Agtor: an agricultural water management model built in Python 3

Project to predict production quantities for a given dataset using Machine Learning algorithms.

My personal GitHub profile repo!

Plant disease detection bot

AgriVision is a project designed to identify cultivatable land for agricultural purposes using real-time satellite imagery and advanced image processing techniques. The project leverages an R Shiny app to provide a user-friendly interface where users can upload satellite images, view processed results, and receive precise crop suitability recommend

Modeling the budding process of the beet plant with neural networks

An Optimal Crop Allocation Model constructed using Operational Research

Innovation in agriculture productivity and gaining time (Smart irrigation system)

A toolkit for geospatial crop simulations

Harmonize heterogenous spatiotemporal gridded agriculture-related datasets. Part of a larger ongoing project to monitor land and water use by combining irrigation and gridded data via remote sensing data with machine learning.

Predicting the price of agricultural

A machine learning application that detects diseases in cotton plants using image analysis and convolutional neural networks (CNNs). Built with Flask for a user-friendly interface and fast, accurate disease classification.

An interactive introduction to modelling using the life-cycle of an agricultural weed as an example.

Projeto de Ciência de Dados para a estimativa de tempo de ordens de serviço, voltado à área agrícola. Desenvolvido em Python, através do Google Colab

Hey, interested in our project. Visit our demo

A demonstration platform designed for agricultural extension services, facilitating outreach and providing a hub for seeking assistance.

Predicting the best suitable crop based on various parameters. The model is based on Random Forest Algorithm

Aquacrop-OSPY implementation to analyze the effects of changing irrigation schedules and irrigation depths on key crop parameters.