Crop yields, weather patterns, farm management
Soil moisture, temperature, and nutrient levels
This dataset provides detailed, timestamped IoT sensor readings for crop health monitoring, including soil moisture, temperature, and nutrient levels, along with device status and geolocation. Designed for precision agriculture, it enables predictive analytics, real-time alerts, and data-driven crop management across diverse field environments.
Farm location, crop type, yield quantity, area harvested
This dataset provides detailed annual and seasonal crop yield records from small-scale local farms, including farm location, crop type, yield quantity, area harvested, and farming practices. It enables comprehensive analysis of agricultural productivity, sustainability trends, and supply chain optimization for local food systems.
Operational metrics, location data, and maintenance indicators
This dataset provides detailed, time-stamped telemetry logs from smart agricultural machinery, including operational metrics, location data, and maintenance indicators. It enables advanced analytics for usage patterns, predictive maintenance, and farm management optimization, supporting both operational and strategic decision-making in precision agriculture.
Animal demographics, health readings, interventions, and outcomes
This dataset provides comprehensive records of livestock veterinary checks, including animal demographics, health readings, interventions, and outcomes, along with farm and veterinarian details. It is ideal for predictive modeling of animal health, regulatory compliance reporting, and farm management analytics. The flat schema ensures compatibility with a wide range of analytical and reporting tools.
Region, crop type, disease specifics, severity, and estimated impact
This dataset provides detailed synthetic records of crop disease outbreaks, including region, crop type, disease specifics, severity, and estimated impact. It is structured for advanced risk modeling, disease prediction, and spatial-temporal analysis, making it invaluable for AgriTech research, policy planning, and precision agriculture solutions.
Soil moisture, crop health indices, equipment status
This dataset provides granular, time-stamped IoT sensor readings from precision agriculture systems, including soil moisture, crop health indices, equipment status, and environmental conditions. It enables spatial and temporal analysis for AgriTech tool development, machine learning for yield optimization, and operational monitoring across farms and fields. The comprehensive structure supports research, analytics, and real-world deployment scenarios in smart farming.
Spatial coordinates, device metadata, and crop context
This dataset provides granular, time-stamped sensor readings from precision agriculture deployments, including spatial coordinates, device metadata, and crop context. It enables advanced analytics for crop yield optimization, anomaly detection, and sustainability research, making it highly valuable for agri-tech startups and researchers focused on smart farming solutions.
Agronomic, environmental, and management features such as soil properties
This dataset provides comprehensive field-level crop yield records, including agronomic, environmental, and management features such as soil properties, fertilizer and pesticide usage, irrigation type, and weather data. Designed for agtech product development and predictive modeling, it enables robust analysis of yield drivers, optimization strategies, and spatial variability across agricultural regions.
Operational parameters, location, and diagnostic error codes
This dataset provides detailed, time-stamped telemetry and fault code logs from farm equipment, including operational parameters, location, and diagnostic error codes. It enables predictive maintenance, downtime reduction, and operational analytics by linking machine health, usage, and fault events to specific equipment and operators. The data is ideal for building machine learning models to forecast failures and optimize maintenance schedules.
Daily synthetic records of market prices for major crops across multiple regions
This dataset provides daily synthetic records of market prices for major crops across multiple regions, enriched with weather conditions and demand/supply shock indicators. It enables detailed analysis of price fluctuations, the impact of environmental and market events, and supports forecasting and agri-finance risk assessment. The dataset is ideal for researchers, policymakers, and financial institutions focused on agricultural markets.
High-resolution synthetic drone imagery of agricultural fields
This dataset contains high-resolution synthetic drone imagery of agricultural fields, each image enriched with detailed metadata, geolocation, crop type, and expert-annotated features such as weeds, diseases, and crop health indicators. It supports advanced analytics in precision agriculture, enabling crop health monitoring, automated feature detection, and field management optimization. The dataset is ideal for developing and benchmarking computer vision models and agronomic decision support tools.
22 cols
Field location, crop type, season, weather conditions
This dataset provides detailed field-level crop yield estimates, including field location, crop type, season, weather conditions, and input usage such as fertilizer and irrigation. It enables robust yield prediction, agronomic benchmarking, and optimization of farming practices by supporting both estimated and actual yields. The comprehensive structure is ideal for agronomy research, precision agriculture, and machine learning applications in crop management.
High-quality, synthetic annotations of crop images
This dataset provides high-quality, synthetic annotations of crop images, each labeled with disease type and severity level, along with optional metadata such as location and annotator details. It is ideal for training and benchmarking computer vision models for early crop disease detection, supporting agricultural research, precision farming, and disease monitoring initiatives.
Forecast methods, timing, and variance calculations
This dataset provides detailed logs comparing projected and actual crop yields at the field level, including forecast methods, timing, and variance calculations. It enables precise analysis of forecast accuracy, supports agricultural planning, and helps identify patterns or anomalies in yield prediction. The data is ideal for farm management optimization, agronomic research, and improving predictive models.
Field location, crop type, and actionable storage recommendations
This dataset provides granular records of moisture levels at harvest for a variety of crops, including field location, crop type, and actionable storage recommendations. It enables farmers, agronomists, and supply chain managers to optimize post-harvest storage, reduce spoilage, and analyze environmental or operational factors influencing crop quality. The dataset is ideal for precision agriculture, storage planning, and research into best harvest practices.
Product details, application rates, targeted pests, applicator credentials
This dataset provides detailed records of pesticide application events on agricultural fields, including product details, application rates, targeted pests, applicator credentials, and environmental conditions. It supports regulatory compliance, traceability, and effective pest management analysis, making it valuable for farmers, agronomists, and regulatory agencies.
28 cols
Farm yield monitoring, capturing crop types, planting and harvest dates
This dataset offers detailed records of farm yield monitoring, capturing crop types, planting and harvest dates, input usage, and key environmental factors at the field level. It enables agricultural businesses to analyze productivity, optimize input application, and make data-driven decisions for improved crop management and planning. The dataset is ideal for yield forecasting, resource optimization, and precision agriculture analytics.
Columns and codes found in the sample rows of all 89 agriculture datasets.
One sentence in. A dataset with that pattern out.
| irrigated | soil_type | rainfall_mm | yield_t_ha |
|---|---|---|---|
| yes | Clay loam | 612 | 9.8 |
| no | Sandy loam | 580 | 6.9 |
| yes | Silt | — | 10.2 |
| no | Chalk | 640 | 7.1 |
A pattern you asked for Everything else