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.

Machine Learning based Crop Yield Prediction

This data package provides a spatially and temporally broad, multivariate dataset that quantifies trade-offs and co-benefits of tillage management in North American row-crop systems. Treatment-level means are provided for multiple ecosystem services, including crop yield, soil organic carbon (SOC) stocks, and N2O emissions, with detailed metadata.

Crop yield prediction using ML on real-world weather, pesticide, and agricultural data.

Plan Disease Prediction Using Machine Learning Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

XAI for soybean crop yield prediction using ConvLSTM

Reproducible agronomic meta-analysis toolkit for sulfur fertilizer yield effects and nutrient co-application

Flask web app that predicts crop yield using CatBoost, XGBoost, and LSTM models.

AI-powered crop yield intelligence for Northeast India. Predicts district-level yields for 5 crops across 95 districts and 8 NE states using XGBoost + LSTM models trained on real Open-Meteo weather, MODIS/GEE satellite NDVI, and ERA5 soil moisture data. Built with FastAPI + Next.js 14 + Docker on Oracle Cloud. Phase 9 complete. Live demo available.

全国大学生统计建模大赛 · 遥感玉米产量预测 — Detrending+LSTM+CNN+XGBoost · R2=0.8236

Crop Yield Prediction - Predictive Systems project in AI / ML / GenAI for CSEProjects360 final year project catalog.

The Crop Yield Prediction System is a machine learning-based web application built with Flask that predicts crop yield based on environmental and agricultural inputs.

District level seasonal crop yield forecast for Germany.

Sustainable Crop Yield Prediction using Machine Learning

Crop yield regression from NDVI and multispectral satellite bands

CropFusionNet: An Interpretable Deep Learning Framework for Probabilistic Crop Yield Forecasting

Description: 🌱 Smart Farm Yield Prediction Dashboard using PySpark, Streamlit, and Machine Learning for crop yield forecasting and interactive visual insights.

hsbdc 202526/ A machine learning project forecasting U.S. Food Security Index changes using USDA crop data, FAOSTAT indicators, shock-lag feature engineering, and Random Forest, RidgeCV, and Gradient Boosting models.

Using Docker and Keras to generate competition-worthy Crop Yield Prediction Models | ISTA429 Midterm project for Team X for MCLAS2021