AgML aspires to identify key research gaps and opportunities at the intersection of agricultural modelling and machine learning research and support enhanced collaboration and engagement between experts in these disciplines.

A basic simulation of a coffee operation.

This repository houses scripts to accompany Crawford et al. 2021 (Ecological Applications), in which we apply a range of biodiversity indices to an agricultural land-use prioritization model, using Zambia as a case study to investigate how variation in how biodiversity is represented affects the results of land-use prioritization analyses.

Course project for the final B.Math career course consisting of a research project about agricultural soil sampling modeling for applying data analysis efficiently to agricultural soils.

Simulate the coupled evolution of a human population and land conversion for agriculture. Explore the agricultural strategies leading to sustainability or collapse.

enhancing the agricultural value chain by offering farm inputs, engaging in rice processing, facilitating market linkages, providing logistics solutions, and streamlining warehousing operations

AI-Assisted Plant Disease Detection and Management System is a deep learning-based solution designed to assist farmers and agricultural experts in identifying and managing plant diseases efficiently.