In this work, silver nanoparticles (AgNPs) were biosynthesized from leaves of Ziziphus mauritiana Lam. jujube plant in Iraq and tested against fungal pathogens. Extract of leaves of Z. mauritiana mixed with 10-3 M AgNO3exposed to slight sunlight for 3 days. Characterization of AgNPs was done using UV-visible spectroscopy, SPM (scanning probe microscopy) and atomic force microscopy (AFM). The change of solution color from pale brown to dark brown and the exhibited maximum peak at 445 nm accepted as an indicator to biosynthesized AgNPs. Aqueous extract of Ziziphus mauritiana is considered as biological reduced and stabilized agent for Ag+ to Ag0. AFM showed the formation of irregular shapes of AgNPs. The biosynthesized silver nanoparticles ha

Anchusa strigosa - prickly alkanet from Boraginaceae grows in roadsides, and fields of a broad range of habitats from mediterranean woodlands, to steppe vegetation, to true desert. It is commonly known as" him him" or "lisan al thawr". Anchusa can withstand hard weather conditions and hence is widely cultivated. The color of its flowers can range from pure white to deep cobalt blue. Various parts of A. strigosa are used in traditional medicine for treating several diseases or symptoms, such as abdominal pain, bronchitis, cough, and diarrhea. The goal of this study was to examine the cytotoxic effect of the crude extract of A. strigosa roots and leaves and their fractions against various tumor cell lines: adenoc

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

The experiment was conducted to study the effect of leaves extract of Salvia sclarea , Rosmarinus officinalis and Thymus vulgaris with 10% and 30% concentration on germination of seeds and growth of seedlings . The effect of these extracts on infection percentage of seeds decay and surface growth of Rhizoctonia solani . The results showed that the three extracts effected significantly to reduced percentage of seeds germination, acceleration of germination , promoter indicator , infection percentage of seeds decay and surface growth of R. solani especially in 30% concentration .