Mohsin Ramay's repositories
Introduction-of-Python-and-Machine-Learning-in-Phytopathology-
Python is a powerful open-source programming language known for its easy-access libraries and framework built for machine learning modeling tasks. With the advancements in plant phenotyping technologies in the past few years, the application of machine learning models in phytopathology for plant disease symptom detection and severity estimation has gained increasing interest. This proposed workshop aims to introduce python language and its environment to plant pathologists and hands-on activities on data manipulation, statistical analysis, and visualization. In addition, this workshop will also introduce machine learning packages and techniques for conducting classification modeling work using datasets from published phytopathological research. This workshop aims to assist plant pathologists in the initial learning curve of a new programming language and motivate them to explore and use python to excel in their research.
Coffee-Leaf-Rust-in-Ethiopia
Coffee leaf rust (CLR) is an economically important coffee disease in Ethiopia. This repository contains the CLR severity data of 31 coffee verities grown under field conditions during three years (2016 – 2018). This compendium also includes the code used for data cleaning, data analysis and visualization of the results.
Remote-sensing-of-Soybean-Sudden-Death-Syndrome
Sudden death syndrome (SDS) is one of the major yield-limiting diseases of soybean in the Midwest. This repository contains SDS foliar severity and incidence data collected from two different experimental locations in Iowa. Also, it has ground-based remote sensing data of SDS that was collected using a handheld multispectral radiometer.
Soft-acaricides-against-honey-bee-mites
Honey bee are important for their products such as honey and bees wax. They are also indispensable in terms of supporting the ecosystem through pollination services. However, the production and function of honey bees is hindered by arthropod pests Varroa destructor that attack bees through their feeding activities. The current study investigates the efficacy of Formic acid, Oxalic acid and Thymol at different concentrations against the Honey bee mites. This repository contains data and commented R scripts that allows reproducing the analysis conducted in the paper.