles were used with 20 ml of polluted water, and the results were Tetra 44% and Levo 32%; after
... Show MoreAgriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes. The data augmentation techniques have been used. In addition to dropout and weight reg
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