Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

In latest decades, genetic methods have developed into a potent tool in a number of life-attaching applications. In research looking at demographic genetic diversity, QTL detection, marker-assisted selection, and food traceability, DNA-based technologies like PCR are being employed more and more. These approaches call for extraction procedures that provide efficient nucleic acid extraction and the elimination of PCR inhibitors. The first and most important stage in molecular biology is the extraction of DNA from cells. For a molecular scientist, the high quality and integrity of the isolated DNA as well as the extraction method's ease of use and affordability are crucial factors. The present study was designed to establish a simple, fast

Extraction and Description of Urease Enzyme Produced from Staphylococcus saprophyticus and study of its effect on kidney and bladder of white mice

ABSTRACT This study developed two adsorbents for extracting salbutamol sulphate (SAS) from water and urine samples after derivatisation with 2-aminobenzothiazole as a colour reagent. These adsorbents include cetylpyridinium chloride surfactant (CPC) modified silica and alumina-coated magnetite nanoparticles (Fe3O4/SiO2/CPC and Fe3O4/Al2O3/CPC). The derivatisation of SAS with the colour reagent resulted in an orange azo dye with maximum adsorption wavelengths of 443.0 nm. UV–Vis spectroscopy was used to identify the target analyte following the magnetic solid-phase extraction (MSPE) method. Under optimal conditions, the concentration ranges of 0.03–5.00 µg/mL and 0.05–6.00 µg/mL with good linearity (˃ 0.99), the detection limi

Liquid-Liquid Extraction of Cu(II) ion in aqueous solution by dicyclohexyl-18-crown-6 as extractant in dichloroethane was studied .The extraction efficiency was investigated by a spectrophometric method. The reagent form a coloured complex which has been a quantitatively extracted at pH 6.3. The method obeys Beer`s law over range from (2.5-22.5) ppm with the correlation coefficient of 0.9989. The molar absorptivity the stoichiometry of extracted complex is found to be 1:2. the proposed method is very sensitive and selective.