Agricultural Technology

State partnership advancing technologies that convert organics and waste into fuels and value-added products.

Developing low-cost sensing networks to monitor dairy farm greenhouse gas emissions and support data-driven management decisions.

Develops spore-trapping methods to detect airborne fungal pathogens threatening horticultural nurseries and maple production in Washington.

Evaluating biomass-derived pyrolysis oils as sustainable pesticide alternatives for major Washington crop pest vectors.

Develops machine learning to predict soil organic carbon using satellite imagery for improved carbon incentive accounting.

Integrating forecasting, remote sensing, and smart markets to improve water allocation and drought resilience in western agriculture.

Develops machine learning to predict soil organic carbon using satellite imagery for improved carbon incentive accounting.

State partnership advancing composting, anaerobic digestion, and waste-to-fuels technologies across Washington.

Limited observations require agricultural AI to combine existing knowledge, uncertainty, and more strategic data collection.

Machine learning and field observations improve tillage maps across diverse eastern Washington cropping systems.

Machine learning and satellite data enable scalable, uncertainty-aware soil carbon measurement to support outcome-based agricultural incentive program

Eleven-video series equips agricultural professionals to understand, assess, and communicate AI in sustainable agriculture.

Progress report advances small-data machine learning to predict soil organic carbon using satellite, management, and environment data.

Agent-based modeling simulates irrigation water trading under drought to evaluate efficient agricultural water market designs.

Smart market incentives can encourage water trades that reduce environmental impacts while maintaining efficient water allocation.

Open-source smart market algorithm reduces water trading costs and improves allocation under regulatory constraints.

Field-level economic modeling framework evaluates water trading policies and environmental outcomes under water scarcity.

Satellite-integrated crop modeling improves field-scale evapotranspiration and irrigation demand estimates in Washington.

Integrating crop models and NDVI improves field-scale evapotranspiration estimates for irrigation management.

New tools improve crop water requirement estimates, drone ET mapping, and irrigation efficiency analysis statewide.

Strong ENSO signals in select basins increase seasonal drought forecast accuracy and economic value.

Research highlight summarizing innovations in forecasting, remote sensing, and smart water markets in the Columbia River Basin.

Assessment of seasonal forecast accuracy for fertilizer and drought management decisions in the Pacific Northwest.

Research highlight summarizing innovations in forecasting, remote sensing, and smart water markets in the Columbia River Basin.

Satellite-based machine learning achieved 87% accuracy in mapping tillage practices across eastern Washington.

Technical assessment evaluating climate benefits and economic feasibility of small-scale biochar systems in Pacific Northwest agriculture.

Literature review assesses emerging plastics recycling technologies and strategies to improve Washington waste management outcomes.

Developing Method 25.3 capability to measure VOC emissions from Washington composting systems.