agriculture-data

Agriculture data interoperability toolkit for .Net

Set of Machine Learning Algorithms developed with the aim of determining health states of different types of crops

Open Intelligence for Every Farm - Monitor crop health with satellite imagery, detect anomalies early, and make data-driven decisions.

Data in Climate Resilient Agriculture (DiCRA) is a collaborative digital public good which provides open access to key geospatial datasets pertinent to climate resilient agriculture. These datasets are curated and validated through collaborative efforts of hundreds of data scientists and citizen scientists across the world.

Centroid-UNet is deep neural network model to detect centroids from satellite images.

Android app for plant disease identification using ML

The Smart Agriculture Advisory System is an application designed to provide farmers with personalized advice on crop management, pest control, and irrigation scheduling. By leveraging machine learning models, the system analyzes various environmental and soil parameters to recommend the most suitable crops for cultivation.

[ACL 2025] SeedBench: A Multi-task Benchmark for Evaluating Large Language Models in Seed Science🌾

Predicting rice field yields through the integration of Microsoft Planetary satellite images, meteorological data, and field information in the 2023 EY Open Science Data Challenge - Crop Forecasting.

ADAPT Framework plugin for ISOXML

Standard data schema for agriculture interoperability

This repository contains 5 different YOLO models enriched with leaf segmentation-focused data.

The ISO 11783 standard specifies a serial data network for control and communications on forestry and agricultural machines. Every control function in an ISOBUS network has a unique NAME ( defined in 11783-5) that contains information about the manufacturer code, the device class and other common fields. The information is encoded in a byte valu…

AI disease detection and prediction for humans, plants, and animals. Complete ML project with custom training, offline operation, no API keys. Detect diseases from images using deep learning and computer vision. Open-source disease detection system for healthcare, agriculture, and veterinary applications. Full code and deployment guides.

The agridatasets package provides a curated collection of agricultural, agronomic, and livestock datasets for data analysis, statistical modeling, and machine learning research.

CartoBio API

This repository includes code for constructing a variety of agricultural development indicators from household survey microdata (primarily LSMS-ISA surveys) as well as documentation for construction decisions across instruments.

Computer vision and satellite imagery analysis for precision agriculture. Detects crop diseases, monitors soil health, predicts yields, and optimizes irrigation using drone imagery and multispectral data.

Harvest data from Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) part of the Australian Department of Agriculture, Fisheries and Forestry and the Australian Bureau of Statistics (ABS) for your work in R

Cleaned and constructed indicators based on the LSMS-ISA Data. Source code for producing the estimates is available at https://github.com/EvansSchoolPolicyAnalysisAndResearch/LSMS-Agricultural-Indicators-Code